bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on Model-Based Combined Failure Analysis Method for Integrated Modular Avionics
Authors: Chen L , Zhang F K , Lin X G , Zhou Y H 
Published: April 2022

Abstract
Aiming at the combined failure problem of Integrated Modular Avionics (IMA) system under the condition of resource sharing, this paper proposes a model-based combined failure analysis method for IMA system. Based on the system architecture model and the fault tree model containing the failure cause, the method integrates the failure cause relationship of the IMA system, and completes the analysis of the combined failure effect of the IMA system. By taking the failure conditions of a certain function of the IMA system as an example, the effectiveness of the analysis method is verified.
Tile-based multiple parallel triangle rasterization algorithm implemented in FPGA
Authors: Xue Junjie , Ai Dihan , Wang Mingjiang 
Published: April 2022

Abstract
With the progress of rendering technology, the industry has put forward higher requirements for GPU performance while rasterization algorithm plays an important role in GPU performance. In this paper, we first review some of the current mainstream rasterization algorithms. Then we propose a triangle rasterization algorithm—tile-based multiple parallel midpoint rasterization algorithm. This algorithm combines the characteristics of midpoint traversal and tiled traversal. At last, we use FPGA to implement the algorithm in order to verify the feasibility of the algorithm. And we use the triangle data set used in previous papers to simulate in Modelsim software. The results show that this algorithm can improve the rasterization speed and the highest frequency of this design is 200MHZ.
AI intelligent wayfinding based on Unreal Engine 4 static map
Authors: Xie Yuhang , Chen Yihong , Wang Ziyi , Ou Yangjun 
Published: April 2022

Abstract
The development of games is closely related to the development of game engines. Unreal Engine is a mainstream game development engine. Unreal Engine has a powerful lighting rendering function and blueprint programming system.Therefore, using Unreal Engine for game development will better meet the requirements of modern game users for game quality and game content. In games, the AI path-finding system is often the core of a game. However, the path-finding component of the unreal engine is usually only applies to three-dimensional game and is used for intelligent path-finding in dynamic environment. Howerve, the 2D game usually finds the way in static environment. At present, there are a lareg number of path-finding algorithms and theoretical studies based on static environment, but there is no simulation experiment and detailed explanation of intelligent path-finding in static environment based on the Unreal Engine platform. This article firstly explains the principle of path-finding algorithms that are several commonly used in static environment. Then it compares the performance of different algorithms, and selects the optimal solution among several schemes by summarizing the experimental results. Then based on the optimal path-finding algorithm, using blueprint programming to implement AI path-finding in the Unreal engine. Finally, this article sort out and summarize the overall work process and indicate direction for future optimization.
A Novel Exploration of Potential Music Influence Based on Graph Theory
Authors: Luo Zheng , Chen Yujie 
Published: April 2022

Abstract
Most artists have been influenced by their predecessors or peers in their lives, who brought them inspiration to form their own composing style and direction. This pattern is particularly important for the study of the developing trend of the music field. Based on the da ta which records the influence relationships of musicians over the years, we construct a directed influence network, reflecting the connection among musicians. Then from the perspective of the subnetwork, a synthetic appraisal model is put forward to quantify the influence of artists. In order to indicate its correctness and objectivity, the influence patterns between musicians and their works are further explored by analyzing the attributes of songs. Finally, for the music itself, the properties of the music are analyzed through standardized regression to obtain the characteristics that have the greatest impact on the music influence.
Airport UAV and birds detection based on deformable DETR
Authors: Shanliang Liu , Yunlong Li , Jingyi Qu , Renbiao Wu 
Published: April 2022

Abstract
The aviation industry is growing rapidly, but due to inadequate airport surveillance technology, there have been incidents of UAV intruding into airports and birds striking aircraft in the clearance area. Existing airports use radar-based detection technology to monitor UAV and birds in the clearance area, and they cannot correctly identify the type and number of UAV and the size and number of birds. Based on this problem, this paper proposes a deformable DETR (DEtection TRansformer) based detection method for UAV and birds to assist airports to better supervise the clearance area and reduce safety hazards. In response to the small size of airport UAV and birds, we adopt a deformable DETR object detection method using multi-feature fusion to detect UAV and birds in the airport environment. The model has good detection performance with mAP of 75.2 and recall of 95.0%, which meets the airport’s requirements for UAV and bird detection, as verified by the actual data collection. This method can help to improve surveillance methods within the clearance area of airports and can also provide technical support for the detection of small objects in other areas.
Improving Few-Shot Learning with Vision Transformer
Authors: Qi Di 
Published: April 2022

Abstract
Vision Transformer (ViT) is emerging as an alternative to convolutional neural network (CNN) for visual recognition and has achieved impressive results, however, due to its data-hungry nature, ViT encoder in few-shot setting remains rarely explored. In this paper, we first propose a simple yet effective baseline that exploits the complementarity of self-supervised learning (SSL) and ViT, enabling the use of standard ViT model as the few-shot learner. Second, based on the baseline, we introduce a novel regularized fine-tuning framework, where the Parametric Instance discrimination (PID) and Base-Novel (BN) regularizations are proposed to reduce the intra-class variance and calibrate the biased distribution of novel classes to further enhance few-shot recognition. We conduct extensive experiments and show that our method can achieve new state-of-the-art performances on two widely used benchmarks.
Multi-scale Image Denoising via a Regularization Method
Authors: Tan Yi , Fan Jin , Sun Dong , Gao Qingwei , Lu Yixiang 
Published: April 2022

Abstract
Image restoration is a widely studied problem in the field of image processing. Although the existing image restoration methods based on denoising regularization have shown relatively well performance, image restoration methods for different features of unknown images have not been proposed. Since images have different features, it seems necessary to adopt different priori regular terms for different features. In this paper, we propose a multiscale image regularization denoising framework that can simultaneously perform two or more denoising prior regularization terms to better obtain the overall image restoration results. We use the alternating direction multiplier method (ADMM) to optimize the model and combine multiple denoising algorithms for extensive image deblurring and image super-resolution experiments, and our algorithm shows better performance compared to the existing state-of-the-art image restoration methods.
Self-supervised flow field decoupling for Controllable face reenactment
Authors: Kong Xianwei , Xiong Shengwu 
Published: April 2022

Abstract
Face reenactment is a face image generation method. Its main task is to generate a new image given a source image and a driving image, which has the facial motion information of the driving image while retaining the content information of the source image. Existing flow-based approaches have demonstrated high-quality results, but these works regard the head movement as a whole, and cannot achieve more flexible movement control, and often suffer from the loss of identity information. In this paper, we propose a novel Controllable multi-identity face reenactment(CFReenet), which uses the prior information of facial motion to decompose the movement as two parts of pose and expression and use the curriculum strategy to decouple movement and identity information and better maintain identity information. The experimental results demonstrate the effectiveness of our method.
A Dual Stream Model for Anti-infrared Decoys: Exploiting Interaction and Contextual Relationship
Authors: Liu Tianyu , Wang Yuehuan 
Published: April 2022

Abstract
The infrared decoy jamming release process has spatio-temporal correlation. In order to mine the spatio-temporal correlation between target and decoys, we propose a dual stream model for anti-decoys based on graph convolutional network and long short-term network. The method proposed models the interaction relationship of the target and decoys, and combines contextual information to infer the real target. Experimental results on our prepared dataset with ground truth labels demonstrate that the algorithm proposed outperforms existed anti-decoy jamming methods in various metrics.
Workingtool for application of granulated ameliorators
Authors: Vasilyev A A , Vasilyev S A , Igoshin D N , Lopotkin A M 
Published: April 2022

Abstract
This article discusses the application and distribution of granulated ameliorants in the subshovel space during tillage with subsurface cultivator. Researches show that subsoil application of nutrient granules improves the agrophysical properties of soil, which in turn increases its fertility. The article presents obtained parameters of agrophysical properties before and after the passage of tillage unit; in particular hardness, volume crumbling coefficient and bulk weight of soil changed after granulated ameliorators were introduced into soil. The obtained results are close to reference values, which make it possible to judge the practical and effective use of this working tool for application of granulated ameliorators.
The effect of low-temperature processing of semi-finished potatoes on the ascorbic acid content
Authors: Grigorieva R Z , Kostina N G , Podlegaeva T V , Shalimova D V 
Published: April 2022

Abstract
In Russia, only 2% of grown potatoes are processed, while in Western countries this figure exceeds 50%. In the food industry the use of potatoes in processed form (various semifinished products) has a number of advantages as compared to fresh potatoes. It is established that the range of processed potato products is expanding every year, however, one of the most popular types of semi-finished products from potatoes are those subjected to low-temperature processing. In this regard, the change in the content of ascorbic acid in semi-finished potato products during freezing and storage was studied. After examining the chemical composition of five varieties of potatoes grown in the Kemerovo region the “Rikeya” variety was selected. Freezing of the potatoes was carried out at temperatures of -24ºC and -40ºC with natural, as well as forced convection with an air velocity of 1.25 and 2.5 m/s. The resulting frozen semifinished products were stored for 25 days at temperatures of -12ºC, -18ºC, -24ºC. It was found that the temperature of freezing and storage, as well as air velocity during freezing, significantly affect the preservation of vitamin C in semi-finished potatoes. The determining factor contributing to the preservation of the processed potatoes’ quality is the temperature regimes of freezing and storage – the smaller the difference of these temperatures, the less the loss of ascorbic acid.
Determination of the drying temperature of the medicinal plant prickly capers - “Capparis spinosa L.” fruits by the method of mathematical modeling
Authors: Ya Inagamov S , Tajibaev G G , Sh Ilhamov H , Yoqubjonov D , Mukhamedov G I 
Published: April 2022

Abstract
In this paper, the optimal drying temperature of the medicinal plant prickly capers - “Capparis spinosa L.” was studied and mathematical models were determined by comparing experimental data with data calculated using the Lagrange and Newton interpolation formula and the choice of regression analysis. The regression equation has the form of a polynomial and a polynomial level. The mathematical model in which the level of the polynomial was 6 and higher was almost indistinguishable from the models in the form of a polynomial which level was 4 or 5. When determining the optimal drying temperature of the fruit of the medicinal plant prickly capers - “Capparis spinosa L.” by mathematical modeling, it is shown that graphs with a polynomial degree of n=3 and higher have the same values as graphs in which the degree of the polynomial is almost equal to n=2. The coincidence of the theoretical results with the experimental data obtained in determining the optimal drying temperature for the fruit of the medicinal plant prickly capers - “Capparis spinosa L.”, shows the adequacy of the mathematical model. It was found that the optimal drying temperature of the medicinal plant prickly capers - “Capparis spinosa L.” is 333 – 343 K and this is confirmed by mathematical modeling.
Evaluation of new cultivars of cherries and sweet cherries on the main economically valuable traits in the conditions of the Bryansk region
Authors: Kanshina M V , Yagovenko G L , Misnikova N V , Astakhov A A 
Published: April 2022

Abstract
The article presents the results of testing samples of cherries and sweet cherries, created at the All-Russian Research Institute of Lupine. Cherry is one of the most important fruit crops in central Russia. In recent years, there has been a sharp reduction in the area of its cultivation. The main cause of the cherry crisis is stress factors that contribute to physiological disorders, weakened resistance to pathogens and reduced yields. Intense damage to leaves by coccomycosis and moniliosis is accompanied by powerful necrosis, which is a phenotypic manifestation of a developing disease and allows an accurate assessment of genotypes by resistance class. Sweet cherry is a new fruit crop in central Russia. Evaluation of 50 varieties of sour cherries and cherries according to a complex of economically valuable traits made it possible to identify a number of promising samples for their transfer to State tests. Among them are varieties and varieties: cherries - Ruskol, Bryansk Talisman, 2-11-33, 2-12-11, 3-18-23; cherries - Rusaliya, Valentina, Darnitsa, Milan and others. The State Register of Breeding Achievements includes 10 cultivars of cherries and 15 cultivars of sweet cherries bred by the All-Russian Research Institute of Lupine, a branch of the Federal State Budgetary Scientific Institution “FNTs VIK im. V.R. Williams”.
Technology of hydroponic growing of cinquefoil (Dasiphora fruticosa (L.) Rydb.)
Authors: Makarov P N , Makarova T A , Samoylenko Z A , Gulakova N M 
Published: April 2022

Abstract
The article assesses the productivity and yield of shrubby cinquefoil grown hydroponically. If the necessary conditions for the cultivation of plants are met, 2-3 cuts can be achieved within 4 months of cultivation. Productivity of plants under the white lights: 0.58 kg/m2 for the first cutting, 1.34 of kg/m2 for the second cutting, 1.12 of kg/m2 for the third cutting; under the combined lights: 0.46 kg/m2, 0.89 kg/m2 and 0.78 kg/m2 respectively. The yield of cinquefoil gowned traditionally is 0.66 kg/m2.
Adaptation of the photosynthetic function of Juniperus communis L. in the mountainous middle taiga dark coniferous forests of the Southern Urals
Authors: Tishkina E A 
Published: April 2022

Abstract
The article studies the accumulation of photosynthetic pigments and the ratio of their forms in the needles of Juniperus communis L. in the mountainous middle taiga dark coniferous forests of the Southern Urals during the winter and summer periods in contrasting conditions of the tundra-clear forest transition zone within the same slope of Dalniy Taganay. The assessment of the morphophysiological state makes it possible to assess the adaptive capabilities of plants, which consist in changing the content and ratio of pigment forms, transformation of the life form, while the accumulation of the pigment composition does not depend on age. Adaptation of the photosynthetic apparatus at the level of the ratio of photosynthetic organs allows this species to maintain growth parameters and gain an advantage in light spruce forest conditions.
Growth and yield of pine plantations of different initial densities
Authors: Dubenok N N , Lebedev A V 
Published: April 2022

Abstract
The purpose of the study is to assess the role of the initial density of forest stands on indicators of growth and productivity based on long-term observation data. Analysis of long-term data on the study of the growth of pine plantations of different initial planting densities showed that the initial planting density initially sets the individual history of the interaction of trees and the formation of the stand. In denser stands, crown closure and the formation of a forest canopy occur earlier. In them, at an earlier age, the volume stock reaches its maximum. The main difficulty in growing forest plantations is the need to take into account biological sustainability.
Isolation and Utilization of Patchouli Oil (Pogostemon Cablin Benth) as an Anti-Bacterial Alternative
Authors: Ermaya D , Widodo YR , Teguh D 
Published: April 2022

Abstract
Patchouli (Pogestemon cablin Benth) is one of the essential plants used as a fixative agent, due to alcohol contains in this plants.. The main component obtained from destilation process is patchouli alcohol (45-50%). Other important industrial chemicals include patchouli camphor, cadinene, azuluene and others. Body scent can be caused by several factors due to excess activity and metabolism. Staphylococcus epidermidis is known as bacteria that trigger body scent. This study aims to formulate deodorant cream from purified patchouli oil. And measure the physical, chemical properties and to determine the deodorant formulation (consentration pachouli alkhol (PA)). Then proceed with statistical processing with ANOVA. Based on the organoleptic test, the best results were obtained from the formula with 1% PA concentration. The result show that patchouli oil has meet the standard according SNI. SNI for patchouli oil, the patchouli oil was brownish yellow colour and had a distinctive patchouli aroma. From the results of GCMS after sonification, the highest component is azuluene followed by patchouli alcohol.
Evaluation of β-lactam therapeutic drug monitoring among US health systems with postgraduate year 2 infectious diseases pharmacy residency programs
Authors: Chen Chieh , Seabury Robert W , Steele Jeffrey M , Parsels Katie A , Darko William , Miller Christopher D , Kufel Wesley D 
Published: April 2022

Abstract

Purpose
While some guidelines recognize the need for β-lactam therapeutic drug monitoring (TDM), there is still a paucity of data regarding the prevalence of and barriers to performing β-lactam TDM in the United States. We sought to estimate the prevalence of β-lactam TDM, describe monitoring practices, and identify actual and perceived barriers to implementation among health systems in the US.

Methods
A multicenter, cross-sectional, 40-item electronic survey was distributed to all postgraduate year 2 (PGY2) infectious diseases (ID) pharmacy residency program directors (RPDs) listed in the American Society of Health-System Pharmacists pharmacy residency directory. The primary outcome was the percentage of institutions with established β-lactam TDM. Secondary outcomes included assessing β-lactam TDM methods and identifying potential barriers to implementation.

Results
The survey was distributed to 126 PGY2 ID RPDs, with a response rate of 31.7% (40 of 126). Only 8% of respondents (3 of 39) performed β-lactam TDM. Patient populations, therapeutic targets, and frequency and timing of obtaining repeat β-lactam concentration measurements varied among institutions. The greatest barrier to implementation was lack of access to testing with a rapid turnaround time. Institutions were unlikely to implement β-lactam TDM within the next year but were significantly more inclined to do so within 5 years (P &lt; 0.001).

Conclusion
β-lactam TDM was infrequently performed at the surveyed US health systems. Lack of access to serum concentration testing with rapid turnaround and lack of US-specific guidelines appear to be considerable barriers to implementing β-lactam TDM. Among institutions that have implemented β-lactam TDM, there is considerable variation in monitoring approaches.
A Data-driven Learning Focus on Form Approach to Academic English Lecture Comprehension
Authors: Zare Javad , Aqajani Delavar Khadijeh 
Published: April 2022

Abstract
Using concordancers in English classes is demanding, time-consuming, and challenging to both teachers and learners. On the other hand, research points to the effectiveness of data-driven learning (DDL) in improving second/foreign language learning. The present study proposed a new task type, that is, DDL focus on form (FonF) tasks, as a combination of DDL and FonF approaches, and investigated if using such tasks improves students’ comprehension of English academic lectures. Drawing on a quasi-experimental validating quantitative data triangulation model, 124 intermediate English learners were pretested, randomly assigned to treatment and control groups, exposed to the treatment and control treatment, and post-tested on immediate and delayed academic English lecture comprehension tests. The treatment required working with 12 DDL FonF tasks, specifically proposed for the present study, during 12 45-min sessions. On the other hand, the control treatment involved working with 12 FonF tasks during 12 45-min sessions. Due to the coronavirus pandemic, the study was done remotely and the tasks were sent through WhatsApp in Word and PDF formats. As part of the validating quantitative data triangulation model, semi-structured interviews were held with the learners in the experimental group to shed light on the treatment. The results of the study suggested that using DDL FonF tasks results in both temporary and durable improvement in the learners’ comprehension of English academic lectures. The study concludes that integrating DDL and FonF approaches to second/foreign language learning in the form of tasks improves academic English lecture comprehension through increase in the learner’s noticing, metalinguistic awareness, discovery learning, and agency.