bluuebunny/crossref_metadata_2025_split huggingface dataset:
Physical and mechanical studies of the influence of the impact angle on the degree of damage to raw cotton in the pneumatic transport system
Authors: Boltabaev Bekzod , Khusanov Sadi , Turaboev Gulomjon 
Published: September 2023

Abstract
The article deals with the physical and mechanical aspects of the transportation of raw cotton in a pneumatic transport system. During transportation the raw cotton collides with the working surfaces of the outlets of the pipelines and the front body of the separator at various angles. A theoretical analysis of the influence of the angle of impact on the degree of damage to raw cotton in the pneumatic transport system was performed. Based on the constructed model of physical and mechanical interaction and the use of an experimental setup an increase in the speed of pneumatic transport of raw cotton, an increase in seed damage, a deterioration in the quality of cotton fibers, and a decrease in their germination during the preparation of raw cotton were studied.
Spectroscopic studies of self-assembly α-carotenoids in binary solvents
Authors: Astanov Salih , Kasimova Guzal , Raupova Iroda , Madaliyev Yarmukhammat 
Published: September 2023

Abstract
The conditions for the appearance of the first stage of self-assembled molecules in the form of dimers and complex associates are revealed as a result of spectral-optical studies of the α carotenoid. It is determined that the structure of associates in the association of molecules is carried out in the form of a head-tail under the influence of a hydrogen bond with their further association in the form of complex associates under the action of dipole-dipole interaction of Van der Waltz forces. It is shown that initially α-carotenoids are oxidized by atmospheric oxygen, as a result of which the compounds in the structure of the studied compounds are more active than C-O groups. The formation of this group contributes to the formation of a homogeneous association of carotenoid molecules in ethanol binary solutions of ethanol + water.
Creation of porous synthetic matrices of polylactic acid (PLA) with ibuprofen impregnation using supercritical fluid
Authors: Rastegaev E K , Gilmutdinov I I , Sandugey N S , Kuznetcova I V , Sabirzyanov A N 
Published: September 2023

Abstract
The synthesis of highly porous biosoluble polymer matrices using supercritical and subcritical fluid technologies is a promising direction in the development of functional materials for modern tissue engineering and regenerative medicine. The subject of the article is the pore formation, the creation of composite polymer matrices and the impregnation of medicinal substances into the resulting structures using supercritical fluids, as well as the identification of patterns of influence of thermodynamic parameters on the physical properties of the resulting structures. Experimental studies were carried out on the creation of PLA polymer implants, composites of PLA-hydroxyapatite HAP with impregnation into the resulting ibuprofen matrix. The obtained samples were studied using spectral methods of analysis and differential scanning calorimetry.
Analysis of the results of physical and mechanical experimental studies of the modernized belt conveyor
Authors: Djuraev A , Jumaev A S , Abduraxmanova M M 
Published: September 2023

Abstract
The article presents a diagram of a modernized design of a belt conveyor with composite guide rollers with elastic elements. A complex experimental technique is given. The patterns of changes in torques and angular velocities of the belt conveyor drums are obtained. The patterns of oscillations of the outer sleeve of the composite rollers of the conveyor guide are determined. Based on the analysis of the constructed profile substitutions their recommended values are determined which ensure high performance with minimal values of the friction force.
Generation of homogeneous flows of fast argon atoms to remove wear-resistant coatings from a product surface
Authors: Metel A S , Melnik Y A , Mustafaev E S , Grigoriev S N 
Published: September 2023

Abstract
A new method is used for stripping coatings from any products before application of new coatings that extend their service life. To fulfil this task it is proposed to act on the surface with energetic atoms. The effectiveness of energetic atoms for stripping the coating is determined by the sputtering rate, which grew because of twentyfold compression of their flow. A 3-μm-thick AlTiN film was removed from a 12-cm2 surface area of a 1-cm-diameter cylinder made of tungsten carbide within 12 min.
Regulation of magnetoresistance in SmxMn1-xS by weak external pressure
Authors: Kharkov A M , Sitnikov M N 
Published: September 2023

Abstract
Magnetoresistive effects in SmxMn1-xS (x = 0.1) are investigated under the influence of weak external pressure versus temperature and magnetic field. The angular dependence of the magnetoresistance upon changing the direction of the magnetic field is found. A decrease in magnetoresistance with an increase in current at certain temperatures is found. The experimental data are explained by a change in the external pressure on the sample.
Determination of the physical and mechanical properties of overalls based on the analysis of geometric and thermophysical parameters
Authors: Chorieva Mukhabbat 
Published: September 2023

Abstract
The article describes the multifactorial experiments to determine physical and mechanical properties of overalls based on the analysis of geometric and thermophysical parameters. The thickness of the fabric, the amount of oleophobic coating, and the air temperature affect the physical and mechanical properties of the fabric. This is explained by the fact that various properties of the fabric decrease at high values of coefficients. Between the protective oleophobic coating layer and the fabric, taking into account the effect on the coefficient between the protective oleophobic coating layer and the air, the theoretical change in the body occurs only in the fabric and the protective layers of the oleophobic coating.
Scientific fundamentals for the use of serpentinized rocks from the eastern region of Cuba
Authors: Ojeda Pardo F R , Pons Herrera J A , Ramirez Perez M C , Quiroz Cabascango V E , Mosquera Urbano A P 
Published: September 2023

Abstract
Cuba has one of the largest reserves of basic and ultrabasic rocks in the world, located mainly in the Moa - Baracoa ophiolitic complex, where dunitic rocks abound, bearing the olivine mineral with important refractory properties. The present work shows the main scientific results, accumulated during more than 20 years of research on this raw material, and the obtaining of different refractory products, such as: foundry sands and non-stick paints, refractory bricks, among others. An experimental design of mixture, Mac Lean - Anderson type, was used, which allowed defining the best mixtures for the manufacture of refractory products, determining also the most important physical-mechanical properties and their comparison with similar materials. The use of this raw material would efficiently contribute to the reduction of the impact on the ecosystem currently caused by the accumulation of this debris in the region of Moa.
Optical transmission modulation by fiber guide bending
Authors: Sedova N , Sedov V , Bazhenov R , Povkh I , Dolmatova O , Bogatenkov S 
Published: September 2023

Abstract
The study is aimed at finding out the influence of bending on the waveguide from the point of view of ray equivalence with its modification based on the concept of local plane waves to provide an illustrative way to describe optical transmission in a multimode optical fiber. The paper covers the physical principles of modulation of optical transmission of fiber light guide by the bending radial variation. In addition, the authors obtained the expression for the total radiant energy in the light guide bend section/cutting in the ray equivalence. The mechanism of modulation of the fiber optical light guide and obtained mathematical expressions are the theoretical foundation for producing amplitude fiber-optic sensors.
Optimization of the physical and mechanical processes of stone crushing by the method of computational scanning
Authors: Akabirova L X , Kamalova F R 
Published: September 2023

Abstract
Physical and mechanical processes for processing dry materials such as grinding and crushing are the most resource-intensive ones. It is preferable to carry out the technological process of stone crushing where maximum yield of fine-grained crushed stone with a size of 0-5 mm is obtained. The purpose of this study is to determine the optimal parameters of stone crushing on a vertical impact crusher where the yield of fine-grained crushed stone will be maximum. The physical and mechanical processes of stone crushing were optimized using the computational scanning method. The optimization was performed based on the obtained regression equation describing the output of fine-grained crushed stone from influencing factors on the process. To determine the optimal values of the factors affecting the process of stone crushing an algorithm flowchart has been developed and a calculation program has been compiled in Delphi. As a result the following values of operational factors were obtained: incoming raw material size d = 0.0375 m; the speed of the crusher rotor, n = 1600 rpm; the distance between the accelerator and the ring platform l = 0.2 m; the concentration of crushed stone size 0-5 mm at the output of the crusher will be a maximum of 55.37%.
Improvement of the method of calculation of the reduced heat transfer resistance of light openings of buildings
Authors: Komilov Ochil , Akhrorova Munira 
Published: September 2023

Abstract
During the construction of buildings in regions with relatively low outdoor temperatures it is necessary to pay more attention to the issues of heat preservation and minimizing heat losses through external enclosing structures. The paper analyzes the main ways of heat loss minimization through translucent enclosing structures. It is revealed that it is more expedient to reduce heat loss through a window structure by using an effective double-glazed window. The main methods of increasing the reduced resistance to heat transfer of a double-glazed window are described. The methods of reducing heat transfer which occurs due to convection and radiation are analyzed. The reasons for the need for the use of energy-efficient double-glazed windows are given.
Diffusion Models-based Data Augmentation for the Cell Cycle Phase Classification
Authors: Chen Zirui 
Published: September 2023

Abstract
For biological research, sample size imbalance is common due to the nature of the research subjects. For example, in the study of the cell cycle phase, the sample size of dividing cells is also much smaller due to the extremely short duration of the mitotic phase compared to the interphase. Data augmentation using image generative models is an excellent way to address insufficient sample size and imbalanced distribution. In addition to the GAN-like models that have been extensively applied, the diffusion model, as an emerging model, has shown extraordinary performance in the field of image generation. This experiment uses the diffusion model as a means of image data enhancement. The experimental results expose that the performance of the classifier with data augmentation is significantly improved compared with the original dataset, and the positive predictive value is increased from about 0.7 to more than 0.9. The results reveal that the diffusion model has a good application prospect in the area of data enhancement and can effectively solve the problem of insufficient data or unbalanced sample size.
Performance analysis of attention mechanism and teacher forcing ratio based on machine translation
Authors: Lu Chengsong 
Published: September 2023

Abstract
The Seq2seq model has the characteristics that the encoder is used to analyze the input sequence, and the decoder is used to generate the output sequence, which is very suitable for the characteristics of machine translation tasks, making it achieve advanced performance in the field of machine translation. In addition, the attention mechanism has achieved remarkable results in many kinds of natural language processing tasks. The combination of seq2seq model and attention mechanism is the critical research direction in machine translation. To compare the effects of different attention mechanisms on the performance of machine translation models, this paper selects two classical attention mechanisms, including Synthetic Attention and Muti-head Attention, to test machine translation tasks. In addition, for another critical set of the sequence model, teacher-forcing, this paper also tests the influence of different teacher-forcing thresholds on the model performance. The experimental results show that Muti-head Attention has apparent advantages over Synthetic Attention. In addition, the reasonable choice of teacher-forcing also affects the stability of the model in the real environment.
Collaborative obstacle avoidance algorithm and simulation of swarm robots with limited viewing angle
Authors: Yunhong Zhou 
Published: September 2023

Abstract
In this paper, the problem of collaborative obstacle avoidance of swarm robots with limited view angles is studied. In the case of limited view angles, the control model of swarm robots system is designed. The swarm robots can safely avoid a single static obstacle when the obstacle is within the robot’s visual angle. The main research result of this paper is to design a collaborative obstacle avoidance control algorithm for swarm robots, and subdivide the overall control algorithm into three sub algorithms: formation, obstacle avoidance and navigation. The condition of limited view angle is added to the collaborative obstacle avoidance control algorithm of swarm robots, and a control model of collaborative obstacle avoidance of swarm robots with limited view angle is constructed. Then based on the Simulink platform, the simulation is carried out in the case of static obstacle to verify the correctness and stability of the algorithm.
Performance comparison among VGG16, InceptionV3, and resnet on galaxy morphology classification
Authors: Qian Yumeng 
Published: September 2023

Abstract
This article introduces the structures of three classical convolutional neural networks: VGG16, InceptionV3, and ResNet50, and compares their performance on galaxy morphology classification. The different structures of these networks give them some distinct features, leading to different results. The dataset used was Galaxy10 DECals created by the Galaxy Zoo project. The models were compared in the same way, using one fully-connected layer only without modifying its original architecture, evaluated by accuracy, precision, recall rate, and f1 score. The experimental results show that InceptionV3 gave the best classification results from all aspects. The inception module performs well on the galaxy morphology classification problem.
Robot navigation based on multi-sensor fusion
Authors: Deng Mingyao 
Published: September 2023

Abstract
Over the past years, with the rapid development of artificial intelligence technology, mobile robots have appeared in more and more fields. Different types of robots play different roles. Due to the complex indoor environment, there are still many technical problems to be solved for robots. Aiming at the shortcomings of single sensor, low mileage accuracy, and poor security in traditional mobile robot navigation systems, we propose a mobile robot autonomous navigation system based on multi-sensor perception. This system integrates mainstream synchronous positioning and mapping algorithms, path planning algorithms, and positioning algorithms, and uses multiple sensors to compensate each other to achieve the automatic navigation function of the mobile robot. In order to verify the reliability of the method, We have carried out multi angle analysis in the simulation environment, and the experimental results show that the proposed navigation system is reliable in operation, high in mileage accuracy, and good in robustness, which broadens the application scenario of mobile robots.
RAT-Cycle-GAN for text to image
Authors: Yin Chenlong , Su Weiheng , Lin Zheyong , Xu Yuyang 
Published: September 2023

Abstract
We present a method that enhances the RATGAN using the idea of CycleGAN to prevent the model from collapsing. The generator with the proposed recurrent affine transformation for text-to-image synthesis and the fusion blocks are connected by an RNN during the generation of fake images to assure the global assignment of text information. The transformation from the phony images to the text is then accomplished using a CNN and encoder with LSTM. A comparison of the generated text with the original text ensures the generator’s preciseness. In order to achieve the state of the art, we evaluated both unconditional and conditional generation’s effectiveness in relation to the accepted standards.
An ultra wideband (UWB) localization system for automatic guided vehicles (agvs) in smart warehouses
Authors: Huang Hao , Huang Ziyu , Wang Dexin , Wang Jiarui , Xu Xiaotian , Yao Peixin 
Published: September 2023

Abstract
As the main component of indoor positioning technology, UWB technology plays an important role in promoting the development of indoor and outdoor seamless positioning technology. This paper presents a proposed localization system of a propagation channel measurement campaign performed in a smart warehouse environment whose dimension is 100 meters * 100 meters and provides an extensive model for this environment. Three different arrangements of basestations are simulated to analyze the effects of basestation constellations and virtual racks are set up to determine the approximate line-of-sight (LOS) probability. At the same time, by considering the influences of varying transmit power, using weighting and using two-way ranging, the distribution of errors and the reliability threshold are drawn and the required bandwidths are determined. Finally, according to the simulation results, the optimal layout and modulation parameters are recommended, and improvements in channel models and algorithms for future work are concluded.
Instrumental variables matter: towards causal inference using deep learning
Authors: Wu Kunhan , Wang Zihan , Zhao Jingyi , Xu Haodong , Hao Tianming , Lin Wenzhi 
Published: September 2023

Abstract
Causal inference requires knowing causal connections between treatment and outcome variables, and DeepIV, a causal inference framework, is the pioneer work to predict such connections by crossing deep learning with causal inference in applying instrumental variables(IVs) to deep neural network. DeepIV has been proved to be one of the best methods in this field theoretically, but how the framework performs on real-life problems still remains unclear. This paper provides an implementation of DeepIV, and use the framework to predict causal effect from people’s educational background on their annual income. DeepIV framework allows us to take advantage of neural network to estimate causal effect by adjusting loss function. To evaluate the performace of DeepIV in solving real-life problems, our experiment is based on real datasets. The result of our experiment shows that DeepIV’s ability to predict causal effect on real data is at least as good as those of other casual inference models’ whose reliability has been verified in practice. Meanwhile, DeepIV does not have obvious shortcoming in predicting outcomes compared with other supervised learning methods.
Impact of multi-GPUs and hyperparameters on parallel algorithms based on pytorch distributed
Authors: Wei Shiyu 
Published: September 2023

Abstract
Neural networks, as powerful models for solving many genuine problems, are suffering from the issue of being too computationally intensive due to the excessive size of the models themselves and the large datasets used for training. This paper’s work focuses on a parallel algorithm, experimented on the classical convolutional neural network LeNet-5, aiming to reduce the time it takes for the neural network to train. This applies a massively parallel GPU structure to take full advantage of its high computing power. Among the approaches to improve the performance of parallel algorithms, many efforts have been made to improve the design of parallel structures, while this work focuses more on the enhancement of parallel algorithms by reasonable settings of neural network hyperparameters. This paper tries to approach (1) reducing the running time by testing parallelism with different numbers of GPUs and (2) further investigating the relationship between parallelism and model accuracy degradation and experimentally deriving a parallel scheme that can reduce the training time while guaranteeing accuracy.
Learning additional latent representations using variational autoencoders
Authors: Shen Chong 
Published: September 2023

Abstract
A noticeable trend of machine learning is to deal with data of various modalities. Besides multimodal motivation, learning more from general information without forgetting the prior, or incremental learning, could also benefit unimodal machine learning. Human understanding often starts from a simplistic, generic view of the whole problem and then fills in the details and nuances. Incremental learning could enable imitation of such a learning process to learn more and potentially faster. This paper examines the possibility of learning additional latent variables from known latent variables for variational autoencoders. A method is proposed to facilitate learning additional information based on a modified β-TCVAE loss function that incorporates known general mutual information. A qualitative comparison is conducted on the dSprites dataset to evaluate the effect of this modification and the change of network structures on the learned latent, which hints at the structural tendency for β-TCVAE to learn new information from explicit known latent.
A microstrip patch antenna for 5G mobile communications
Authors: Li Yitong 
Published: September 2023

Abstract
The advantages of microstrip patch antennas include small size, adaptable surface, ease of fabrication, and compatibility with integrated circuit technology. Numerous experiments have been done over the past few decades to enhance the performance of this antenna, and both military and commercial sectors have found many uses for it. This paper introduces a microstrip patch antenna with an operating frequency of 28GHz for 5G mobile communication. This research designed and simulated a rectangular microstrip patch antenna with 3.494 mm * 5.3 mm * 0.003 mm. The proposed antenna resonates at 28 GHz with a reflection coefficient of -24 dB, a bandwidth of 280 MHz, and a gain of 2.2 dBi. The inset feed technique matches the 50 Ω transmission line impedance. In the design, Rogers RT5880 substrate and copper ground are used. The antenna’s geometry was calculated, and simulated results were analyzed using Computer Simulation Technology Microwave Studio. In conclusion, the proposed antenna has a reflection coefficient of -24 dB, VSWR of 1.24, an input impedance of 51.6Ω, and a gain of 2.2 dBi at operating frequency with a compact geometry can be used in 5G mobile communications. The future shift in resonance frequencies and beams can be considered to make the antenna operate as a smart antenna.