bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel visible-infrared image fusion method based on visual enhancement and multiscale decomposition
Authors: Li Lingxiao , Feng Yong , Ma Zezhong 
Published: September 2021

Abstract
Aiming at the problems of low contrast, low signal-to-noise ratio and scattered energy in the field of optical detection and imaging, a visual enhancement and multi-scale decomposition method for fusion of visible and infrared images is proposed based on the visual characteristics of different bands’ image. Firstly, the infrared image with less texture information and low contrast is preprocessed to weaken the background noise and improve the visual contrast. On this basis, the multi-scale image is decomposed by detail preserving filter, and the saliency map of each scale image is obtained by saliency extraction method. Then, the multi-source images of each scale are fused with saliency map, and binary filtering fusion rules are adopted for the regions with salient details while weighted fusion rules are adopted for other regions. Finally, the images of all scale are reconstructed to get better fusion results. The experimental results show that this method can significantly improve the visual contrast of the fused object, and the objective evaluation indexes are superior to other comparison methods.
IGBT lifetime prediction based on EMD-LSTM
Authors: Wang Ziyang , Du Xianjun 
Published: September 2021

Abstract
Aiming at the problem of fatigue failure caused by the cyclic impact of thermal stress and electrical stress during IGBT operation, a long short-term memory (LSTM) network life prediction method based on EMD (Empirical Mode Decomposition) decomposition is proposed. This experiment uses the accelerated aging data set provided by the NASA PCoE laboratory, analyse and select the collector-emitter transient spike voltage as the failure characteristic parameter, and use the EMD algorithm to decompose the original time series into multiple relatively stable and with different characteristic scales the eigenmode function and trend term reduce the complexity of the time series. Through the LSTM network prediction model, the decomposed eigenmode function components and trend items are respectively predicted, and then the prediction results are superimposed to obtain the result. The results show that the prediction accuracy of the EMD-LSTM model is higher, and it can better realize the life prediction of IGBT, and it also has certain reference value for the life prediction of other power electronic devices.
Fault detection observer design in finite-frequency domain for networked interconnected systems
Authors: Guo Haixiao , Chen Xiaoming , Wang Yanping 
Published: September 2021

Abstract
With the development of network technology, information can flow flexibly, and the research of interconnected systems are booming. The article proposes an H
∞ / H
- fault detection observer design means for a networked interconnected system. First, convert a linear networked interconnection systems to linear network systems. Next, the H
− index is accustomed to measuring the worst-case sensitivity to failure and H
∞ norm from ungiven inputs to residuals is accustomed to measure disturbance robustness performance, so that the residuals generated by the designed fault detection observer are sensitive to failures and robust to disturbance in finite-frequency domain. Besides, sufficient conditions of the observer design are derived and transformed by a set of LMIs. Lastly, numerical simulations are provided to demonstrate the correctness and effectiveness of the designed means.
A Test Method for Instructional Software of Evaluation and Exercise Based on Mobile Platform
Authors: Yu Jiujiu , Zhang Jishan , Chen Yun , Wu Ning , Mei Yingying , Zhang Deqing , Zhu Lili , Zhu Canglu , Sheng Yuliang 
Published: September 2021

Abstract
The research is based on the characteristics of instructional software of evaluation and exercise, taking a small examination system for driving license as an example, this study is devoted to exploring a feasible test method for instructional software of evaluation and exercise based on mobile platform. The test method consists of four testing phases of unit and integration testing, functionality testing, comprehensive testing and teaching evaluation which existed research of functionality testing for modern Android mobile Apps is fully used for reference. Furthermore, further work is put forward. Firstly, a special defect management database for bug definition and analysis needs to be established. Secondly, major test points in comprehensive testing phase should be converted to user stories in modern agile testing environment for software exploratory test methods positively.
Malicious Code Detection Method Based on Static Features and Ensemble Learning
Authors: Li Wei , Zhang Chenyi , Zhou Jieying , Wang Dan , Li Nuannuan 
Published: September 2021

Abstract
In recent years, malicious code emerges in endlessly. New types of malicious code evade the traditional malicious code detection technology through polymorphism, shelling, confusion and other ways. In order to solve the challenges brought by various technologies to the research of malicious code detection, in this paper, we propose a malicious code detection method based on static features and ensemble learning. This method extracts the information in the PE header file of malicious code samples as static features, and on this basis, builds a malicious code detection model by using stacking ensemble learning. In order to verify the effectiveness of the model, experiments are carried out on a dataset containing 5000 malicious codes and 4943 benign codes. Experiments show that the classification model based on stacking ensemble learning is the best, with 97.22% precision rate and 96.45% stable F1 score.
Vehicle detection base on Road Segmentation for surveillance satellites video
Authors: Meng Yun , Wang Xiaoyong , Yuan Shuai 
Published: September 2021

Abstract
With the development of data acquisition ability, the LEO satellites can work with a surveillance camera on board by focusing a particular area for dozens of seconds, so it drives us to develop some applications based on this data. In this paper, a data preparation method named DERS (Density Estimation based Road Segmentation) is proposed to divide the road from background to reduce the worse impact from relative-motion and then improve the precession and recall for vehicles for surveillance satellite video sequence. DERS has three main steps: frame difference, morphology, pyramid iteration, segmentation. Our experiments with the satellite videos from SkySat-1, and compared between Gaussian Mixture Model (GMM) and GMM with Ders shows that the precision rate and recall has improved of the traditional method with Ders, the precision of GMM with Ders has been improved from 64.42% to 88.71, the recall of GMM with Ders is from 76.21% to 74.16%, and the F-Score has been improved from 69.82% to 80.79%.
Automatic Diagnosis of COVID-19 Using a tailored Transformer-Like Network
Authors: Liu Chengeng , Yin Qingshan 
Published: September 2021

AbstractThe emergence of the novel coronavirus(COVID-19) has left disastrous effect on global health and individuals. Even though in most areas, the RT-PCR test used as the dominant approach for diagnosis of COVID-19 has shown good accuracy, the test requires equipment, personnel and it is time-consuming. Researches have shown the effectiveness of X-ray images for predicting COVID-19. In this study, we applied a transformer-like deep-learning model on this problem with transfer learning technique, to diagnose X-ray images as COVID-19 or normal. The model outperformed the CNN SOTA. The model achieved a classification accuracy of 99.7% on the targeting dataset.
The Research and Implementation of Electronic Device Detection System Based on STM32H7
Authors: Li Chao , Zhang ShaoYang 
Published: September 2021

Abstract
In engineering practice, it is often necessary to test the performance of electronic devices. In order to provide a convenient and fast solution for the job of electronic device detect, this paper has designed and implemented an electronic device test system based on STM32H7 platform. This system can output frequency and amplitude controllable sinusoidal wave, collect and monitor the output voltage of electronic device in real time, analyze and judge the detection results automatically, and display the detection results in real time through the combination of sound and light. In this paper, through the experimental verification, the system can achieve the detect function of electronic device, it has the advantages of simple operation, high accuracy, great reliability and strong scalability.
Industrial Control System Defense Decision-Making Method Based on Dynamic Attack-Defense Game
Authors: Zhang Shenyi 
Published: September 2021

Abstract
Industrial control systems are different from traditional information systems and require extremely high system availability. In the face of potential attack incidents, blind defense deployment may affect system performance and efficiency, which is counterproductive. For this reason, this paper proposes a defense decision-making method for industrial control systems based on dynamic attack-defense games. This method first analyzes the actual attack-defense confrontation scenarios in the industrial control system, and constructs a dynamic attack-defense game model based on this. After that, an industrial control system attack-defense game tree defined on this model is constructed, and the game tree is used to describe the specific attack-defense confrontation process. Then the backward induction method is used in the game tree to find the equilibrium path. The information on this path is of great reference value for defenders to choose a reasonable and efficient defense plan, maintain system stability and reduce defense costs. At the end of this paper, this method is applied to a real limestone powder preparation system for experiments. The experimental results verify the effectiveness of the method in actual scenarios.
Infrared moving dim point target detection based on spatial-temporal local contrast
Authors: Zhao Bendong , Lu Fengshun , Hu Xingzhi , Liu Duoneng , Wang Wenkai 
Published: September 2021

Abstract
Aiming at the detection of dim and small moving point targets in space-based infrared (IR) imaging systems, a detection method based on spatial-temporal local contrast (STLC) is presented. Firstly, use the spatial and temporal information to estimate the background gray value of each pixel, and obtain two prediction results respectively. Then, the spatial local contrast (SLC) and the temporal local contrast (TLC) are defined according to the original image and two estimated backgrounds. Next, the STLC is defined as the product of SLC and TLC. Finally, a threshold value is set in the STLC for target detection. Four groups of experiments are conducted, and the simulation results indicate that the proposed method has a great advantage in terms of background suppression factor (BSF) and gain of signal-to-noise (GSNR).
Emergency valve fault location based on improved optimal binary tree support vector machine
Authors: Cui Yupeng , Liu Ze 
Published: September 2021

Abstract
This paper presents a new algorithm IOBT SVM (improved optimal binary tree support vector machine) to locate the fault of the passenger train emergency valve and improve the test efficiency of the brake system. To reduce the classification classes and identify different faults, every two carriage faults are merged into one class and multiple sets of air pressure curve characteristics are extracted in sections. Furthermore, the structure of the classification tree is constructed from the leaf nodes to the root node combining with the class separability between every two classes. Every two most similar classes are selected in turn for classification and will be merged into one class after classification until the last class is left. Experimental results show that the structure of the classification tree generated by this algorithm is reasonable, which improves the efficiency and accuracy of emergency valve fault location.
Design of Water Quality Monitoring Visualization System Based on Cloud Platform
Authors: Huang Ziheng , Tang Bin , Wang Renjie , Zhao Mingfu , Chen Qing , Miu Junfeng , Liu Keyan 
Published: September 2021

Abstract
In response to the problem of domestic and severe water pollution control, in order to help the water environment monitoring department, this paper proposes a structure of B/S/D as architecture, Spring Boot + MyBatis + MySQL + CXF for the programming framework Water quality visual cloud monitoring system. The system abandoned the traditional method using Spring/Spring MVC as a program framework, using the Spring Boot new frame structure, which greatly enhances the readability of programming simple and program, and changed the lengthy, low running rate, and front end of the web page. Slow disadvantages. The system is actually developed, and the deployment results show that the system operates stable, and can perform long-term continuous, real-time monitoring, and can send real-time data and historical data to the information terminal to provide reliable cases and solutions to strengthen water quality supervision.
Live weight and digestibility of feed nutrients when using amino acids and silicon in the diet of broilers
Authors: Mustafina A S , Sizova E A , Kholodilina T N , Mustafin R Z , Klimova T A 
Published: September 2021

Abstract
The article presents the results of a study to determine the effect of ultra-large silicon dioxide and amino acids (arginine + lysine+methionine) both separately and in a complex on the live weight of broiler chickens. The average daily gains, as well as the coefficients of digestibility of the main components of feed were determined. It was found that the combined use of UFP SiO2 and amino acids increased the live weight of the experimental bird for 21 days by 6.1% (p≤0.05), and by the end of the experiment for 12.3 % (p≤0.05). The average daily increase 83.18 g in live weight was noted by the end of the experiment, which is 12.77 grams higher than in the control group. There was also an increase in the digestibility coefficients of dry matter of mixed feed by 4.2% (p≤0.01), organic matter – by 3.7% (p≤0.05), crude fat and crude protein - by 3.4% (p≤0.05). Thus, the data obtained in the experiment are consistent with the results of other researchers describing the effect of preparations of various ultra-large metals and amino acids on the productivity of poultry.
Early ripening variety of spring soft wheat Kanskaya
Authors: Sidorov A V , Neshumaeva N A , Plekhanova L V , Fedosenko D F , Bogdanov V V 
Published: September 2021

Abstract
The forest-steppe zone, where the main sown areas of spring wheat are located, is characterized by a short frost-free period and frequent repetition of the spring-summer type of drought. The purpose of this research was to create an early ripening variety of spring wheat that combines high productivity and drought resistance. The article presents biological, agronomic, genetic, technological and morphological characteristics of the new variety. The experimental part of the work was carried out on the experimental fields of the Krasnoyarsk Scientific Research Institute of Agriculture. The predecessor is fallow, the seeding rate is 5 million germinating grains per hectare, the soil is leached chernozem. Standard varieties - early ripening Novosibirskaya 15 and mid-early Altayskaya 70. Variety Kanskaya was created by the method of intraspecific hybridization and subsequent individual selection from a hybrid population (Altai 98 x G-17-1) x Altai 98. Since 2015, the variety is included in the State Register of Breeding Achievements of the East Siberian region. Kanskaya belongs to lutescens type. The variety is medium early. In terms of the growing season, it occupies an intermediate position between Novosibirskaya 15 and Altayskaya 70. For four years of competitive variety testing (2011-2014), the average grain yield of the new variety was 31.8 c / ha (from 16.8 to 38.2 c / ha). Kanskaya surpassed Novosibirskaya 15 by 6.6 c / ha, Altai 70 by 1.1 c / ha. In the conditions of the Krasnoyarsk Scientific Research Institute of Agriculture, the variety showed resistance to brown rust and head smut. Has an individual allelic composition of gliadins and a high component composition in the electrophoretic spectrum. In terms of grain quality, the variety is classified as a valuable wheat.
Improving commodity lending to the agro-industrial complex as an element of the state support system
Authors: Zhichkin K , Nosov V , Zhichkina L , Eryushev M , Sleptsova L , Udovik E 
Published: September 2021

Abstract
The study relevance is due to the fact that commodity lending is a fairly new procedure for agricultural producers in the state support. The study purpose is to diagnose the mechanisms of commodity lending in the livestock industries in the Samara region AIC and to develop methods for their optimization. Today, the current state of commodity lending is largely a prerequisite for the development of the economy and an integral element of the country’s economic growth. At the same time, we propose to introduce a system of control over the use of funds aimed at commodity lending, grants, subsidies, state support, to optimize the purposefulness of the received commodity lending funds, in order to prevent their further use for other purposes. The recommendations will contribute to improving the process of commodity lending to the AIC, both in the medium and long term. Competent organization of the commodity lending process will ensure the uninterrupted and effective work of the SUE SR “Veles”, the Ministry of Agriculture, agricultural producers in the field of commodity lending and, as a result, will strengthen the economy of the region as a whole.
A way to increase crop science productivity
Authors: Grishin A P , Grishin A A , Grishin V A , Semenova N A 
Published: September 2021

Abstract
It is shown that in earlier studies, the results of which were reported in the article "Digital wireless mini-sensor of plant thermoregulation", the presence of three phases of the thermoregulation process was experimentally revealed, and the task of further research aimed at theoretical and experimental confirmation of the hypothesis was set that the maximum productivity of the plant is ensured at the optimum air temperature and the maximum consumption of the nutrient solution. A number of statements, which do not require proof, are presented about the relationship between photosynthesis and air temperature and their effect on productivity. The article sets the task of developing a universal algorithm for maintaining the air temperature. Thermoregulation processes of plants were chosen as the object of research. These included the temperature of the leaf surface, the temperature difference between the leaf surface and the ambient air, and the flow rate of water for cooling evaporation. Two plant samples were chosen as the subject of research: salad variety "Red Dubolistny" and tomato variety "Fighter" (Buyan). The change in the mass of water in the container was measured using an ML-A01 balance with a measurement accuracy of 0.01 g, and the temperature was measured with an infrared IR thermometer Kelvin IKS 4-20 / 5. Data were recorded at 5-minute intervals and repeated three times over a short period of time. The plants were placed in containers with an airtight lid, which contains an oil seal for the plant stem. Moreover, the roots were placed under a lid with an aqueous nutrient solution. At the boundary of phase 2, there is a zone of maximum consumption of nutrient solution through plants, while the temperature is optimal, which corresponds to the maximum rate of photosynthesis. Further, the object of research was the process of forming a productive mass in a plant, depending on the air temperature. The weight of the plant was measured separately, on more accurate scales of the ML-A01 brand with a measurement limit of 100 g and a graduation of 0.01 g, twice a day: in the morning and in the evening. Next, weight gain dependence graph on the air temperature was built and the trend was found in the form of a second-order polynomial, which had a maximum. Its coordinates are 29.29 Co and 0.75 g of green weight gain. The maximum increase is provided at an air temperature corresponding to the boundary of phases 2 and 3. From previous studies, we found this value, it was 29.36 Co, that is it differs by 0.2%.
Anderson localization induced by complex potential
Authors: Wang R , Zhang K L , Song Z 
Published: September 2021

Abstract
In the Hermitian regime, uncorrelated disorder potential in one-dimensional lattice induces Anderson localization, whereas quasiperiodic potential can lead to both localized and extended phases, depending on the potential strength. In this study, we investigate the non-Hermitian regime. We analytically and numerically study Anderson localization in a one-dimensional lattice with the non-Hermitian complex disorder and quasiperiodic potential. We present a non-Hermitian Su-Schrieffer-Heeger (SSH) chain and demonstrate that the Hermitian counterpart with full real spectrum is a standard Anderson chain, which indicates that a nonzero imaginary disorder on-site potential can induce standard Anderson localization. We further demonstrate that the non-Hermitian Aubry-André -Harper (AAH) model exhibits a transition in parameter space, which separates the localization and delocalization phases and is determined by the self-duality of the model. This indicates that a pure imaginary quasiperiodic potential plays the same role as a real quasiperiodic potential in the transition point between localization and delocalization. Notably, a system with complex quasiperiodic potential exhibits an interference-like pattern on the transition points, which arises from the interplay between the real and imaginary components.
OptM: estimating the optimal number of migration edges on population trees using Treemix
Authors: Fitak Robert R 
Published: September 2021

Abstract
The software Treemix has become extensively used to estimate the number of migration events, or edges (m), on population trees from genome-wide allele frequency data. However, the appropriate number of edges to include remains unclear. Here, I show that an optimal value of m can be inferred from the second-order rate of change in likelihood (Δm) across incremental values of m. Repurposed from its original use to estimate the number of population clusters in the software Structure (ΔK), I show using simulated populations that Δm performs equally as well as current recommendations for Treemix. A demonstration of an empirical dataset from domestic dogs indicates that this method may be preferable in large, complex population histories and can prioritize migration events for subsequent investigation. The method has been implemented in a freely available R package called “OptM” and as a web application (https://rfitak.shinyapps.io/OptM/) to interface directly with the output files of Treemix.