Development Of Processing Technology Research Articles

MS-Net: a novel lightweight and precise model for plant disease identification.

The rapid development of image processing technology and the improvement of computing power in recent years have made deep learning one of the main methods for plant disease identification. Currently, many neural network models have shown better performance in plant disease identification. Typically, the performance improvement of the model needs to be achieved by increasing the depth of the network. However, this also increases the computational complexity, memory requirements, and training time, which will be detrimental to the deployment of the model on mobile devices. To address this problem, a novel lightweight convolutional neural network has been proposed for plant disease detection. Skip connections are introduced into the conventional MobileNetV3 network to enrich the input features of the deep network, and the feature fusion weight parameters in the skip connections are optimized using an improved whale optimization algorithm to achieve higher classification accuracy. In addition, the bias loss substitutes the conventional cross-entropy loss to reduce the interference caused by redundant data during the learning process. The proposed model is pre-trained on the plant classification task dataset instead of using the classical ImageNet for pre-training, which further enhances the performance and robustness of the model. The constructed network achieved high performance with fewer parameters, reaching an accuracy of 99.8% on the PlantVillage dataset. Encouragingly, it also achieved a prediction accuracy of 97.8% on an apple leaf disease dataset with a complex outdoor background. The experimental results show that compared with existing advanced plant disease diagnosis models, the proposed model has fewer parameters, higher recognition accuracy, and lower complexity.

Research on pruning optimization techniques for neural networks

Large deep neural networks have been deploying in more and more application scenarios due to their success in multiple application scenarios. However, deep neural networks are difficult to apply to devices with fewer resources, as the large models and huge demand for computing resources make this difficult. Pruning optimization, as a critical model compression method, has become an essential part of the deployment process of deep neural networks and has extreme significance. This article summarizes the methods of deep neural network pruning optimization technology, sorts out the current research status of pruning optimization technology, analyzes different fine-grained pruning optimization technologies based on the different fine-grained levels of pruning optimization technology, and comparing the characteristics of different fine-grained pruning optimization techniques. This article also introduces the development process and current development direction of different fine-grained pruning optimization technologies, compares the effectiveness differences between different fine-grained pruning optimization technologies and looks forward to the combination of pruning optimization technology and model quantification technology. The end of the paper summarizes pruning optimization techniques and provides prospects.

A novel collaborative bearing fault diagnosis method based on multi-scale dynamic fusion network under speed fluctuating condition

Improving bearing fault diagnosis accuracy under speed fluctuation is a challenge in engineering applications. With the development of big data processing technology, a new solution, multi-sensor complementary information, has emerged. However, single-scale dimension compression, which is adopted in most multi-sensor data fusion methods, captures only a small amount of valuable information. To deal with this deficiency, a multi-scale dynamic fusion network (MSDFN) is proposed. First, considering the existence of non-stationary features in the fluctuating speed signal, the FReLU function is adopted to activate the features after considering contextual information. Then, multi-sensor features are fused by multiple scales to obtain richer feature information, and fusion features at different scales are weighted by using the attention mechanism. Finally, batch normalization is employed to standardize the variable speed feature distribution. The validity of the MSDFN is proved by conducting fault diagnosis experiments on two bearings under speed fluctuating conditions. Experimental results indicate that the MSDFN is not only effective in identifying various types of fault samples, but also shows higher stability in multiple trials when compared with other methods.

Oat and Oat Processed Products—Technology, Composition, Nutritional Value, and Health

Oat has been known in food technology and human nutrition for a very long time. Its rich chemical composition and high nutritional value make it of interest to scientists in the field of food processing technology as well as nutritionists. Low-processed, whole-grain oat products rich in biologically active substances with well-proven preventive and therapeutic effects include not only dehulled oat grains and groats but also a wide range of breakfast cereals. These products fit into the definition of functional foods and are considered excellent prebiotics. The continuous development of cereal processing technologies can improve existing cereal products and help to create new ones; however, it also increases the possibility of raw material over-processing, thus decreasing its functional properties. Therefore, monitoring technological progress and the quality of the products obtained is of great value and interest for nutritionists and consumers. The work presented here aims at systematizing existing knowledge on oat products, their impact on human health, and progress in oat processing technology. It also brings insight into various new avenues for the utilization of oat products in food technology.

Aspects Regarding of Nanomaterials and Nanocomposites in 3D Printing Technology Process Development for Application in Biomedicine

This paper will present the advantages of developing the 3D printing process of nanomaterials in different fields such as electronics, biomedical and bioelectronics. As it is already known, nanomaterials are starting to become more and more useful, and more emphasis is being put on the development of new technologies to enable the use of these materials. Nanomaterials consist mainly of chemical substances made up from very small particles that are no larger than a hundred nanometers. These materials occur in nature, they can be an accidental product of human activity, or they can be consciously made to develop new characteristics such as strength, chemical reactivity or increased conductivity compared to the same material that does not display nanometric characteristics. By integrating nanomaterials to 3D printing technology, it is possible to create unique structures, which are difficult to achieve. Nanomaterials can possibly work on personal satisfaction and add to the advancement of European industry. However, new materials can also pose health and environmental risks. Scientific research has turned its attention to the potential outcomes of the production and application of nanomaterials. Meanwhile, the newest method for 3D printing of nanomaterials is Multiphase Direct Ink Writing (MDIW), a method developed from Direct Ink Writing (DIW), a revolutionary additive manufacturing mechanism with wide applications in structural engineering systems, thermal isolation, electrical conductivity, optical reflectivity, and biomedical scaffolds.

Possibility Assessment of Automatic Formation of Technological Processes in Small Batch Production

The work is devoted to urgent problem solution of lack of convenient tools with functional capabilities of the system of route technological process automated design, adapted to small-scale production. The estimation of potential possibility of automatic small-scale production formation by means of estimation of efficiency and expediency technological processes of automation of key stages of design of production technological preparation, such as equipment selection, selection of cutting modes, workpiece, cutting and measuring tools and tooling selection is given. The key stages of technological process development are considered and characterized, such as selection of technological bases, type of workpiece and equipment, formation of route technological process, calculation of cutting modes, selection of allowances and so on. The paper shows both the relevance and necessity of analyzing approaches to automation and their correct adaptation to production needs to achieve maximum efficiency and resource savings for small batch production, and the high relevance for small-batch production of the automatic formation of route technological processes. At the same time, the paper shows the lack of automated systems adapted to the specifics of small-batch production. The existing approaches to the formation of stages are analyzed, as well as the possible methods of automation of stages and the existing limitations of these methods are considered, the efficiency of the considered approaches is evaluated. The methods of automation of separate stages of technological preparation of production are analyzed and the efficiency of the considered approaches is evaluated. The original concept of solving the problem of automation for small-scale production by using a combination of a limited number of standard solutions, represented as a set of technological parameters or knowledge base, with individual solutions, adapted to the specifics of enterprises and industry, is proposed and the potential effectiveness of this approach is shown.

Psoriasis Skin Disease Classification based on Clinical Images

Psoriasis is an autoimmune skin disorder that causes skin plaques to develop into red and scaly patches. It affects millions of people globally. Dermatologists currently employ visual and haptic methods to determine a medical issue's severity. Intelligent medical imaging-based diagnosis systems are now a possibility because of the relatively recent development of deep learning technologies for medical image processing. These systems can help a human expert make better decisions about a patient's health. Convolutional neural networks, or CNNs, on the other hand, have achieved imaging performance levels comparable to, if not better than, those of humans. In the paper, a Dermnet dataset is used. Image preprocessing, fuzzy c-mean-based segmentation, MobileNet-based feature extraction, and a support vector machine (SVM) classification are used for skin disease classification. Dermnet's dataset was investigated for images of skin conditions using three classes Psoriasis, Dermatofibroma, and Melanoma are studied. The performance metrics such as accuracy, precision-recall, and f1-score are evaluated and compared for three classes of skin diseases. Despite working with a smaller dataset, MobileNet with Support Vector Machine outperforms ResNet in terms of accuracy (99.12%), precision (98.65%), and recall (99.66%).

Modern linguistic resources and IT applications for the Tatar language: Regional practices

The issue of preserving the language of an ethnic group as a language of communication, as well as a carrier of cultural codes, has now acquired particular urgency and relevance. How to preserve and develop a language in the conditions of globalization and widespread digitalization, in the conditions of coming, and in many ways already real, information chaos and in conditions when in the near future most of the known languages are threatened with complete extinction. Obviously, one of the reliable and promising solutions is embedding a language in the digital space as a language of accumulation, processing and transmission of information; a language of communication in the global Internet network. Currently, in the Republic of Tatarstan, a set of organizational and policy measures has been almost completely implemented and the necessary information and technological base has been created to ensure full functioning of the Tatar language in computer technologies, including business and management spheres, publishing, educational activities, linguistic research and development. Another effective and very promising activity is the research and use of the language as a cognitive-conceptual tool that can enrich the mental and spiritual space of civilization as a linguistic-semiotic resource that has the necessary potential for creating new knowledge processing technologies and an intelligent interface. This paper presents the experience of research and practical activities of the Institute of Applied Semiotics of the Academy of Sciences of the Republic of Tatarstan in one of the important areas of artificial intelligence called “Natural Language Processing”. Research and development are carried out in three theoretical and applied areas: 1) Tatar national localization of infocommunication technologies, 2) Development of software tools, systems and technologies for natural language processing and creation of linguistic resources, 3) Creation of new intelligent information processing technologies based on the research the cognitive potential of the Tatar language.

DMFF-Net: Double-stream multilevel feature fusion network for image forgery localization

With the rapid development of image processing technology, it has become increasingly easy to manipulate images, which poses a threat to the stability and security of people’s lives. Recent methods have proposed the fusion of RGB and noise features to uncover tampering traces. However, these approaches overlook the characteristics of features at different levels, leading to insufficient feature fusion. To address this problem, this paper proposes a double-stream multilevel feature fusion network (DMFF-Net). Unlike the traditional feature fusion approach, DMFF-Net adopts a graded feature fusion strategy. It classifies features into primary, intermediate, and advanced levels and introduces the Primary Feature Fusion Module (PFFM) and the Advanced Feature Fusion Module (AFFM) to achieve superior fusion results. Additionally, a multisupervision strategy is employed to decode the fused features into level-specific masks, including boundary, regular, and refined masks. The DMFF-Net is validated on publicly available datasets, including CASIA, Columbia, COVERAGE, and NIST16, as well as a real-life manipulated image dataset, IMD20, and achieves AUCs of 84.7%, 99.6%, 86.6%, 87.4% and 82.8%, respectively. Extensive experiments show that our DMFF-Net outperforms state-of-the-art methods in terms of image manipulation localization accuracy and exhibits improved robustness.

Research and development of gold ore processing technology

This paper presents the results of technological studies of two samples of gold-bearing ore from the gold-bearing deposit of Kazakhstan deposits 1 and 2. A comprehensive analysis of ore samples by X-ray fluorescence, X-ray phase, chemical, and mineralogical methods was carried out. The calculated initial gold content was determined, and X-ray fluorescence analysis showed that the main elements that make up the ore are oxygen up to 51% and silicon up to 33%. X-ray phase analysis showed the presence of more than 95% quartz and muscovite in the samples. The form of finding gold in the ore, according to the results of mineralogical analysis, is defined as free gold and gold in iron hydroxide. Silver is present in the studied samples in the form of various types of halides. An ore beneficiation scheme has been developed and presented, including gravity and flotation. Gravity enrichment was carried out in two stages, with the production of concentrate and tailings, with the maximum recovery of gold in concentrate up to 91%, flotation enrichment using butyl xanthate reagents and a blowing agent, was carried out in two stages with the production of main and control concentrates and final flotation tailings. The subsequent hydrometallurgical study of the ore was carried out to assess the effect of sodium cyanide on the extraction of gold, tests were performed on the leaching of the initial samples of the ore and the obtained flotation and gravity concentrates in the agitation mode, it was found that cyanide leaching is an effective method for processing the mineral raw materials of the gold-bearing deposit of Kazakhstan, and the obtained flotation concentrates, with the recovery of gold into solution under optimal conditions up to 98%. The results obtained make it possible to predict the effectiveness of the main technological stages in the ore processing scheme, technology optimization, and maximum gold recovery.

Innovative Environmentally Safe Processes for the Extraction of Rare and Rare-Earth Elements from Complex Ores of Perplexed Material Composition

Domestic and world tendencies of involvement in the processing of ores of rare metals (RMs) and rare-earth metals (REMs) are shown. It is shown that the main direction of innovative activity is the development and application of modern breakthrough technologies for complex processing of mineral raw materials with the production of high-quality products while minimizing environmental damage. The main deposits of rare and rare-earth metals are systematized from the standpoint of the content of the main components, concentrator minerals and the main enrichment methods. The main principal technological schemes of processing of some deposits of RMs and REMs in Russia (Lovozer, Tomtor, and Afrikand deposits) are given. Options for involving technogenic and off-balance raw materials in the processing in order to extract strategic metals are considered. It is substantiated that innovative environmentally friendly processes for the extraction of rare and rare-earth metals from complex ores of complex material composition are being actively developed in Russia at present.

Component composition of the processed forming mixture and mineralogical recommendations for its re-use

Modern industrial production is aimed at the development of waste-free technological processes, wider use in the production of waste and by-products. The largest amount of waste is generated from the activities of mining and metallurgical enterprises. One of the problems of foundry production is the disposal of multiton solid waste, about 90% of which is spent molding mixture. Part of the spent mixture is reused as recyclable, but the main mass of it is collected at municipal solid waste landfills. This work is devoted to the study of the component composition of foundry production waste – spent molding mixture with the aim of its reuse. According to the results of the research carried out by the authors, mineralogical recommendations regarding its reuse were provided. Involvement in the reuse of spent molding mixture will allow to free up part of the solid household waste landfills, reduce the negative man-made load on the environment, and additionally obtain conditioned restored molding sands.

An Enhanced Application Authentication and Key Management in 5G

AKMA (Application Authentication and Key Management) is a technology that 3GPP (3rd Generation Partnership Project) provides security capabilities to 5G (5th generation wireless systems) as a third party. At present, 3GPP has finalized the publication of AKMA specifications in Release 16 and is developing AKMA phase 2 in Release 18. At the current stage, it is recommended to conduct enhanced research on AKMA to solve some security problems of AKMA. This paper first briefly describes and analyzes the principles and technological development process of two mainstream application authentication technologies GBA (Generic Bootstrapping Architecture) and AKMA, and analyzes the advantages and limitations of these two technologies. Secondly, we also analyze the signaling loss caused by the AKMA process conducted independently by different application servers in the same trust domain, and the security risk caused by the long-term use of the same application key by AKMA users. Finally, this paper proposes solutions to AKMA performance and security problems from the perspective of security, universality, and performance impact.

Technologies for manufacturing of Bi-Te-based thermoelectric materials

Bismuth-Telluride(Bi-Te)-based alloys are well-known for their high thermoelectric conversion efficiency, especially near room temperature, making them ideal for applications in solid-state refrigeration and power generation from waste heat. However, to expand their applications further, it is essential to improve their performance and reliability. To achieve these goals, recent research has been dedicated to developing processing technologies that can concurrently enhance the thermoelectric and mechanical properties. This is particularly crucial because the manufacturing process for these materials is intricate and demands precise parameter control to ensure the production of high-quality products. This review offers a comprehensive overview of the process technology employed in manufacturing Bi-Te-based thermoelectric materials, alongside introducing a cutting-edge near net shape hot extrusion technique recently developed for their production.

Development and Application of 3D Modeling in Game

The development and progress of computer graphics and 3D modeling technology play an important role in the development of 3D game animation. Three-dimensional modeling technology combines artistic design and computer technology perfectly with a real sense of depth, so it has been widely used in the game industry. This paper introduces the development process of 3D modeling technology and the application of 3D modeling technology in games. At the same time, it gives suggestions on the problems existing in the application of 3D modeling technology in games, as well as researches and looks forward to the development trend of 3D modeling technology.

Characterization of planetary regolith simulants for the research and development of space resource technologies

Human planetary exploration and colonization efforts are reliant on the ability to safely interact with planetary surfaces and to leverage local regolith as a resource. The high-cost and risk-intensive nature of establishing planetary infrastructure and resource utilization facilities necessitates risk reduction through laboratory-based research and development of space resource acquisition, processing, and extraction technologies using appropriate, well-characterized, mineral-based regolith simulants. Such simulants enable the planetary exploration and resource utilization communities to test large-scale technologies and methodologies for a relatively low cost as an alternative to scarce and expensive returned samples. The fidelity of a regolith simulant for any application is, in part, determined by the mineralogical composition and particle size distribution. The importance of composition is well established for in situ resource utilization studies sensitive to geochemical properties but tends to be ignored in studies concerned with physical properties. Neglecting to consider mineralogy reduces the fidelity of a simulant since each mineral species has its own unique grain density, preferred grain geometry, and intergranular forces, all of which affect the physical properties of the simulant (e.g., shear strength, bearing strength, bulk density, thermal and electrical properties, magnetic properties). Traditionally, regolith simulants have been limited in quantity and availability; Exolith Lab remedies these problems by designing simulants in a constrained maximization approach to fidelity relative to cost, material availability, and safety. Exolith Lab simulants are designed to approximate the mineralogy and particle size ranges of the planetary regolith being simulated, with composition constrained by remote sensing observations and/or returned sample analyses. With facilities and equipment capable of high-volume simulant production, Exolith Lab offers standard simulants in bulk that are readily available for purchase and shipment. This work reviews the production methods, equipment, and materials used to create Exolith Lab simulants, provides compositional data, particle size data, and applications for each standard lunar, Martian, and asteroid simulant that Exolith Lab offers.

Impacts of Solid-State Fermented Barley with Fibrolytic Exogenous Enzymes on Feed Utilization, and Antioxidant Status of Broiler Chickens.

The present and future high demand of common cereals as corn and wheat encourage the development of feed processing technology that allows for the dietary inclusion of other cereals of low nutritional value in poultry feeding. Barley grains contain anti-nutritional factors that limit their dietary inclusion in the poultry industry. The treatment of barley with solid-state fermentation and exogenous enzymes (FBEs) provides a good alternative to common cereals. In this study, barley grains were subjected to solid-state microbial fermentation using Lactobacillus plantarum, Bacillus subtilis and exogenous fibrolytic enzymes. This study aimed to assess the impact of FBEs on growth, feed utilization efficiency, immune modulation, antioxidant status and the expression of intestinal barrier and nutrient transporter-related genes. One-day-old broiler chicks (Ross 308, n = 400) comprised four representative groups with ten replicates (10 chicks/replicate) and were fed corn-soybean meal basal diets with inclusions of FBEs at 0, 5, 10 and 15% for 38 days. Solid-state fermentation of barley grains with fibrolytic enzymes increased protein content, lowered crude fiber and reduced sugars compared to non-fermented barley gains. In consequence, the group fed FBEs10% had the superior feed utilization efficiency and body weight gain (increased by 4.7%) with higher levels of nutrient metabolizability, pancreatic digestive enzyme activities and low digesta viscosity. Notably, the group fed FBEs10% showed an increased villi height and a decreased crypt depth with a remarkable hyperactivity of duodenal glands. In addition, higher inclusion levels of FBEs boosted serum immune-related parameters and intestinal and breast muscle antioxidants status. Intestinal nutrient transporters encoding genes (GLUT-1, CAAT-1, LAT1 and PepT-1) and intestinal barriers encoding genes (MUC-2, JAM-2, occludin, claudins-1 and β-defensin 1) were upregulated with higher dietary FBEs levels. In conclusion, feeding on FBEs10% positively enhanced broiler chickens' performance, feed efficiency and antioxidant status, and boosted intestinal barrier nutrient transporters encoding genes.

Направления рационального и комплексного использования минеральных ресурсов недр при открытых горных работах

The aim of the work is to study the methods of rational subsurface use in open-pit mining. The article outlines the main directions of rational and integrated use of mineral resources of the subsurface and the ways of their implementation in the open method of field development. The problems that prevent further expedient waste processing are identified. The achieved experience and prospects of complex development of deposits of ferrous and non-ferrous metals, mining and chemical raw materials and coal are analyzed. The problem of complex utilization of coals in industry in order to extract rare elements (in particular germanium and scandium) from the mineral component is considered. Special attention is paid to the specifics of transition to low-waste, resource-saving technologies of mining and enrichment production, to their efficiency and environmental safety at many mining enterprises. The directions of waste disposal of mining and processing industries and ways of their use for the internal needs of the enterprise, namely the use of overburden rocks of the Lebedinsky mining and processing plant, are investigated. Recommendations for the involvement in the development of man-made deposits and substandard mineral raw materials using physico-chemical methods for extracting useful components are given. It is noted that a comprehensive system of rational development of the country’s mineral resource base has not been built to date. This system is of great importance for the preservation of non-renewable natural resources of the subsoil and the successful implementation of the tasks of the National Project “Ecology”. A special role should be given to scientific research on the development of eco-innovative technologies for mining and processing of minerals.

The application of SLAM technology in indoor navigation to complex indoor environments

This paper reviews the application progress of Simultaneous localization and mapping (SLAM) in complex indoor environments. SLAM is a technology used to manufacture mobile robots and autonomous vehicle. It can achieve autonomous localization and mapping in unknown environments. In dealing with complex indoor environments, SLAM technology faces many challenges, such as missing local perspectives, detecting moving objects, constructing dense maps, and real-time requirements in large-scale environments. However, with the development of technology, more and more SLAM technologies are being applied to complex indoor environments, among which the fusion of multimodal vision and deep learning technology, enhanced camera positioning technology, and navigation algorithms based on intelligent platforms are currently relatively advanced technologies. This article will briefly introduce the main development process of SLAM technology in dealing with complex indoor environments and the application of deep learning technology. By utilizing this technology, map features can be extracted more accurately, objects can be recognized, and obstacle avoidance can be achieved. This provides a good development direction for SLAM technology.

Current development status and application analysis of microelectronics technology

With the rapid development of microelectronic technology in the 21st century, microelectronic technology has been widely used in various fields, which has promoted various fields and improved the level of industrialization in the world. But there are still many problems, so this paper will introduce the application of microelectronics technology, let readers understand that microelectronics technology has a strong research prospect. The research methods of this paper are as follows. Firstly, the importance and significance of microelectronic technology are described, and the development process of microelectronic technology is introduced. Then its applications in microelectronics automation and microelectronics packaging are introduced. It makes readers understand that there are many application scenarios of microelectronic technology and provides scholars with different research directions. This article will first describe the history of the development of microelectronic technology, and then explain its various applications. The future research directions of microelectronic technology in several industries are also highlighted.