bluuebunny/crossref_metadata_2025 huggingface dataset:
Dietary influences in Attention Deficit/Hyperactivity Disorder: an evidence-based narrative review
Authors: Boaz Mona , Kaufman-Shriqui Vered
Published: December 2022

Background: A number of nutrients and dietary patterns have been proposed as therapeutic interventions for attention deficit/hyperactivity disorder (ADHD), a neurodevelopmental disorder prevalent in as many as 5% of school-aged children. Evidence for these claims is inconsistent.Objectives: To estimate the efficacy of interventions with specific nutrients: vitamin D, omega-3 fatty acids, magnesium, iron, zinc, copper, and the Mediterranean diet pattern in reducing ADHD symptoms.Methods: A narrative review of the literature Results: The interventions considered herein have biological and physiological rationale supporting their proposed use in treating ADHD.  Evidence supporting their use is frequently seen in observational studies, but this evidence is less convincing in clinical trials and meta-analyses.  Conclusions: Professional bodies do not recommend these interventions for the general ADHD population in the absence of documented deficiencies.  Because the Mediterranean diet prevents chronic disease and promotes general health and wellness, it can be recommended as appropriate for children with ADHD.  Keywords: Attention deficit/hyperactivity disorder (ADHD); vitamin D; omega-3 fatty acids; magnesium; iron; zinc; copper; Mediterranean diet
Scientific and Professional Degrees in Russia: Developing Traditions into the Future
Authors: Rudskoy A. I. , Borovkov A. I. , Romanov P. I. , Grishina N. S.
Published: December 2022

When studying the history of Russian education, one becomes convinced of the validity of the dialectical principles of spiral development. The period of cyclicality in the history of attestation of scientific personnel is approximately equal to a century. In the first quarter of every century, starting from the time of the tsar Peter the Great, events took place that brought the system to a fundamentally new level. But at the same time, the fundamental foundations laid by the tsar Peter the Great and Lomonosov remain constant. Analyzing the attestation system development spiral, we find ways to solve urgent problems, and the foremost among them is ensuring Russia’s technological sovereignty. A similar problem stood a century ago. It was fully resolved in the USSR, but the foundations for its solution were laid in 1917 in the decree issued by the Russian Provisional Government: “On granting the Petrograd Polytechnic Institute the right to award academic degrees”. In the socioeconomic conditions of the modern Russia, we need new solutions. In this article we offer them
Method for weak zones location at the coal-bed – host rock joint relative to the problem of sudden outbursts: theory and laboratory experiment
Authors: Nazarova Larisa A , Nazarov Leonid
Published: December 2022

Within the framework of a geomechanical model that describes the deformation of a rock mass during the subhorizontal coal-bed extraction, the mechanism for the formation and implementation of a sudden outburst is substantiated: as working face gets close to the weak zone of coal-bed – host rock joint, areas of tensile stresses arise, which creates the prerequisites for face space spalling and coal loss with methane. The inverse problem of determining the conditions at the horizontal boundaries of a coal-bed is formulated and solved using tomography data (longitudinal wave velocity V distribution) and the empirical dependence of V on the mean normal stress σ. Lab tests results on stepwise compression of parallelepipeds made of artificial geomaterials are presented. Tomography of the specimens was performed by acoustic sounding data, and the distribution of velocities V* was found. Using the pre-established empirical dependence V(σ) for geomaterial, the distribution σ*=V-1(V*) in the specimen was calculated, which served as input data for inverse problem of determining the shear stresses σxy at the “specimen faces – press platens” joints. Lab data inversion confirmed the possibility of identifying weak zones of the boundaries where σxy=0. These zones are associated with probable nucleus of failure and sudden outbursts.
Improvement of crack tip position estimation in DIC images by image processing methods
Authors: Zekriti Najat , Majid Fatima , Taoufik Hachimi , Tounsi Yassine , Rhanim Rajaa , Mrani Ibrahim , Rhanim Hassan
Published: December 2022

The study presents and compares an application of two procedures to identify the crack tip location in PVC Sent samples under a uniaxial tensile test based on the image processing method. An IDS camera captures several photos of the PVC surface as part of the image analysis procedure. All relevant data on crack initiation and propagation is collected and assessed using ImageJ software using image processing methods for detecting cracks. However, the second procedure involves a developed algorithm detecting the discontinuity using digital image correlation (DIC) measurement. Although, because of the experimental conditions, the acquisition of images by the digital camera is never perfect. This noise comes from several sources, including the digital camera, image distortion due to lens magnification or lens angle, the shape and size of the pattern, and electronic noise; ... This article discusses image enhancement methods to overcome these objectionable characteristics using and comparing several filters:  Gaussian, median, and Unsharp Mask filters. The performance of the Gaussian filter is better than the Median and Unsharp mask filters. This research demonstrates that DIC is an effective technique for monitoring deformation and understanding the failure mechanism with the best-suited filter.
Description of Fatigue Sensitivity Curves and Transition to Critical States of Polymer Composites by Cumulative Distribution Functions
Authors: Staroverov Oleg , Mugatarov Artur , Yankin Andrey , Wildemann Valeriy
Published: December 2022

In this paper, a novel model is presented to describe the composite mechanical properties degradation during cyclic loading. The model is based on cumulative distribution functions using. Weibull probability distribution law and beta distribution are considered. The dependences of the fatigue sensitivity coefficient on the preliminary cyclic exposure are derived. The damage value function derivative using is proposed to define damage accumulation stages boundaries. Model parameters are obtained using experimental data. Determination coefficients are calculated. A high descriptive capability is noted. Rationality and expediency of using cumulative distribution functions as the approximation of experimental data on mechanical characteristics reduction after preliminary cyclic exposure is concluded.
Numerical nonlinear analysis of RC beans with un-strengthened and CFRP-strengthened opening drilled under service loads within shear zones
Authors: Khalaf Magdy , Aboul-Nour Louay , Khater Mahmoud , Ibrahim Marwa
Published: December 2022

Current research paper deals with reinforced concrete (R.C.) beams numerical modeling and suggested strengthening procedure if it is required to create an opening within their shear zones. Strengthening is assumed to be achieved during different service load application conditions. Reinforced Concrete beams with rectangular or circular opening in shear zone; as critical regions; sustain two concentrated system of loads are tested till failure before and after performing suggested opening assessing technique by means of Carbon Fibers Reinforced Polymer sheets (CFRP). The main aim of this research is simulating real practice situation where the beam is subjected to service loads, supported temporary by means of hydraulic jacks, opening is created and strengthening is performed then jacking supports are released. Results of achieved numerical nonlinear modeling are introduced and influence of strengthening achieving on improving assessed beams almost structural behavior such as initial cracking loads, load deflection curves, cracking patterns, failure loads & modes for reference (without opening), main un-strengthened control beams, and CFRP strengthened opening beams are introduced and analyzed in details. Some important conclusions & recommendations for designer and executive engineers are stated.
Pattern of Out-of-Class Activities of Korean University Students: Latent Profile Analysis
Authors: Bae Sang Hoon , Hwang Soo Jeong , Byun Bo Kyoung
Published: December 2022

This study examined how HIP participation patterns differ among students in different Korean universities. Moreover, this study explored whether there is an association between the likelihood of a student belonging to a specific group and their individual characteristics along with their university’s supportive campus environment. This study analyzed the data from the 2019 wave of the Korean-NSSE (National Survey of Student Engagement), and the samples included 12,784 college seniors from 112 institutions. Furthermore, it employed latent profile analysis and multinomial logistic regression. As a result, this research identifies five distinctive HIP participation patterns. Family income and student-faculty interaction levels determine which group a student belongs to. For example, economically disadvantaged students tend to belong to a group with lower participation in study abroad programs. Finally, the supportive campus environment was strongly associated with being a member of actively participating groups compared to being in a less engaged group.
Abenteuer Schülerfirma – Von der ersten Idee in die Schieflage und zur Problemlösung
Authors: Hienzsch Felix
Published: December 2022

Anhand des fiktiven Gründungszenarios einer Schülerfirma können die Lernenden elementare Probleme und Prozesse der Unternehmensgründung entdecken. Dieser Kontext eignet sich besonders aufgrund von dessen Anschlussfähigkeit an die Lebenswelt der Lernenden sowie für die Problematisierung eines Gründungsszenarios. Weiterhin stellen Schülerfirmen reduzierte Nachbildungen realer Unternehmen dar. Dem Gegenstand selbst liegt somit schon eine inhärente didaktische Reduktion zugrunde, die deshalb für die Behandlung von Unternehmensgründungsprozessen mit jüngeren Lerngruppen besonders geeignet ist. Das Unterrichtsvorhaben eignet sich ab der achten Klasse und dauert ca. fünf Unterrichtsstunden.
Die Notwendigkeit der Pluralität im Diskurs über Verständnisse von Demokratie und die Unverzichtbarkeit einer nicht-affirmativen demokratischen Erziehung. Eine Erwiderung auf den Beitrag von Edwin Stiller in Politisches Lernen 1-2|2022
Authors: Röken Gernod
Published: December 2022

In meiner Antwort auf Edwin Stillers Darlegungen konzentriere ich mich auf einige relevante Gesichtspunkte und strebe ein Herausmodellieren der kontroversen Vorstellungen an, sodass ein nachvollziehbarer Diskursraum angeboten wird. Die jeweiligen Argumente von Edwin Stiller sollen auf ihre Überzeugungskraft, auf ihre Geltungsansprüche geprüft und in ihren Begründungen in einer gekürzten Darstellung hinterfragt werden. Dabei soll das Gebot wechselseitiger und kritischer Anerkennung nicht außer Acht gelassen werden, da ich keineswegs das eigene Verständnis für allein maßgebend erachte, aber die Gegenposition auf der Grundlage meiner Geltung beanspruchenden Argumentation als streitbar erachte.
To “Evaluate the Mental Powers of the Indian Children": Race and Intelligence Testing in Canada's Indian Residential School System
Authors: Giancarlo Alexandra
Published: December 2022

Scholars have examined how theories of race-based intelligence as they relate to IQ testing have impacted Canadian society in the realms of educational policy, immigration, and public health, yet little research has focused on the role of IQ and other intelligence testing in the Indian residential school system. When administrators observed students’ poor grade progression, they sought not to reform a system that forced the children to work for at least half the day, but rather to blame students’ home environments and supposedly hereditary racial traits. This paper examines the social scientific context of intelligence testing in residential schools in the early to mid-1900s and argues that testing results—a biased and inaccurate measure of mental ability—played a role in justifying the schools’ emphasis on a limited academic curriculum. It argues that the data gathered on Indigenous mental deficiency came to form part of the “official information” guiding the Department of Indian Affairs’ administration of the residential school system. Ultimately, discourses of race-based mental inferiority impacted the type and quality of education provided to Indigenous children with reverberations down to the present day.
Plumbing the University of Toronto: William James Dunlop and the History of Adult Education in Canada
Authors: McLean Scott
Published: December 2022

Working as the director of University Extension and Publicity for the University of Toronto from 1920 to 1951, William Dunlop built a large and diverse set of adult education programs, developed an influential discourse of extension, and sustained support for the adult education movement from three university presidents. This article explains the rise of institutional commitment to extension work due to political, financial, and competitive factors and demonstrates that the enduring outcomes of Dunlop’s work included programmatic forms through which university extension was delivered and discourses through which extension work was positioned at Canadian universities. Rather than accept the rhetoric of university leaders—that the extension movement was about the democratization of higher education—scholars should recognize that the engagement of universities in extension work was rooted in those institutions’ struggles for resources and was implicated in the role of universities as agents in developing new forms of social class relations.
Study on Special Temperature Measuring Equipment for Fermentation Bed in Large Scale Chicken Farm
Authors: Tang Wanpeng , Wen Weijian , Tang Qingsong
Published: December 2022

In this paper, a kind of temperature sensor for fermentation bed in large scale chicken farm was studied. The temperature sensing equipment includes a temperature sensor housing, a circuit board and a temperature probe detection sensor. The circuit board is provided with a microprocessor and a wireless Bluetooth communication module. The temperature probe detecting sensor is fixedly connected with the sensor housing, and at least two temperature detecting elements are arranged inside the temperature probe detecting elements, which are spaced inside the probe tube. The microprocessor is connected with the temperature detecting element and wireless Bluetooth module respectively. The temperature sensor is used to detect the wall temperature of the probe tube and generate temperature signals. The microprocessor is used to receive the detection signals and forward them to the wireless Bluetooth module. The wireless Bluetooth module is used to convert the temperature detection signals into wireless signals and send them out.
Image Recognition Technology and Development of YOLO Algorithm
Authors: Wu Chenbo , Luo Qiang , Shou Derong
Published: December 2022

With the rapid development of image recognition technology, it has its applications in medical, security and other fields, but this technology has many areas to be improved, such as the accuracy of recognition, real-time and other issues, which have always been a hot research topic in this field. This article involves the development process of image recognition (traditional image processing, machine learning, deep learning), and focuses on the advantages and disadvantages of the popular YOLO algorithm in image recognition. Finally, it describes the technical problems faced by the current target detection technology and the corresponding solutions.
Safety Helmet Monitoring of Power Grid Staff Based on Improved YOLOv3
Authors: Rao Fanxing , Xi Xianchang , Wu Shaobo , Sheng Jing , Zhang Yang
Published: December 2022

Aiming at the problem that the staff do not wear safety helmets or even wear safety helmets in the construction and maintenance of new energy charging stations, an improved YOLOv3 safety helmet detection method is designed in this paper. Firstly, the 128*128 feature map output is added based on the three feature map output of YOLOv3 algorithm, and then the FI module is added to fuse the four scale feature information to improve the detection accuracy of small targets. Firstly, on the basis of the 3 feature map outputs of the YOLOv3 algorithm, 128*128 feature map outputs are added, and then the FI module is added to fuse the information of the 4 scale feature information to improve the detection accuracy of small targets; Secondly, the DIoU function is used to optimize the boundary frame loss function, so that the boundary frame regression is more accurate. Compared with the original algorithm YOLOv3, the proposed algorithm has higher detection accuracy, shorter time consuming and meets the requirements of real-time detection. Compared with other advanced algorithms, the robustness, detection accuracy and detection speed of the proposed algorithm are better, which can provide technical reference for avoiding staff safety hazards.
Design and Implementation of Mini Program for College Students’ Psychological Test Based on Behavioral Characteristics Recognition
Authors: Jiang Pan , Zhang Tong
Published: December 2022

In modern society, due to the diversification of information and the acceleration of network communication, the barriers of communication between teachers, parents and college students are increasing, so that teachers or parents can’t understand the psychological state of contemporary students in time. When college students have psychological problems, they are more willing to ask for help from classmates and friends than from teachers or psychologists. Therefore, this system is devoted to solving the problem that college students are not willing to talk to their teachers and parents, and providing the characteristic psychological analysis function for college students to evaluate their psychological state. Firstly, This paper describes the research background and significance, and then, it introduces Wechat Mini Program, Springboot framework, database and behavior recognition technology. On the basis of the above, the overall architecture, functional structure and database of the system are designed. Finally, the functional modules of the system are coded. The system interface is beautiful, easy to operate, and set practicality and interest in one, can let college students more understand their psychological state, face mental health problems.
An Improved Neural Network Method for Plant Leaf Recognition
Authors: Guo Chunlai , Guo Chunmei , Cui Li , Cao Xianying , Wang Guanhua , Wang Jianmin , Ma Yingchen
Published: December 2022

Under the background of the general plan for general survey of Germplasm Resources issued by the State Forestry and grassland administration, in order to establish the forest and grass germplasm resources management system, it is urgent to identify the forest vegetation types. In the past, manual identification was often used, which was inefficient and had a high error rate. Considering the small number of samples in the plant leaf database, in order to improve the accuracy of plant leaf identification, In the framework of tensorflow, a convolution neural network method for plant leaf image recognition based on transfer learning is proposed. Firstly, the plant leaf image is preprocessed, and the plant leaf image data set is expanded through the horizontal transformation, random clipping, translation transformation, color and illumination transformation of the original image, and is divided into training set and test set in the ratio of 7:3, the concept V3 model is applied to image data processing by migration learning. The trained models ResNet50 and Concept V3 are migrated and trained on the plant leaf image data set, and the full connection layer is replaced in the pre training model, so that it can adapt to the recognition of plant leaf images. The accuracy of the test set obtained from the pre training model of this method is 95.22% and 95.45%, reaching the excellent level required by the task.
Application of Car-Following Model Based on Neural Network to FCEV Power System
Authors: Wang Tianxiang , Min Dehao , Zhang Tong
Published: December 2022

In order to improve the overall economy of fuel cell vehicle, this paper proposes an energy management strategy based on the Car-Following Model of Long Short-Term Memory Neural Network (LSTM-CFM), which classified vehicles according to the Vehicle_ID, Frame_ID, Global_Time and other core data based on the vehicle information collected from the Next Generation Simulation (NGSIM) data set on the US 101 highway in south California. The two adjacent vehicles were identified and the data were extracted and processed into the LSTM-CFM for training. In the simulation stage, UDDS (a standard driving condition) is taken as the driving condition of the followed vehicle and 50m is taken as the initial distance between the following vehicle and the target vehicle. Under these initial conditions, we can get the speed prediction data of target vehicle based on the Car-Following model. The energy management strategy is designed based on the principle of minimum equivalent fuel consumption, and the equivalent factor can be solved by using the speed prediction. The simulation results show that the economy of the fuel cell vehicle under the LSTM-CFM energy management strategy is better than that of the rule-based strategy, which verifies the effectiveness of the LSTM-CFM energy management strategy.
Research on a Garbage Distribution Bucket Based on Intelligent Voice
Authors: Tao ZhiXiang , Wang Jing , Qiu Xiufang , Li Minyi
Published: December 2022

With the development of economy and the improvement of people’s living standards, the garbage problem has become increasingly prominent, and people’s concept of environmental protection has been continuously enhanced. In response to the popularization of garbage classification and environmental pollution of garbage, the industry has seen innovative designs for traditional garbage bins. The intelligent waste distribution bin studied in this paper adopts micro-control chip, infrared detection device, mechanical transmission device and linkage mechanism, which can solve the difficulty in separation from the source, cultivate the public’s awareness of waste separation and reduce the cost of waste disposal, It protects user privacy and improves security through blind processing, and thus has practical research significance.
Local Motion Planning Subject to Constrained State for Quadrotor with Model Predictive Control
Authors: Lu Guolin , Zhang Shihuan , Jiang Jinhong
Published: December 2022

As for the challenges of local motion planning subject to constrained state for quadrotor in evaluating the health status of photovoltaic power generation in complex environment, including fast replanning, limited onboard computational resources, a practical framework for constructing motion trajectory from the bounded states is proposed in this work. The references and nominal inputs are made by the scheme of receding horizon fashion of model predictive control (MPC) by means of gradient-based method in the continuous domain. In order to avoid the complex calculation of the optimal gradient, the ability of approximation of a neural network make it possible for the fast evaluation and online optimization. The simulations with variety types of trajectories are made by means of a quadrotor to demonstrate the good efficiency and real-time of the proposed approach.
Simulation of High Temperature Thin Film Thermocouple on Engine Blade Surface
Authors: Zhang Meiju , Tian Bian , Ma Rong , Huang Manguo , Liang Xiaobo , Liu Jiangjiang , Zhang Zhongkai
Published: December 2022

In order to avoid the instability flutter of aero-engine blade and prevent the failure of thin film thermocouple caused by the blade in complex environment, the structural strength of the thermocouple on the actual blade surface was studied in this paper. Firstly, based on the 3D scanning of the real blade, the blade model is established after the point cloud graphics. The surface thermocouple model of the blade is established in Solidworks for simulation, and the modal and harmonic response analysis of the blade is simulated. Secondly, the vibration of the curved thin film thermocouple and the stress distribution of the blade under the acceleration shock were studied in Comsol, and the failure weakness was analyzed to avoid the failure of the thin film thermocouple caused by the bending, fracture or shedding of the thin film thermocouple on the blade due to vibration and shock, providing the most suitable thermocouple selection for the engine blade.
Three-Coordinate Localization Method of Monocular Vision Robot Target Based on BP Neural Network
Authors: Sun Lixin , Xie Wenyu , Gao Chunyan , Zhang Minglu
Published: December 2022

At present, the monocular vision robot target localization under the condition of unknown depth information is still difficult. So, a method based on multi-level residual neural network was proposed for Targets in three-dimensional space localization. The target image segmentation was realized by lightweighting YOLOv5s. The traditional method was used to segment and process the target image more accurately. And a function representing the world coordinate system and image features was derived according to the camera imaging model. Three neural networks were designed to map this function. The experimental results show that the highest positioning error of this method is 0.747%.
Research on Human-Computer Interaction on the Field of Intelligent Vehicles
Authors: Zhao Shuyan
Published: December 2022

With the development of information technology and Internet technology, the functions inside the car are constantly integrated, and the operation mode is increasingly complex. The traditional functions of the car cannot meet the growing needs of human beings. The new era of intelligent cars requires the participation of human-computer interaction, so that the car is more intelligent and more modern. Human-computer interaction refers to the process of information exchange between human and computer by using a certain dialogue language and in a certain interaction way to complete certain tasks. An important problem of human-computer interaction is that different computer users have different usage styles – they have different educational backgrounds, different ways of understanding, different learning methods and different skills, as well as cultural and ethnic factors. Secondly, the research and design of human-computer interaction needs to consider that the user interface technology changes rapidly, and the new interaction technology provided may not be applicable to the previous research. This paper discusses the research of human-computer interaction in the field of intelligent vehicles from the perspectives of voice interaction, vehicle voice image personality, visual gesture recognition and on-board music control.
Study on Dynamic Resource Scheduling Method for Domestic Operating System Virtualization Based on Computing Domain
Authors: Yang Chao , Liu Pengyu , Liu Wangxin , Sun Junwei , Li Dongyang
Published: December 2022

Virtualization of computing resources has become a mainstream technology in the computer world. This paper takes the performance optimization of resource virtualization platform on domestic operating system as the research object, deeply analyses the hardware support technology of virtualization, and the corresponding software principle and mechanism. From the point of performance research and improvement of resource virtualization, the Computer Domain (CD) based on virtualization technology is proposed. Based on the software driving principle and operating mechanism of the Virtual Manage Platform (VMP) kernel module for computational area analysis, three optimization directions are proposed: resource virtualization scheduling, I/O optimization and VM immersion optimization. The computing domain based on resource virtualization unifies the consistency of resource scheduling and improves the efficiency of resource scheduling. The experimental results show that the dynamic resource scheduling method based on computing domain can achieve significant performance improvement.
Research on the Construction of a Fifth-Dimensional Battlefield Based on UAVs – Integrated Electronic Warfare System to Seize Electronic Magnetic Rights
Authors: Yan Dong , Gan Fajin , Tian Yaming , Xing Huankui , Wu Haiyu
Published: December 2022

The electromagnetic battlefield is the fifth-dimensional invisible battlefield above the tangible geographical battlefield of land, sea, air and sky. The integrated electronic warfare system is a killer to seize the right to control the electromagnetic properties of the system to the system and the organization to organization in modern war. Unmanned aerial vehicle has significant advantages in terms of endurance, combat distance and mobility, which are more suitable for application in electronic warfare. In this paper, a method of constructing an integrated EW system based on UAVs is proposed, which takes integrated design, integrated control, integrated management and comprehensive application as the core. The single platform is realized through the hardware integrated of general sensors, general antennas, general interfaces and general processers, as well as software drivers of flight management, load management, navigation management and platform management. The multiplatform is realized through satellite platforms, high-altitude and long-endurance UAVs, medium-altitude and long-endurance UAVs, medium-low altitude and long-endurance UAVs, vertical takeoff and landing UAVs, underwater UAVs, ground equipment and vehicle-mounted platforms. By means of combat classification commands, intelligence hierarchical processing and distributed confrontation to make each defense zone and each system can not only fight independently but also command cooperatively. The repeated use of force is reduced, the effective use of intelligence is improved, and the continuous combat force is ensured through the comprehensive management of three armed forces. Through the combination of peace and war, far and near, air and land, soft and hare, and true and false to maximize the effectiveness of integrated electronic warfare system most efficient. Therefore, the method in this paper will surely become a brand-new conceptual weapon with a high cost-effectiveness ratio and both attack and defense, which is of military significance.
Research on Error Tracing of Synchronizer Gear Hub Based on Variable Step Fa-Rbf Neural Network
Authors: Liu Yongsheng , Cai Shiyang , Zhao Jin , Chen Yixin , Hui Jizhuang
Published: December 2022

The synchronizer gear hub has a complex structure and involves a wide variety of processing equipment. It is difficult to trace the reason for the abnormal fluctuation of the processing quality by simply detecting the data of local processing conditions. Based on the analysis of the machining error of gear hub, an error tracing method based on the radial basis function (RBF) neural network which optimized by variable step firefly algorithm (FA) was proposed. The FA-RBF error tracing model was built based on the machining error, gear hub quality feature information and the error influencing factor, and the relevant parameters of the neural network were optimized through the variable step firefly algorithm. The verification experiment was done by 164 groups quality data collected from a gear hub production line, 159 groups of the data were used to train the model and 5 groups of the data were used to test it. The experimental results show that the support degrees of the corresponding error types of the 5 groups test data are 0.882, 0.889, 0.98, 0.895 and 0.768. It means that the error types can be accurately traced by the proposed error tracing method. The method can effectively identify the error source of abnormal fluctuation of machining error during the machining process, and it can provide a basis for error compensation.
Design and Precision Analysis of Hydraulic Turning Mechanism for Spent Fuel Cladding Assembly
Authors: Yang Kai , Wang Xiangjiang
Published: December 2022

In order to meet the nuclear industry’s requirements for post-processing of spent fuel cladding assemblies, the design of the spent fuel cladding assembly inversion mechanism was completed through the analysis of the design and research of the inversion mechanism at home and abroad. In order to ensure the machining accuracy of the system, the accuracy of the hydraulic turning mechanism is analyzed based on the mathematical model and finite element simulation software. The analysis shows that the thermal error caused by the heat fluctuation caused by the external load will be caused by the ball screw in the hydraulic turning mechanism during the transmission process. Deformation, the pitch error caused by the wear of the ball screw and the ball during long-term contact use, and the machining error caused by the processing process, etc., these factors will affect the transmission accuracy of the hydraulic turning mechanism to a certain extent. Finally, according to the results obtained from these analyses, a specific solution is given to solve it.
A Multi-Target Detection Method on Distribution Cabinet Based on Improved Faster R-CNN
Authors: Sun Zhenguo , Huang Tianzhi , Wang Donghua
Published: December 2022

It is an inevitable trend to detect and recognize the states of different component on distribution cabinet panel more effectively and accurately by using inspection robots instead of manpower. Aiming at the problems of multiple recognition targets and large size difference in image recognition of distribution cabinet panel, an improved Faster R-CNN multi-target detection method is designed. Automatically detect and recognize of different targets on required cabinet panel is achieved by this method. In this paper, Resnet50 is used instead of VGG16 as the feature extraction network in Faster R-CNN, Adam Optimizer is used instead of Momentum, and anchor box size is changed to adapt target size difference on cabinet panel. Experiments show that the improved model has higher accuracy and less computational cost on the required distribution cabinet panel dataset.
Research on Artificial Intelligence Technology Promoting High-Quality Development of High-End Equipment Manufacturing Industry – A Case Study of Linyi City, Shandong Province
Authors: Wang Yong , Kang Kenan , Kong Qingdong , Ge Xiaohan
Published: December 2022

The high-quality development of the high-end equipment manufacturing industry is inseparable from the support of emerging technologies. As a typical emerging cross-cutting technology, artificial intelligence has been widely used in many fields of the high-end equipment manufacturing industry in Linyi City, Shandong Province. Combined with the application of artificial intelligence technology in the local high-end equipment manufacturing industry in Linyi, the paper analyzes and explores the impact of artificial intelligence technology on the development of high-end equipment manufacturing industry, and focuses on artificial intelligence technology in construction machinery, agricultural machinery, intelligent manufacturing equipment, new Specific application cases of key equipment manufacturing industries in Linyi City, such as energy vehicles and parts, illustrate specific measures and methods on how to apply artificial intelligence technology to promote the development of high-end equipment manufacturing industries.
A Modified Multiple Properties Constrained Target Detection Algorithm Based on Extended Morphology for Hyperspectral Imagery
Authors: Wu Hulin , Deng Xianming , Zhang Tiancai , Li Zhongsheng , Cen Yi , Zhou Kun , Wang Jiahui , Wu Falin , Chen Zhihua , Xu Lang , Zhu Fan
Published: December 2022

We proposed an improved target detection algorithm for Hyperspectral Imagery, referred as EXmorMPCTD (extended morphology based Multiple Properties Constrained Target Detection). By comparing the spectral difference between targets and sample pixels of hyperspectral image and selecting the pixels with conspicuously different spectral characteristic with targets to construct the background characteristic matrix, efficiently reduces the interference information and improves the accuracy of background characteristic matrix extremely. We carried out the validation test of the proposed algorithm. The results show that the detection accuracy of the traditional algorithms MCEM, ACE, OSP and TCIMF is 0.9264, 0.9057, 0.8843 and 0.8581, while the detection accuracy of the proposed algorithm in this paper reaches 0.9922. The DI (Detection Index) is also increased from 0.611,0.608,0.601 and 0.5940 of the traditional algorithms MCEM, ACE, OSP and TCIMF to 0.669 of the proposed algorithm in this paper.
Study on Dynamic Characteristics of High Speed Projectile Impacting Concrete Target
Authors: Cheng Desheng , Pu Wenjing , Huang Lingling
Published: December 2022

In this paper, the dynamic characteristics of projectile penetrating concrete target at high speed are studied. The mechanism of high-speed projectile penetration into target plate is analyzed theoretically. Through ANSYS-LSDYNA numerical modeling, a numerical model is established, and a suitable grid model is divided. The numerical calculation of projectile deflection, kinetic energy loss, stress distribution and overload characteristics of high-speed projectile penetration into target plate is carried out. The calculation results show that the software simulation method can better reflect the phenomenon of the high-speed projectile penetrating into the concrete pit. The penetration speed of the projectile has an impact on the projectile offset, kinetic energy loss, stress distribution and overload characteristics during the penetration process, but these effects are not linear, especially the overload characteristics of the projectile. The overload of the projectile penetration process exists in the form of shock pulses, The characteristics of shock pulse overload have great influence on the structure design of projectile.
Validation of Airborne Bathymetry Using Long-Short Term Memory Neural Network
Authors: Sayfeddine Daher
Published: December 2022

Drones are adaptable technologies that can be used in several applications. They are especially effective in monitoring and surveying tasks due to the low cost and time embedded in such operations. Unmanned Aerial surveys can be repeated with minimal abortive cost and do not require special setup. The ability to carry wide spectrum of airborne sensors render these platforms optimal and compatible with different flight missions and real-time scenarios. This paper carries out a study on bathymetric technique. Datasets obtained by real airborne bathymetry are used to train an LSTM neural network that will be implemented as quality control for the fathometer reading prior to further processing. The extrapolated values will serve as an orienteer for flight mission success depending on auto and partial correlation of the dataset.
Design of Automated Warehouse Storage Scheme in Crop Genebank
Authors: Lin Yunan , Chen Yanqing , Fang Wei , Cao Yongsheng
Published: December 2022

The contributions of crop germplasm resources to food security depend on their conservation and accessibility for use. The automated warehouse has begun to be applied to the ex situ preservation of crop germplasm resources in the crop genebank. Identifying the proper storage scheme for potentially hundreds of thousands of seeds is a primary task that faces the crop genebank manager during the design of a new automated crop genebank. There are mainly three areas to focus on, hardware and software, seeds storage assignment policy and seeds labelling technology. This paper aims to propose automated crop genebank storage schemes for two kinds of crop genebank (the long-term crop genebank and the middle-term crop genebank), which supports managers in determining the technologies that can be applied in the automated crop genebank. Firstly, the selection of hardware and software should be based on the functional orientation of the long-term crop genebank and the middle-term crop genebank. Secondly, for the seed storage assignment policy, the sequential storage assignment is designed for the long-term genebank while the cache storage assignment is developed for the middle-term genebank. Finally, a QR code labelling technology based on image recognition is designed for both the long-term crop genebank and the middle-term crop genebank.
Communication Quality Indicator System of Industrial Communication Network and Related Diagnostic Evaluation
Authors: Liu Dan , Tang Chune , Li Wenjuan , Wang Zhen
Published: December 2022

The industrial communication networks are the infrastructures to connect the bottom field devices and control devices in the factory, which realize the interconnection and interoperability of intelligent manufacturing. Its communication quality is a prerequisite to ensure the normal operation and production in the factory. According to the layered functions of industrial communication network protocol, this paper establishes a communication quality indicator system, consisting of physical layer waveform characteristic indicators and time characteristic indicators, data link layer performance indicators and function indicators, and application layer behavior related indicators. The general process of industrial field communication quality diagnosis and evaluation is proposed. Through the detection of industrial communication quality indicator parameters, the possible problems in the field can be diagnosed and evaluated, thus the rapid location of communication anomalies or faults in the industrial field can be achieved.
Compensation Methods for Industrial Robotics Under Varying Payloads with Deep Reinforcement Learning
Authors: Xiao Wenlei , Sun Zihui , Qi Qi
Published: December 2022

Due to the weak rigidity of an industrial robot, its end effector usually has poor absolute positioning accuracy, especially under varying payloads. Such situation is common in scenarios of handling, machining and tool changing. Conventional off-line calibration or compensation methods can only eliminate systematic errors, while such methods are invalid to the dynamic errors brought by varying payloads. This paper proposes a deep reinforcement learning(DRL) approach to solve the problem of dynamic errors, in consideration of external payloads changed manually. An online full closed loop system is established to verify the proposed method, which consists of a KUKA robot KR6, a Leica laser tracker, and a BECKHOFF PLC controller. The robot and the laser tracker work as the slavers of the master PLC controller, in between the communication is accomplished using EtherCAT. Logically, the robot is controlled by mxAutomation and the laser tracker is connected to an embedded EtherCAT slave card. Experiments on the robot demonstrate the effectiveness of the proposed DRL methods. The changed payloads range from 1.177Kg to 4.179 Kg, while the position accuracy of the robot can be maintained no more than 0.4mm by the DRL algorithm.
Research on Energy Management Strategy of Fuel Cell Hybrid Electric Vehicle Based on Multi-Objective Optimization
Authors: Liu Shikun , Wan Zhiwen , Hu Xiao , Zhang Tong
Published: December 2022

In this paper, an estimation model of fuel cell life degradation and lithium battery life degradation is defined based on experimental data. A dynamic programming algorithm based on global optimization is proposed, which takes the total equivalent hydrogen consumption cost of power system and the cost of fuel cell power degradation as the target function, and weights the power degradation term of fuel cell with a penalty coefficient, so that the designed energy management strategy can take into account the economy and durability of the vehicle. Considering that the control strategy based on global optimization is sensitive to operating conditions, i.e. the reduction of hydrogen consumption and fuel cell degradation costs by dynamic programming algorithm is based on operating conditions. Once the input condition of operating conditions is changed, the control strategy will not guarantee the optimum. Therefore, this paper uses the optimal results of dynamic programming algorithm to provide the data set of off-line training. Transformer is applied to make time series prediction, which will help to solve the problem of balancing power distribution considering economy and durability under various conditions. The input characteristics of the transformer network are the current bus demand power, the battery state of charge and the fuel cell power of the previous time, and the output is the fuel cell power predicted at the current time. The results of Transformer model are compared with those of dynamic programming, and they are very close. The Transformer model was trained using standard UDDS and NEDC operating conditions and tested on HWFET. The test shows that the developed Transformer model has good generalization ability for different operating conditions.
Fouling and Secondary Water Chemistry of CPR1000 Steam Generators
Authors: Chen Jie , Zhao Qingsen , Peng Weidi , Xia Peng , Tian Fujun , Yang Jie
Published: December 2022

Steam generators (SGs) performance degradation is one of the important concerns of nuclear power plants, which not only affects safety, but also affects the outputs in some power plants. With the large number of CPR1000 nuclear power plants put into commercial operation in China, some plants also experienced the steam pressure loss at the SGs secondary side. Compared with the known empirical laws and phenomena, the duration of the steam generator pressure loss in CRP1000 units is longer, and there are large differences between different units in different fleets. The typical trends in SGs thermal performance includes: a) an early steam pressure loss phase with a penalty of 0–1.6bar, b) a subsequent increase in steam pressure which often, but not always, results in net heat-transfer enhancement, and c) a more gradual long-term decreases with an average rate that depends on the iron transport rate and deposit characteristics. The CPR1000 units basically follow the secondary circuit control process of EDF, using NH3 and N2H4 to control the feedwater pH Value. The control target of pH value is between 9.6–9.8, and each fleet is consistent. This is a significant deviation from the different steam generator thermal performance trends. It can be seen that micro scale has a great impact on the thermal performance, which should be paid more attention, especially in the early stage of steam generator operation. Plants which have experienced a higher ratio of particulate to soluble impurity concentrations in feedwater have tended to experience smaller detrimental, or even beneficial, effects of the developing scale while others with relatively high soluble impurities have exhibited thermal performance decreases. This difference in behaviour is thought to be the result of a fundamental difference in the resulting deposit morphology. Specifically, particulate deposition is believed to enhance the population density of boiling nucleation sites on the tube while precipitating deposits tend to decrease this population density. Higher hydrazine concentrations may result in an elevated distribution of soluble iron that could decrease the population density of boiling nucleation sites. This increase in soluble species not only can form a dense scale layer that would add conductive resistance, but also lead to a decrease in boiling heat transfer coefficient. Both effects result in a performance decrease that reduces steam pressure. However, despite the promise of this line of research, no definitive guidance is yet available.