bluuebunny/crossref_metadata_2025 huggingface dataset:
Security Service Function Chain based on Software-Defined Security
Authors: Zhu Sheng , Zhou Cheng , Wang Cheng
Published: September 2021

Software-defined networks face not only traditional network security threats, but also new network security threats brought by centralized and programmable control planes. To address the above problems, this paper proposes a business chain design mechanism for security protection functions based on software-defined security, which constructs a security service function chain according to user requirements and also realizes security resource scheduling according to the load of hosts, and the security service function chain rules classify and redirect network flows to corresponding security devices sequentially in the form of OpenFlow flow tables to realize network traffic Dynamic control of network traffic. The test shows that this mechanism can effectively realize security service virtualization and provide flexible and dynamic security protection mechanism according to security service requirements.
Impact of explosive charge mass on reflected shock wave of high explosion
Authors: Gao Rui , Wang Bairong , Luo Xia
Published: September 2021

Overpressure is an important metric of the destructive effect of the shock wave produced by high explosion. Investigating the overpressure of shock wave on the surface is an essential way for evaluating the power of explosive device. This study has important implications for quantitative analyses for establishing the relationship between parameters of reflected shock wave by using the numerical simulation software AUTODYN with different TNT explosive charge mass. The research indicates that with the increase of explosive charge mass, the initial value of peak overpressure of high explosive increases and the attenuation rate accelerates, it also provides the condition that the similarity law can be established in the relationship between peak overpressure and scale distance.
Hardware Design and Implementation of Image Processing System Based on FPGA
Authors: Zhao Dongmei , Zhou Bo , Song Yang , Li Ling
Published: September 2021

Discussed the hardware design and implementation of the image processing system with Virtex-XC5VSX95T as the algorithm processing chip. The large-capacity data storage chip XCF128X is selected to store the program flow. The user clock, DDR2 clock, SATA clock and other clock modules are designed. Designed LVDS and SATA as a high-speed data interface for image data transmission. Designed RS-422 as a communication interface for parameter, command and status data transmission. DDR2 memory modules and NAND Flash are as memory for image data caching. Dedicated voltage regulator chip is selected to meet the requirements of each module of the system for DC voltage. The test proves that the hardware design of the image processing system is correct and can realize the expected function.
An Auxiliary Identification System for Destructive Pests
Authors: Mai Weijian , Wu Fengjie , Chen Jiangtao , Tang Yisheng , Liu Qingkun
Published: September 2021

This work takes this Asian Hornet’s invasion of Washington in 2020 as an example to build an auxiliary identification system for Destructive Pests to help the government’s rescue work. To help the government to prioritize the resource to the most possible reports and improve the investigation efficiency, we built a binary classification model to classify the report that contains images and text. For image classification, we design a VGG16-based convolutional neural network pretraining with ImageNet, which achieved superior performance with a high F1 score (95.08%) on our dataset. For text classification, we use the Latent Dirichlet Allocation (LDA) model to cluster words into different themes and adopt cosine similarity to calculate the similarity between the new report and the benchmark positive/negative sets. The results demonstrated that our approach can identify target pests efficiently and help the government to prioritize the resource to the most possible reports, improving the investigation efficiency.
Research on Image Classification Algorithm Based on Convolutional Neural Network-TensorFlow
Authors: Zhao Jiantao , Li Lili
Published: September 2021

Image Classification is one of the important processing methods in the field of image processing. Traditional Classification algorithms, such as KNN (K-NearestNeighbor), have been unable to meet the accuracy standards of image Classification. And convolutional neural networks (CNN) are increasingly used to solve the problem of image classification. This paper briefly ces the convolutional neural network, which is constructed using the TensorFlow deep learning framework, and conducts experiments on 2000 pieces of custom data set of 10 classification obtained by crawler technology. At the same time, a comparative experiment is conducted on the traditional image classification KNN algorithm. Experimental results show that the application of convintroduolutional neural network in image classification has relatively large advantages, and the accuracy has been greatly improved.
Visible and infrared missile-borne image registration based on improved SIFT and joint features
Authors: Xue Song , Zhang Xiaorong , Zhang Hang , Yang Chuandong
Published: September 2021

For the acquired visible and infrared missile-borne images, in order to provide accurate and reliable image data for the subsequent processing of images to achieve complementary information, we carried out visible and infrared missile-borne image registration research. Firstly, the shape context is used to extract the rough edge features of the image. Then we improve the SIFT gradient definition to overcome the difference in image gray value, and combine with the coherent point drift algorithm to increase the number of correct matching points to achieve global image registration. Experimental results show that, compared with the existing registration methods, the proposed method has a good visual effect of registration, greatly improves the correct registration points and registration accuracy, and can better solve the problem of visible infrared missile-borne image registration.
Prediction and Analysis of Short-Term Load Forecasting Model Based on Similar Day Clustering and CatBoost
Authors: Chen Zhonghua , Chen Jiamin , Wang Caiqian
Published: September 2021

Accurate load forecasting provides a reference of vital importance for power generation and power dispatching systems. A short-term load forecasting model combining similar day clustering and CatBoost method is proposed in this paper. Similar day clustering is a method for evaluating the similarity between the days to be forecast and historical days. Similar day clustering is based on K-means clustering which can classify samples with similar features into the same category. Then, CatBoost is used to build load forecasting models. CatBoost enables us to directly handle categorical features without pre-processing. This paper utilized the information collected by a substation in Hangzhou as the data set, and compare the proposed model with the existing forecasting model based on Autoregressive Moving Average, Gradient Boosting Decision Tree, CatBoost, Long Short-Term Memory. The experimental results show that the proposed model provides more accurate results compared with other models in terms of MAPE, RMSE.
Topic evolution analysis of radar research using a dynamic topic model based on latent Dirichlet allocation
Authors: Huang Xiaoguang , Fang Hui
Published: September 2021

This work applies a dynamic topic model based on latent Dirichlet allocation to investigate the evolution of radar research and applications. To address the problem that processing a large number of papers exceeds the capacity of computers, we propose a method to sample documents according to their citation count. Of 104,428 sampled articles, 108 research topics are extracted. The evolution of topics is analysed from two dimensions: content and strength. The results show that radar technology, which arose mainly from physics and engineering science, has been widely applied in studies in the civil engineering, geographical, environmental, meteorological, geological, agricultural, ecological, among others. In the long-term development of radar, new technologies have continuously been produced. At the individual topic level, the research content has changed over time. The development objectives of radar systems are to enhance functionality, extract more information and improve clarity.
Voxel-wise binocular energy models for binocular disparity decoding
Authors: Zheng Hongna , Chen Maoming , Yao Li , Long Zhiying
Published: September 2021

Binocular disparity is a powerful cue for depth perception in three-dimensional (3D) space. Some neurophysiological studies proposed the binocular phase-shift and position-shift energy models to predict the responses of individual disparity-tuned neurons in cats and macaques. By far, it is unclear how to use binocular energy models to characterize the voxels’ responses in human visual cortex. In this study, we introduced the binocular energy models to the functional magnetic resonance imaging study and constructed the position-shift receptive-field model (Position-RFM) and the phase-shift receptive-field model (Phase-RFM) to predict voxel responses to disparity and to identify novel disparity levels from voxel responses. The results revealed that Phase-RFM outperformed Position-RFM in fitting the voxel responses for all the visual regions. Moreover, the novel disparity levels can be better identified from voxel’s responses in visual regions by Phase-RFM than Position-RFM. The findings may suggest that Phase-RFM can better encode the responses of disparity-tuned neuron populations than Position-RFM for human visual regions.
Weakly and semi-supervised learning for sound event detection using image pretrained convolutional recurrent neural network, weighted pooling and mean teacher method
Authors: Cai Xichang , Yu Dongchi , Liu Duxin , Wu Menglong
Published: September 2021

In this paper, we propose a sound event detection (SED) method which uses deep neural network trained on weak labeled and unlabeled data. The proposed method utilizes a convolutional recurrent neural network (CRNN) to extract high level features of audio clips. Inspired by the impressive performance of transfer learning in the field of image recognition, the convolutional neural network (CNN) in the proposed CRNN is an image-pretrained model. Although there is a significant difference between audio and image, the image-pretrained CNN still has competitive performance in SED and can effectively reduce the amount of training data needed. To learn from weak labeled data, the proposed method utilizes a weighted pooling strategy which enables the network to focus on the frames containing events in an audio clip. For unlabeled data, the proposed method utilizes a mean teacher semi-supervised learning method and data augmentation technique. To demonstrate the performance of the proposed method, we conduct the experimental evaluation using the DCASE2021 Task4 dataset. The experimental results demonstrate that the proposed method outperforms the DCASE2021 Task4 baseline method.
MOOC Dropout Prediction Based on Multi-view Learning
Authors: Li Feifan , Wei Zhengang
Published: September 2021

Massive Open Online Courses (MOOCs) provides a promising way to support education for all. Nonetheless, one central challenge is the remarkably high dropout rate, with completion rates for MOOC recently reported to be below 5%, and high dropout rates limiting their effectiveness. Building on the analysis of dropout as closely related to user and course interaction patterns, this paper presents an end-to-end multi-view interactive framework (EMIF) to predict user dropout in MOOC. We extract learning activity information, user enrolment information, and course knowledge information through a set of lD-CNNs, obtain mutual information of these and fuse the above information-view loss through a self-weighing method. Experimental evaluation of our solution on the KDDCUP 2015 and MOOCCube datasets showed better results (AUC & F1 scores). We have a better performance compared to several existing methods, without using different architectures for different datasets.
Adaptive Weight Fusion Algorithm of Infrared and Visible Image Based on High-Frequency Domain CNN
Authors: Wang Chuanyun , Yang Guowei , Sun Dongdong , Zuo Jiankai , Wang Ershen
Published: September 2021

Aiming at covering the shortage of single source sensor imaging and improving the contrast between the target and the background in image, this paper proposes an adaptive weight fusion algorithm of infrared and visible image based on a High-frequency Domain Convolutional Neural Network (HDCNN). Firstly, the high and low frequency components of the original image are obtained by using the Daubechies wavelet transform, and then a high-frequency domain convolutional neural network which can detect the frequency information ratio of infrared and visible light in the high-frequency subband is trained. Secondly, the network is used to perform adaptive weight fusion for the high frequency components and regional energy is used for fusion of the low frequency components. Finally, the fusion image is obtained by inverse wavelet transform. A large number of experiments have proved that the algorithm in this paper has a greater improvement over similar comparison algorithms in objective evaluation metrics such as standard deviation, spatial frequency and average gradient. The algorithm enhances the contrast between the target and the background in the fusion image, and enriches the characteristic information of the target itself.
Design and Implementation of Face Emotion Recognition System Based on CNN Mini_Xception Frameworks
Authors: Sun Lili , Ge Chenhao , Zhong Yuanchang
Published: September 2021

In the new era, the rapid development of information technology makes the face recognition technology in artificial intelligence also develop rapidly, among which, face expression recognition has become a research hotspot. In recent years, due to deep learning, convolutional neural network and multilayer perceptron and other related algorithms have become the research focus of scholars, so their wide application in the field of facial expression recognition is also the direction of face emotion recognition exploration and research. In addition, computer software is widely used in human daily life, so it is also very important to design and implement an intelligent, real-time and universally applicable UI interface for facial emotion recognition system. Therefore, this paper firstly completed the facial expression recognition model based on the Mini_Xception framework of CNN by training the FER2013 expression database. Secondly, the system UI interface is designed and realized through PyQT5, OpenCV, Keras and other libraries. The final results show that the system is based on the algorithm model, and the UI interface designed and realized can not only recognize the saved pictures, but also recognize the real-time face emotions through the camera, and the overall effect of the system is outstanding.
An efficient backbone network for target detection in aerial images
Authors: Zhang Sihan , Liu Yaping , Wang Xile , Zhang Miaohui
Published: September 2021

Target detection in aerial images by high altitude unmanned aerial vehicles is one of the hot research topics. A detection that is efficient and accurate is of a high value in the military and civilian fields. However, due to the irregular distribution of targets and their various scales shown in aerial images, it is difficult for existing backbone networks to effectively extract target features based on deep learning. To address these problems, in the paper, an efficient backbone network called AerNet is proposed, to which a local feature enhancement module (LFEM) is added to fully extract discriminative features of aerial targets via multi-scale convolutional layers. The network AerNet consists of 55 layers, which can keep high spatial resolution in deeper layers and maintain a large receptive field. Experimental results show that our AerNet has achieved a satisfying detection performance on the DOTA benchmark.
Intention prediction of UAVs based on improved DDQN
Authors: Chen Tianpei , Liu Haotian , Wang Yuhui
Published: September 2021

Intention prediction plays an indispensable role in future informationized air combat, which will help the command and control center to make a more correct decision. In this paper, an intelligent intention prediction approach based on an improved double deep Q network (DDQN) is developed to generate real-time intention flight paths for unmanned aerial vehicles (UAVs) in complex air combat environment. Initially, by introducing an actual topographic map, the different threats of UAVs in different terrains on the map are analyzed, based on which, a terrain environment reward function is constructed. Secondly, by splitting a complete maneuver action into six basic maneuver units and determining the probability value of each unit, a maneuver reward function is obtained. Further, to improve the real-time performance and accuracy of the standard DDQN algorithm, an improved DDQN algorithm is proposed by using temporal-difference (TD) method and binary tree data structure. Finally, the simulation results verify show that the proposed algorithm has achieved better results under complex terrain conditions.
Chaos-GA-BP Neural Network Power Load Forecasting Based on Rough Set Theory
Authors: Li Dianwen , Ji Xiu , Tian Xin
Published: September 2021

In order to accurately grasp the trend of power load changes and provide guidance for stable and efficient operation of the power system, this paper proposes a Chaos-GA-BP power load forecasting model based on rough sets. First, screen the main factors that affect power load changes, remove redundant data, and optimize the input of the prediction model; Second, rely on the BP neural network prediction model to adjust its topology, optimize weights and thresholds, and build a rough set-based Chaos-GA-BP power load forecasting model; Finally, considering the impact of severe power load fluctuations on the forecast results, rough set theory is introduced to perform forecast compensation when the slope on both sides of the peak is large. Applying the above method to a one-month power load forecast in a certain area in Northeast China, the change trend of the forecast curve closely follows the actual load curve. Compared with the traditional method, the average absolute error percentage is reduced by 2.67%. The experiment shows that this method has certain practicability.
Research on Prediction of Oxygen Consumption in Converter Steelmaking Based on IGWO-SVM Model
Authors: Wen Daoyuan , Zhu Yingtao
Published: September 2021

The oxygen supply for converter steelmaking is the main factor affecting the quality of molten steel. To improve the accuracy of the oxygen consumption prediction model for converter steelmaking, an improved gray wolf optimization algorithm is proposed to optimize support vector machines to establish an oxygen consumption prediction model (IGWO-SVM), effectively improving the prediction accuracy of oxygen consumption in converter steelmaking. Firstly, aiming at the problem of slow convergence of the standard gray wolf algorithm and easy to fall into local optimality, Bernoulli chaotic initialization is introduced to enhance the uniformity and ergodicity of the initial population; and an adaptive decreasing convergence factor is introduced to balance the global search of the gray wolf algorithm and local search capability, while adopting adaptive inertia weight strategy to update the population position and speed up the convergence speed. Secondly, the benchmark function is used for testing, and the results show that the improved gray wolf optimization algorithm has improved convergence speed and search accuracy. Finally, based on the measured data of a steel plant to predict the oxygen consumption of converter steelmaking, the simulation results show that the oxygen consumption prediction model of converter steelmaking based on IGWO optimized SVM has high accuracy and strong generalization ability.
Face Replacement and Image Animation System in Cultural Experience
Authors: Li Jiayue , Wang Qing , Li Shiji , Zhou Qian , Zhong Qiang
Published: September 2021

As a unique representative of Chinese culture and civilization, Chinese traditional portrait painting has a certain cultural influence all over the world. However, what kind of human-computer interaction system can attract more people’s interest and attention, is still a field worthy of exploration. This paper focuses on the instantiation expression of Chinese traditional portrait, improves the regional feature point matching based on the research of Photo to Chinese Portrait method (P-CP), compares the effects of different color correction approaches on the experimental results, and introduces the form of real-time image driving animation. We hope that we can provide new inspiration for the dissemination of traditional culture and the application of modern technology.
An aerodynamics-centric framework for multidisciplinary coupling analysis and its application
Authors: Jiang Xiong , Wang Ziwei , Lu Fengshun , Liu Duoneng , Zhao Bendong , Wang Wenkai
Published: September 2021

There are many multifaceted problems in the aerospace engineering domain, which demand the multidisciplinary simulations for coupling analysis and the development of coupling frameworks. In order to address the issue of lacking domestic coupling framework, we propose an aerodynamics-centric framework for multidisciplinary coupling analysis, and then demonstrate the usage of it in developing a structured-unstructured grid coupling software, which is validated with an external store separation case study.
Research on Weak Current Detection System Based on Embedded System
Authors: Long Xiaoli , Li Xinxue , Guan Jian
Published: September 2021

In today’s society, the rapid development of science and technology requires the detection of weak current signals in many fields of scientific research. The research of its detection technology plays a very important role in promoting the development of science and technology. Considering that the weak current signal has strong background noise, it is easy to be submerged, the detection is difficult, and the professional requirement is strong. This research proposes a weak current detection system based on an embedded system that can detect nan oampere-level weak currents. The detection system is mainly composed of signal conversion amplifier filter circuit module, signal acquisition circuit, STM32, FPGA, upper computer and so on. Through experimental inspection, the researched detection system has the advantages of high accuracy and good stability.
Research on Motion Intensity Monitoring and Motion Scheme Recommendation Based on Internet of Things
Authors: Chen Yu , Zhu Jiadong , Wang Mengnan
Published: September 2021

With the development of Internet of Things technology, digital sports training will become a hot topic in the field of sports science. Digital exercise training is a training mode of monitoring the quality of the training in real time in the process of using technology to train practitioners and adjusting the physical training process according to the data. By combing the main application of international Internet of technology in sports training, this paper proposes the use of technology to monitor the movement intensity, and realizes the sports scheme intelligently recommended technical scheme, and implements it, and carries out the practical application and achieves commercial benefits according to the monitoring results.
Complementary Filter for Attitude Estimation Based on MARG and Optical Flow Sensors
Authors: Li Xiang , Xu Qing , Shi Qi , Tang Yanmei
Published: September 2021

The combination of tri-axial magnetometer, accelerometer, and gyroscope has been widely used for three-dimensional attitude measurement, and this combination is also called MARG sensor. However, the measurement of accelerometer contains both the gravitational and motional acceleration, and only the former is useful for attitude estimation. As a result, MARG-based attitude estimation is easily disturbed by motion acceleration. In this paper, we introduce a complementary filter that estimates gravity and geomagnetic vectors in parallel, and utilize an optical flow sensor to detect and compensate motion acceleration. Experiment results show that the proposed algorithm has better performance than the existing ones when experiencing linear acceleration.
Research on SDN Congestion Control Based on Reinforcement Learning
Authors: Zhang Limin , Tian Xiaolu
Published: September 2021

Aiming at the congestion control problem of SDN, this paper designs a network congestion control scheme based on Q-learning algorithm of reinforcement Learning. According to the usage of link bandwidth in the network, the algorithm adjusts the transmission rate of the source data stream continuously, and finally obtains the optimal data stream allocation scheme. Experimental simulation evaluates the performance of the algorithm, the proposed control algorithm based on reinforcement learning congestion, can effectively improve the link utilization, reduce network congestion. The experimental results show that the congestion control algorithm proposed in this paper can allocate the optimal rate for each data stream, reduce network congestion, and has better performance than the traditional SDN algorithm.
Comfort Optimization of Adaptive Cruise Control Based on Heart Rate Variability and Fuzzy Control
Authors: Yang Zhibo , Fu Wen-Hui , Zhang Zhiqiang , Zhang Jiarui , Wang Lei
Published: September 2021

This paper investigated the impact of braking intensity of self-driving cars at different initial speeds on straight road sections on drivers’ comfort, with a view to achieving the comfort optimization of adaptive cruise control (ACC). Specifically, the real vehicle test was conducted in an enclosed venue based on the within-subjects design of 3 × 3 × 2, and the data pertaining to electrocardiogram (ECG) and subjective evaluation of 9 subject drivers in 9 sub tests were collected. Besides, the impacts of different motion states on heart rate variability (HRV) parameters were analyzed using the general linear model for repeated measures, and the relationships among drivers’ comfort, decelerations, and standard deviation of NN intervals (SDNN, an index of HRV) were obtained based on subjective and objective analyses. Additionally, a control strategy based on HRV and fuzzy control was formulated to realize the comfort optimization of ACC in case of an abrupt deceleration of the preceding vehicle, the verifications were performed through joint simulation. The results exhibited that the control strategy based on HRV and fuzzy control could shorten the deceleration time in case of an abrupt deceleration of the preceding vehicle, and may improve the comfort in such scenario.
Speech endpoint detection in fixed differential beamforming combined with modulation domain
Authors: Wang Hongli , Zeng Qingning , Zhao Xuejun
Published: September 2021

The actual speech signal is always in a complex environment, which affects the accuracy of speech endpoint detection. In order to improve the accuracy of speech endpoint detection under low Signal-To-Noise Ratio(SNR), a speech endpoint detection technology based on fixed differential beamforming and modulation domain is proposed. Firstly, two microphones of the first-order differential microphone arrays(DMAs) are used to collect the target speech and noise, and then a fixed differential beamformer is used to reduce the noise. Then, the phase compensated modulation domain spectral subtraction method is used to further eliminate the residual noise. Finally, the subband spectral entropy algorithm is used to detect the speech signal endpoint. The experimental results show that, compared with the existing methods, the proposed method has a higher accuracy of speech endpoint detection in the low SNR environment of -10∼5dB.
Development of a Modularized Virtual Flight Simulator based on Multiple Discipline Coupled Method
Authors: Liu Fan , Wang Ziwei , Zhang Sheng , Xiao Zhongyun
Published: September 2021

The problem of aircraft control involves multiple subjects and has always been extremely complicated in mechanics modelling. Virtual flight simulation was put forward in order to reduce the cost of full-scale airplane flying test and wind tunnel experiment. A typical virtual flight simulator includes a computational fluid dynamics (CFD) solver, a structure dynamics (FD) function, and a flight controller. However, existed virtual flight solver usually ignores the universal modelling of dynamics for complex aircraft configuration and the modularization of CFD, FD and flight controller module, which makes it very inconvenient for many in-house virtual flight codes for engineering application and commercial software development. A new framework of virtual flight simulation platform is established with a parallel Reynolds Averaged Navier-Stokes (RANS) solver, a structured moving overlapping grid function, a generic multiple body dynamics (MBD) solver, and a plug-in type flight controller platform. A universal data exchange interface between MBD and flight controller is presented. An X-wing missile flying forward and pitching-up maneuvering validation case is conducted with the current virtual flight simulator, the result is compared with Matlab Simulink solver based on steady aerodynamic database and good agreement is obtained.
Design of Host Computer for sonar based on Ethernet
Authors: Zhang Qijiang , Wang Jing , Li Wei , Wang Zhiyuan , Tan Mingchuan
Published: September 2021

The Host Computer for sonar based on Ethernet is suitable for Single-beam Mechanical Scanning Sonar with a scanning frequency of 675KHZ and 1MHz. It is completed by using C# programming language in Windows. The Host Computer based on the framework of C#.Net. TCP, UDP are used to communicate between single beam mechanical scanning sonar and Host Computer. The scan data of sonar can be received by the Host Computer, the functions of setting and query sonar operation parameters are provided. The Host Computer uses two network transport layer protocols, TCP and UDP. Most of the sonar data transmission uses only a single protocol. Finally, the received sonar scanning data will be displayed. Wireshark is used to verify the packet capturing of the transmission process.
Effects of resonance states in barrier region on non-exponential decay of wave-packets scattered by rounded-rectangular potentials
Authors: Takahashi Kin’ya
Published: September 2021

The decay processes of wave-packets scattered by periodically perturbed and unperturbed rounded-rectangular potentials are studied numerically and theoretically, when the widths of the potentials L are very large. For the case of the unperturbed potentials, four different stages successively arise in the decay process of the wave in the potential region: two pre-exponential decays, namely power–law decay of t
−3 and oscillating power–law decay, exponential decay and post-exponential decay, which is also power–law decay of t
−3. The post-exponential decay is usually extremely small in magnitude. The characteristics of the pre-exponential and exponential decays are explained with the properties of resonance states, i.e. the Gamow states, for the unperturbed system. The rate of the exponential decay is determined by the imaginary part of the eigenenergy of the first resonance state. For the two pre-exponential decays, the ending time of the t
−3 decay is a linear function of L and that of the oscillating power-law decay is proportional to L
3. In the limit of L → ∞, the t
−3 decay is observed persistently, namely the decay for the rounded-step potential. For the perturbed potentials, even if the average energy of an initial wave-packet is relatively smaller than the oscillating potential, the noninstanton tunnelling, i.e. the multi-quanta absorption tunnelling, raises the tunnelling wave component up to the oscillating top of the rounded-rectangular potential, and the tunnelling probability rapidly increases with the perturbation strength. The properties of the resonance states are almost the same as those of the Gamow states because of the flatness of the potential top. As a result, the decay process after the tunnelling is almost the same as that for the unperturbed system. It is suggested that the tunnelling amplitude and tunnelling time, namely the amplitude and period of the pre-exponential decay, can be controlled by the perturbation strength and the potential width, respectively.
The effectiveness of organomineral feed additives from local raw materials in feeding young horses in Yakutia
Authors: Grigorev M F , Grigoreva A I , Ivanov A I , Gogoleva I V
Published: September 2021

The article presents data on the study of the effect of organomineral feed additives based on sapropel and zeolite in combination with mineral salt while feeding young horses in the Far North of Yakutia. The research was carried out on young horses of the Yan type of the Yakut breed. Three groups of experimental young horses were selected. Clinically healthy animals were approved for scientific experiment. The research program included the study of growth and development for individual periods of cultivation, assessment of nutritional value of diets by groups, the study of the blood morpho-biochemical composition to determine the effect of feed additives on the animal physiology. Experiments have shown that animals consuming organomineral feed additives grew more intensively and surpassed their peers in all periods of rearing. Thus, at 5 months of age horses from II and III experimental groups surpassed others by 0.78% and 0.50%, and upon reaching 6 months of age this indicator was equal to 2.37% and 1.55%. In total, during the experiment the animals from the experimental groups exceeded the test group by 10.92% and 6.21% in terms of live weight. This is most noticeable in the average daily gain in live weight. Therefore, at the age of 4-5 months the experimental groups grew more intensively than the test group by 8.68% and 3.77%; in the 5-6-month age the result was similar (by 13.16% and 8.65%). It means that feeding organomineral additives to young horses contributed to a significant increase in live weight and to the improvement in the blood morpho-biochemical composition.
Research of strength properties of half-finished products
Authors: Barakaev N , Urinov N , Juraev J , Ergashov D
Published: September 2021

The article covers experimental study of knives with different sharpening angles to determine the strength properties of molded half-finished product and associated energy consumption for cutting. Determination of the values of the limiting shear stress of products depending on moisture content of the dough and the radius of rounding of the knife.
Iodine and iron fortified muffin technology
Authors: Ivanova N G , Nikitin I A , Rodionova S N , Krasnova E A , Makharov Z I
Published: September 2021

Flour confectionery is considered as one of the most popular food products. They can’t be included in the food ration of people leading a healthy lifestyle due to their chemical structure and nutritional value. The recent trend is to expand a range of flour confectionery products by imparting functional properties to them. The development of muffins with a reduced sugar and fat content is relevant taking into account the worldwide increase in the level of nutritional diseases (cardiovascular and oncological diseases, obesity, anemia, etc.). Improving the technology of confectionery products by introducing persimmon and feijoa into the formulation of processed products will make it possible to deal scientifically with the issue of the lack of confectionery products with the increased nutritional value and reduced calorie content. So it can improve their assortment and ensure widespread consumption in everyday life. The paper presents the research results concerning the development of technology for muffins enriched with iodine and iron. The paper also states the substantiation of the reduction in the prescription amount of sugar and substitution of margarine with a smaller amount of sunflower oil, as well as the introduction of persimmon puree and pieces of feijoa fruit into the recipe. The presented muffin is characterized by a high content of iodine, iron, calcium, magnesium, potassium and dietary fiber, as well as reduced by a third the content of added sugar and fat.
Biotechnology of freeze-dried sour clotted milk with pumpkin and topinambour
Authors: Krasnova I S , Ganina V I , Semenov G V , Ionova I I , Guchok Zh L
Published: September 2021

The research aimed to substantiate rational parameters of the vacuum freeze-dried sour clotted milk biotechnology. It was revealed that the use of novel starters containing cultures that can synthesize exopolysaccharides provided a symbiotic relationship of fermented milk system particles and prevented its disintegration in freeze dry products rehydration. This was confirmed by microscopic analysis of histological preparations prepared from rehydrated samples of freeze-dried sour clotted milk. It was shown that the addition of topinambour powder resulted in production of freeze-dried sour clotted milk with organoleptic parameters not meeting established requirements. Adding freeze-dried pumpkin powder to the sour clotted milk formulation contributes to increased survival of lactic acid bacteria cells during vacuum freeze drying by an order of magnitude in average. It has been shown that the combined use of novel starter cultures and prebiotics results in production of freeze-dried sour clotted milk with required quality parameters.
Kinetic dependences for the extraction of apricot pits kernels with ethanol-water solvent
Authors: Gafurov Karim , Muslimov Bobirjon , Saidmuratov Uktam , Kuldosheva Firuza , Ibragimov Ravshan , Rakhmatov Umid
Published: September 2021

During the extraction of a capillary-porous body, such as the nuclei of fruit seeds, the movement of the distributed substance in the solid phase is carried out by means of molecular diffusion. The amount of material flow in a solid per unit surface is determined by Fick’s law using the diffusion coefficient. The molecular diffusion coefficient depends on the structure of the solid, temperature and soluble substances, and does not depend on the hydrodynamic conditions on the surface of solid particles and the design of the apparatus. The article studies the kinetics of extraction of petals of apricot kernels with ethanol-water solvent. When calculating the value of the residual mass content of plant raw materials during the extraction process, an interval calculation method was used. Based on the experimental data of the extraction kinetics, the molecular diffusion coefficient was determined, which significantly increases during 600-700 s of extraction, and then decreases by 2 times after 1800 s. After 3000 s from the beginning of the process, the diffusion coefficient decreases less sharply. A significant increase in the diffusion coefficient at the beginning of the extraction process, including the impregnation stage, is associated with the uneven distribution of the extracted components in the initial sections of the capillaries. In the studies carried out, the nature of the change in the diffusion coefficient over time does not contradict modern concepts of the mechanism of extraction of a porous structure from plant raw materials.
Obtaining technologically and physiologically functional special-purposes of fat products
Authors: Isabaev Ismoil , Khudaykulov Anvar , Dzhuraeva Nafisa , Ashurova Zebiniso , Tursunova Umida
Published: September 2021

The possibilities of obtaining special fat products for baking and confectionery products based on two-stage hydrogenation, both on stationary promoted and dispersed catalysts, are investigated. At the same time, at the first stage, non-selective partial hydrogenation was carried out to obtain liquid baking fats characterized by a sufficient amount of solid glycerides, and at the second stage, this partially hydrogenated fat was subjected to final selective hydrogenation to obtain high-solid confectionery fat. In order to enrich the obtained fats with polyunsaturated fatty acids of the group ω-3, it was first proposed to mix these fats with non-fat flaxseed flour to obtain functional fat-flour compositions.
Optimization of food compositions according to the ideal protein profile in a personalized nutrition system
Authors: Zverev S V , Karpov V I , Klokonos M V , Sorokin A E , Masyagin G M
Published: September 2021

The article deals with the problem of optimizing food compositions from plant raw materials according to the ideal protein profile. The mathematical formulation of the issue is carried out and the result is obtained by a computer software developed by the authors for this class of issues. Two options were used as criteria for the rationality of the blend being composed: with all essential amino acids of the proteins of the developed mixture components, and with only those essential amino acids, the score of which is less than one. The formation of the optimal blend was carried out for two criteria: the minimum score and the proportion of total protein based on plant materials. The resulting blends from mixtures of plant cultures have a higher biological value and can be used to enrich the composition of functional and specialized products, as well as in the development of products and diets for personalized nutrition.
Using lingonberries in the production of meat products
Authors: Skachkov D A , Ramazanova G F , Pilipenko D N , Filipov N V , Obrushnikova L F
Published: September 2021

The article describes the solution to the problem of expanding the range of meat products with the addition of plant-based ingredients of a functional orientation with a reduced caloric content. The research was carried out on experimental samples of raw smoked sausages, for which original recipes were developed. The study is aimed at studying the effect of a plant food additive on the nutritional value of a meat product, namely, energy, biological and organoleptic values. For this purpose, the content of the mass fraction of moisture, fat and vitamin C in the finished product was determined.
The development of the sports nutrition drink formula with low allergenic capacity
Authors: Melnikova E I , Bogdanova E V
Published: September 2021

The key trend of sports nutrition market growth in Russian Federation is the development of new products, in particular, which may have specific effect on the human body. Proteins are of the highest value in sports nutrition, and more especially, whey proteins. However, their application in food products manufacturing requires carrying out technical operations, which provide the decrease of their allergenic capacity. The purpose of the research was the development of sports nutrition drink formula with low allergenic capacity. The objects of the study were whey protein hydrolysate, obtained from cheese whey ultrafiltration concentrate with the usage of proteolytic enzyme preparations Promod 439L and Flavorpro 766MDP; sports nutrition drink on the basis of hydrolysate, produced by adding banana, peach and squash juices. The whey protein hydrolysate was used as the main formula ingredient, and fruit juices were used as an additional source of biologically active elements. The microstructure differences of the investigated mixtures were defined. The protein conglomerate size varied from 50 up to 80 μm in diameter, lactose was in form of crystals up to 5-7 μm by size. It was proved, that polysaccharides, presented in fruit juices, were involved with the structure formation of drinks. Considering high content of starch among complex carbohydrates of banana in comparison with squash and peach, the sample with squash juice was chosen as the working formula of sports nutrition drink. The usage of whey protein hydrolysate allowed getting the final product with high biological value, digestibility and low allergenic capacity.
Milk productivity of cows and the content of the metal-ligand forms of iron
Authors: Kazakova T V , Marshinskaia O V , Notova S V
Published: September 2021

The milk productivity of animals was evaluated and the content of the metal-ligand forms of iron was studied against the background of changes in the total content of manganese in the blood serum of dairy cows using the hybrid technique (HPLC-ICP-MS). For this purpose, groups were formed for comparing animals with low-normal values of manganese (Mn concentration up to the 25th percentile) and high-normal values (Mn concentration above the 75 th percentile) according to the results of a previous study. The Mn content in the blood serum of all animals was within the physiological normal range. Analysis of the data obtained showed that high-normal levels of manganese in the blood were accompanied by a significant decrease in the indicators of milk productivity of cows. The metal-ligand forms of iron have undergone significant changes. Changes in metal ligand homeostasis can be considered early biomarkers for predicting the state of mineral metabolism to increase productivity.
Development of natural semi-finished poultry meat products enriched with iodine
Authors: Khramova V N , Korolyov A V , Khramova Ya I , Korotkova A A , Kartushina Yu N
Published: September 2021

This article briefly covers the problem of iodine deficiency in the country, it is described about the iodine-containing preparation "Yodozin". Research data is given and illustrates its effect when adding in natural-finished products from poultry meat. In the course of the work, the practical use of the preparation was proved. When it is added to semi-finished products, the mass concentration of iodine increases and is retained in products even after bringing them to culinary readiness. "Yodosin" does not affect the physicochemical and organoleptic characteristics of the product.
Development and research of a product for gerodietic nutrition
Authors: Felik S V , Antipova T A , Androsova N L , Simonenko S V
Published: September 2021

This article presents material on the development and research of gerodietic nutrition. The composition of the developed product, including ingredients of animal and plant origin, is given, and the choice of raw materials and components used in the development of formulas is explained. A flowchart of the production stages is presented, according to which, in the experimental shop of the Research Institute of Children’s Nutrition - a branch of FGBUN "FITS Nutrition and Biotechnology" a development type was produced. Based on the data obtained in the study of the nutritional value of the product, established the acceptability of its practical use in the diet of the elderly and old age.
Colostrum in technology of functional products: possibilities and opportunities
Authors: Glagoleva L E , Zatsepilina N P , Galimov A S , Pavlova S V
Published: September 2021

Currently, there is great interest in the field of nutrition - colostrum (colostrum), which has extensive protective factors that allow the use of colostrum not only for newborn calves, but also for deterministic groups of the population - children, debilitated patients, the elderly. colostrum in technology of functional products. Colostrum is considered abnormal milk, since a sharp change in the physiological state of an animal at the beginning and at the end of the lactation stage is accompanied by the formation of a secret, the composition, physicochemical, organoleptic and technological properties of which differ significantly from the same indicators of normal milk. Thus, the obtained positive data indicate the possibility and prospects of using colostrum in the technology of functional products.