Development Of Processing Technology Research Articles

Effect of injection compound rolling process and curdlan gel on water retention of sauced beef

Research background and significance: Under the current development trend in the field of global food science and technology, consumers' requirements for food safety, nutritional value and sensory quality are increasing, prompting the innovation of food processing and preservation technology to become the core of the industry development. In the production of traditional food spiced beef, how to ensure the yield and quality of spiced beef is the focus of the spiced beef market. By adding edible glue can gain weight, thereby improving the yield, but previous studies have shown that carrageenan, seaweed extract and so on seriously affect the sensory quality of marinated beef, especially causing its juice oozing, colloidal attachments oozing and so on. Research content: Through the systematic study of the application of curdlan gel in the processing of brine injection spiced beef, the specific effects of curdlan gel on the water retention and sensory quality of spiced beef were discussed in this study. (1) Sensory optimization injection rolling composite curing process. The experiment was carried out with beef tendinous meat and a series of auxiliary materials, using fine processes and methods, including saline injection, rolling salting, cooking treatment, etc., and then conducting sensory evaluation. (2) Compare the quality difference of curdlan gel 1 and 2. Determination of gel strength and optimization of water retention of stewed beef were carried out. Single factor ANOVA test was used to determine the optimal dosage of curdlan gel. The results showed that the water retention of beef with brine injection could be enhanced significantly when the dosage was 2%, respectively. Under the optimal process conditions, the sensory score of brined beef was 85.4 points. Through this study, important scientific and technological findings were obtained, which did not mean that the higher the concentration of curdlan gel, the better the water retention, on the contrary, the higher the concentration of its water retention would be affected but would decrease. This research not only expands the application range of curdlan gel in the food industry, but also provides new technical solutions and theoretical support for the innovation and development of meat processing technology, and meets the needs of consumers for high-quality meat products.

Laser-Induced Ultrafast Spin Injection in All-Semiconductor Magnetic CrI3/WSe2 Heterobilayer.

Spin injection stands out as a crucial method employed for initializing, manipulating, and measuring the spin states of electrons, which are fundamental to the creation of qubits in quantum computing. However, ensuring efficient spin injection while maintaining compatibility with standard semiconductor processing techniques is a significant challenge. Herein, we demonstrate the capability of inducing an ultrafast spin injection into a WSe2 layer from a magnetic CrI3 layer on a femtosecond time scale, achieved through real-time time-dependent density functional theory calculations upon a laser pulse. Following the peak of the magnetic moment in the CrI3 sublayer, the magnetic moment of the WSe2 layer reaches a maximum of 0.89 μB (per unit cell containing 4 WSe2 and 1 CrI3 units). During the spin dynamics, spin-polarized excited electrons transfer from the WSe2 layer to the CrI3 layer via type-II band alignment. The large spin splitting in conduction bands and the difference in the number of spin-polarized local unoccupied states available in the CrI3 layer lead to a net spin in the WSe2 layer. Furthermore, we confirmed that the number of available states, the spin-flip process, and the laser pulse parameters play important roles during the spin injection process. This work highlights the dynamic and rapid nature of spin manipulation in layered all-semiconductor systems, offering significant implications for the development and enhancement of quantum information processing technologies.

Spatial transcriptomics techniques and its applications in plant research

The heterogeneity of gene expression in plant cells plays a crucial role in determining the functional differences among tissues. Recent advancements in spatial transcriptome (ST) technology have significantly contributed to the study of specific biological questions in plants. This technology has been successfully applied to examine cell development, identification, and stress resistance. This review aims to explore the application of ST technology in plants by reviewing three aspects: the development of ST technology, its current application in plants, and future research directions. The review provides a systematic description of the development process of ST technology, with a focus on analyzing its progress in studying plant cell growth and differentiation, plant cell identification, and stress resistance. In addition, the challenges faced by ST technology in plant applications are summarized, along with proposed future directions for plant research, including the advantages of combining other omics technologies with ST technology to tackle scientific challenges in the field of plants.

КОМП’ЮТЕРНИЙ МОДУЛЬ ПРОГРАМИ ДЛЯ ВИЗНАЧЕННЯ ОПТИМАЛЬНОЇ ФОРМИ ЗАПРАВКИ НИТКИ НА ТЕХНОЛОГІЧНОМУ ОБЛАДНАННІ

The results of determining the optimal form of thread filling on the technological equipment of the light and textile industry using the computer module of the program for determining the tension of technological processes are given. The computer module of the program for determining the intensity of technological processes, using the recursion algorithm, allows you to determine the optimal form of filling the thread for obstacles in the form of a vertical straight line, a circle and a rectangle. These geometric images reflect real guides and working bodies of technological equipment. The development of new technological processes in the light and textile industries and the improvement of existing ones is based on the optimization of thread tension in the working area. An increase in the amount of tension leads to thread breaks, and a decrease in its value leads to a violation of technological processes, a deterioration in the quality of manufactured products and, as a result, also leads to breaks in raw materials. Thus, the optimization of the thread tension in the working area allows you to maximally exclude thread breaks, increase the productivity of the technological equipment and the quality of the manufactured products. When processing raw materials on the technological equipment of the light and textile industry, the thread tension gradually increases from the exit zone from the packaging to the working zone. The increase in tension is due to the contact of the thread with the guiding and working bodies of the technological equipment of the light and textile industry. Due to the frictional forces in the contact zone, the thread tension increases after the guiding and working bodies of the technological equipment. The magnitude of the friction force is affected by the angle of coverage of the thread of the guide. The form of filling the thread on the technological equipment is a broken line. The guiding and working bodies of the technological equipment are located at the breaking points. Optimizing the filling form consists in minimizing the total angle of coverage of the guide thread. Graph theory and specialized software must be used to solve the complex task of optimizing the thread filling form on technological equipment. The magnitude of the frictional force in the zone of contact with the guiding and working bodies of the technological equipment of the light and textile industry depends on the tension of the thread in front of the guide, the radius of curvature of the guide surface, the angle of coverage by the thread of the guide, guide material and thread, speed of thread movement.

Development of process technology for preparation of beverages from watermelon with pectin as stabilizer

Development of process technology for preparation of beverages from watermelon with pectin as stabilizer

REASONS AND REGULARITIES OF THE INFLUENCE OF MAGNETIC FIELDS ON THE MECHANICAL PROPERTIES AND STRUCTURE OF DEFORMABLE METALS

Background. The strength of metals greatly limits the possibility of obtaining products by plastic deformation. The electromagnetic nature of the processes of structure formation and plastic deformation provided the basis for the application of additional influence of the magnetic field. A fairly large volume of research material has been accumulated on the topic of additional influence of the magnetic field on ferro-, dia- and paramagnetic metals. The researches of recent years have an applied nature of studying the magnetoplasticity of technical alloys. Their generalization will make it possible to move from laboratory research to the development of equipment and technologies for combined pressure processing of metal products in a weak magnetic field. Objective. Generalization and analysis of the results of laboratory and theoretical studies of the additional application of the magnetic field in the processes of mechanical testing of metals and alloys.Methods. Literary review of materials of articles, monographs, dissertations. Results. Reasonable use of a magnetic field for plastic deformation of metals. The explanation of the mechanism of the influence of the magnetic field on the structural elements of metals based on the effect of magnetoplasticity has been made. The description of changes in the mechanical properties of metals and alloys under the additional influence of a magnetic field is given. Conclusions. The phenomenon of magnetoplasticity has been studied for a wide range of materials such as pure metals and their alloys, including industrial steels and alloys. Various types of positive effects of a magnetic field on the mechanical properties of metals have been established: a decrease in the yield strength and deformation resistance, an increase in strain, relaxation of internal stresses, and a decrease in dislocation density. There is also a reverse, negative effect of the influence of a magnetic field: increased rate of hardening, embrittlement, increased creep of metals. What will be the effect of a magnetic field on a specific metal cannot be guaranteed with high accuracy.

Deep Learning-Based Forest Fire Risk Research on Monitoring and Early Warning Algorithms

With the development of image processing technology and video analysis technology, forest fire monitoring technology based on video recognition is more and more important in the field of forest fire prevention and control. The objects currently applied to forest fire video image monitoring system monitoring are mainly flames and smoke. This paper proposes a forest fire risk monitoring and early warning algorithm, which integrates a deep learning model, infrared monitoring and early warning, and forest fire weather index. The algorithm first obtains the current visible image and infrared image of the same forest area, utilizing a smoke detection model based on deep learning to detect smoke in the visible image, and obtains the confidence level of the occurrence of fire in said visible image. Then, it determines whether the local temperature value of said infrared image exceeds a preset warning value, and obtains a judgment result based on the infrared image. It calculates again a current FWI based on environmental data, and determines a current fire danger level based on the current FWI. Finally, it determines whether or not to carry out a fire warning based on said fire danger level, said confidence level of the occurrence of fire in said visible image, and said judgment result based on the infrared image. The experimental results show that the accuracy of the algorithm in this paper reaches 94.12%, precision is 96.1%, recall is 93.67, and F1-score is 94.87. The algorithm in this paper can improve the accuracy of smoke identification at the early stage of forest fire danger occurrence, especially by excluding the interference caused by clouds, fog, dust, and so on, thus improving the fire danger warning accuracy.

Didactic requirements for fostering the growth of future translators� technology proficiency within the framework of their localization-focused training

Relevance. The transition of society�s spheres of activity to new technological systems implies the need to introduce changes in educational standards, as well as to change approaches to the professional education of future industry specialists, including in the training of professional translators. Purpose. The study aims to identify the pedagogical conditions necessary for the development of future translators� technological competence, especially in the context of their localisation-based training. Methodology. The study applied systemic-structural and interdisciplinary approaches, as well as dialectical, historical, and legal comparative, logical and semantic and other methods. Results. The study found that in the context of the current realities, not only the classical professional knowledge of future translators needs to change, but also the adaptation of pedagogical programmes to the rapid development of technological processes. The active expansion of contacts between different countries of the world and the increasing importance of developing information communication between representatives of different countries make the latest technologies particularly valuable in areas designed to address global and international issues. One of these areas of professional activity is translation, which includes not only translation technologies but also translation education in the context of training professional translators. Conclusions. The complexity of the translation process due to its technology requires the development of the technological competence of professional translators. The practical significance of this study lies in the possibility of implementing the results achieved in the process of improving the content of existing or opening new educational programmes for future professional translators to adapt them to the requirements of the modern environment. Keywords: professional education; localisation; information technology; automated systems; strategy; post-editing

The improved strategy of BOA algorithm and its application in multi-threshold image segmentation

In response to the low efficiency and poor quality of current seed optimization algorithms for multi-threshold image segmentation, this paper proposes the utilization of the normal distribution in the cluster distribution mathematical model, the Levy flight mechanism, and the differential evolution algorithm to address the deficiencies of the seed optimization algorithm. The main innovation lies in applying the BBO algorithm to image multi threshold segmentation, providing a new perspective and method for image segmentation tasks. The second significant progress is the combination of Levy flight dynamics and differential evolution algorithm (DEA) to improve the BBO algorithm, thereby enhancing its performance and image segmentation quality. Therefore, a multi-threshold image segmentation model based on the optimized seed optimization algorithm is developed. The experimental results showed that on the function f1, the iteration of the improved seed optimization algorithm was 53, the Generational Distance value was 0.0020, the Inverted Generational Distance value was 0.098, and the Spacing value was 0.051. Compared with the other two algorithms, the improved seed optimization algorithm has better image segmentation performance and clearer image segmentation details. In summary, compared with existing multi-threshold image segmentation methods, the proposed multi-threshold image segmentation model based on the improved seed optimization algorithm has a better image segmentation effect and higher efficiency, can significantly improve the quality of image segmentation, has positive significance for the development of image processing technology, and also provides references for the improvement and application of optimization algorithms.

The prospect exploration of artificial intelligence technology and its application

With the rapid development of science and technology, artificial intelligence technology has become one of the most popular research fields in today's society. From intelligent voice assistants to self-driving cars, to medical diagnostics and financial risk control, AI technology has shown huge potential and value in all fields. This paper deeply explores the current situation, development trend and its application prospect of artificial intelligence technology in various industries. This paper briefly introduces the development process of artificial intelligence technology, including its origin, development status and key technologies. Then, it focuses on the application cases of AI technology in healthcare, finance, education, industry and other fields, and evaluates its impact and potential value. It discusses the challenges of artificial intelligence technology, such as data security and privacy protection, algorithm fairness and moral considerations. In view of these problems, the corresponding solution strategies and development suggestions are put forward. The future development trend of artificial intelligence technology is discussed, including the research and application of cutting-edge technologies such as deep learning, natural language processing and emotional computing. The conclusion pointed out that artificial intelligence technology will continue to change human life in the future and bring more innovation and breakthrough to various industries.

Optimization and Performance Evaluation of Deep Learning Algorithm in Medical Image Processing

In this paper, the optimization and performance evaluation of deep learning algorithm in medical image processing are studied. Firstly, the paper introduces the importance and challenges of medical image processing, and expounds the application prospect of deep learning in this field. Subsequently, this paper discusses the optimization methods of deep learning algorithm in detail, including model structure design, data preprocessing, super parameter adjustment and so on. In terms of performance evaluation, this study selected classic models such as U-Net, DeepLab and DenseNet, and compared them with ROC curve and AUC value to evaluate their predictive ability in medical image classification. The results show that the DenseNet model shows high performance in prediction accuracy, while the performance of U-Net and DeepLab models is slightly average. Finally, the advantages and disadvantages of each model are analyzed, and the future research direction is prospected. This study is of great significance to promote the development and application of medical image processing technology, and provides important theoretical and technical support for medical diagnosis and treatment.

Preface: 3rd International Conference on Software, Data Processing and Information Technology (SDPIT 2024)

The 2024 3rd International Conference on Software, Data Processing and Information Technology (SDPIT 2024) is a leading conference held at Washington DC, USA during February 17-18, 2024. It encourages communication and collaboration, hoping to provide an international platform for its participants to present, share, and learn the latest advance and development of software engineering, data processing, cloud computation, mathematical modeling and information technology. Academics, researchers, and students from across the world are all welcomed to exchange findings and ideas, to draw further inspirations in these research fields. It's a great opportunity to deepen your understanding in the related topics. Everyone interested in these fields were welcomed to join the conference and to give comments and raise questions to the speeches and presentations. We are hoping we could see each other again next year. Each submission to SDPIT 2024 was reviewed by at least two program committee members. We would like to thank the program committee members and external reviewers for their hard work in reviewing and selecting papers. Hopefully, all participants and other interested readers can benefit scientifically from the proceedings and find it rewarding in the process. Chairman of Conference Committee Washington DC, USA

Predicting attitudes toward ambiguity using natural language processing on free descriptions for open-ended question measurements

Individual traits and reactions to ambiguity differ and are conceptualized in terms of an individual’s attitudes toward ambiguity or ambiguity tolerance. The development of natural language processing technology has made it possible to measure mental states and reactions through open-ended questions, rather than predefined numerical rating scales, which have traditionally been the dominant method in psychological research. This study presented three ambiguity-related situations and responses collected online from 591 participants in an open-ended format. After the analysis with bidirectional encoder representations from transformers, correlations were calculated using scores from the numerical evaluation by conventional questionnaire, and a significant moderate positive correlation was found. Therefore, this study found that attitudes toward ambiguity can be measured using an open-ended response method of reporting everyday life states. It is a novel methodology that can be expanded to other scales in psychology and can potentially be used in educational and clinical situations where participants can be asked to respond with minimal burden.

АТОМНО-ДИСЛОКАЦИОННАЯ МОДЕЛЬ УДАЛЕНИЯ ПОВЕРХНОСТНЫХ СЛОЕВ СТРУЙНЫМ ЭЛЕКТРОЛИТНО-ПЛАЗМЕННЫМ ПОЛИРОВАНИЕМ

This work is devoted to the development of a model for the removal of surface layers of anode material due to a jet electrolyte-plasma discharge formed by a hollow cathode. The results of studies of the main types of discharges that occur during the formation of jet electrolyte-plasma processing are presented. The influence of each type of discharge on the morphology of the surface layer of the anode-product was studied. The power, lifetime and energy of single discharges are estimated, and their influence on the surface is assessed. A theory has been proposed for the removal of surface layers by single discharges at the atomic dislocation level. Theoretical calculations are confirmed by the results of experimental studies and multiphysics simulations carried out in the COMSOL Multiphysics program. Practical research results confirm the possibility of reducing the roughness parameter Ra during jet electrolyte plasma by more than 20 times, while obtaining an extremely low parameter Ra of 0.019 μm. The area of application of the results of these studies may be the development of technological processes for dimensional and finishing processing of curved surfaces, such as blisks, turbine blades, and various products for household and medical purposes.

Method for determining the number of defective products in a sample based on one measurement result

The most pressing problems in terms of production are increasing labor productivity and the quality of its results. One of the main ways to increase labor productivity is the development of new progressive technological processes. There are methods for controlling batches of products that can reduce the time of its control and increase labor productivity, which include methods of statistical quality control based on an alternative criterion. However, a sample from a batch of products must be fully controlled. When inspecting with one inspection tool, the sample inspection time is no less than the sum of the inspection times of all sample items. The purpose of this work is to develop a method for determining the number of defective products in a sample with one inspection tool, allowing to reduce the sample inspection time to the minimum possible. A method is proposed for determining the number of defective products of a certain class in a sample with one inspection tool using samples, which allows to signifi cantly reduce the sample inspection time. The samples are connected in parallel to the controlled products and are connected in series. All products in the sample with samples are controlled simultaneously, the total value of the controlled parameter is determined for them, and the number of defective products in the sample is determined by the formula. The effectiveness of the method is shown using the example of monitoring electromagnetic relays. The method makes it possible to reduce the sample inspection time to the minimum possible value, equal to the inspection time of one product.

INTELLIGENT DATA ANALYSIS ON AN ANALYTICAL PLATFORM

The article discusses methods for processing unstructured data using an analytical platform. The authors analyze existing methods and technologies used to implement data processing and propose new approaches to solving this problem. The possibilities of using analytical platforms to solve the problem of processing source data are considered. The purpose of the article is to explore the possibilities of data import, partial preprocessing, missing data recovery, anomaly removal, spectral processing and noise removal. The authors explored how analytics platforms can function without a data warehouse, obtaining information from any other sources, but the most optimal way is to use them together, and how big data and unstructured data can be processed using an analytics platform. The authors solved a specific problem related to processing problems and proposed ways to solve them using an analytical platform. Particular attention is paid to a complete set of mechanisms that allows you to obtain information from any data source, carry out the entire processing cycle and display the results. Overall, the paper represents an important contribution to the development of raw data processing technologies. The authors plan to continue research in the field of processing big unstructured data.

Разработка гибридного ветро-солнечного энергокомплекса

The relevance of the problem of energy and environmental security is increasing every year. Therefore, in the energy sector, the improvement of renewable energy sources is extremely important. The comprehensive development of optimal technological processes that are cost-effective and allow increasing the efficiency of wind-solar installations is an important problem today. The article discusses issues related to the use of renewable energy sources. An energy system has been created that combines wind and solar energy. Its design includes a horizontal axis wind turbine and solar panels. The blades of a wind turbine are made of polyvinyl chloride. The project presents modeling of two new energy supply systems using renewable energy sources: solar and wind. The energy produced by both sources was combined using a charge controller and then transferred to the inverter. The resulting energy was used to provide electricity to residential premises. The prototype demonstrates an evaluation of the effectiveness of a combined solar and wind system to provide essential home comfort needs such as lighting, fans, etc. In addition, the wind turbine is able to operate at lower wind speeds, which increases the overall efficiency of the system. This prototype was tested in combination with photovoltaic panels to verify the power output and overall efficiency of the integrated system. The comparison between the proposed and current systems confirmed many advantages of the proposed configuration. The efficiency of the wind turbine has been improved during its manufacturing process, especially when used in conjunction with photovoltaic panels, significantly increasing overall productivity

Effect Analysis of Fourier Transform and Neural Network on Image Noise Reduction

During the acquisition, transmission, and processing of digital images, noise often appears in the pictures, seriously affecting the quality of the images and the accuracy of subsequent analysis. To solve this problem, many scholars have conducted in-depth research on image denoising, aiming to find denoising methods suitable for different scenarios. This study aims to compare the effects of Fourier transform and neural network methods in eliminating stripes in pictures. The discrete Fourier transform denoising method performs best in sharpness and has a fast processing time, but its image restoration is poor. Although the artificial neural network method has a long processing time and depends on the training set, it has good noise reduction effect. The Photoshop (beta) method is relatively simple and easy to use, with good overall effect. It is hoped that through further research, a better understanding of the role of Fourier transform and neural network methods in image noise elimination can be achieved, providing more references for the development of image processing technology. This article introduces in detail the Fourier transform method and neural network method, analyzes their advantages and disadvantages and scope of application. These results shed light on guiding further exploration of noise reduction.

STUDYING THE APPROACHES OF EUROPEAN COUNTRIES IN FORESIGHT STUDIES OF THE DEVELOPMENT OF SCIENCE AND GREEN TECHNOLOGIES FOR ADOPTING THEIR EXPERIENCE IN THE CONTEXT OF KAZAKHSTAN

This paper reviews the application of foresight methods in the field of science, especially in the development of green technologies in various European countries, with the aim of identifying the most suitable approaches for future use in Kazakhstan. The analysis shows that green technology forecasting promises to be an effective tool for managing sustainable development. Methods for forecasting green technologies are focused on a systematic approach and integrated solutions, taking into account the environment and social aspects. It is also important to consider both global and local environmental issues to gain a full understanding of future development trends. The article provides a comparison of the Dutch and Danish approaches. Green technology foresight research can play an important role at the national level, especially in integrating sustainability considerations into technology development and innovation processes. They also contribute to the development of more effective and sustainable development strategies for companies and government in Kazakhstan. These studies contribute to increasing environmental awareness and awareness in society regarding the importance of sustainable development. Technology forecasting values the use of Delphi surveys to provide a better understanding of possible future trends. The knowledge gained is the basis for developing strategic plans in the field of green technologies and ensuring sustainable development of the energy sector.

Climate services for agriculture: Steering towards inclusive innovation in Australian climate services design and delivery

CONTEXTClimate services are integral to climate change adaptation in agriculture. Inclusive innovation prioritises inclusion of marginalised actors, grassroots knowledge and accessibility of use. Yet many innovation processes are multi-stakeholder, complex and may not prioritise inclusion from the outset. In these circumstances, researchers and designers may seek to influence existing projects towards greater inclusivity. OBJECTIVESThis paper explores efforts to increase the inclusivity of existing innovation processes, focusing on the design of My Climate View, an online Australian climate services platform for agriculture. Findings relate to contemporary issues in inclusive innovation literature, including: (1) Who should be included in innovation processes (within given resourcing)?; (2) How requirements for inclusion or exclusion can emerge through the design and use of a technology; and (3) The influence of program level structures upon inclusivity and design. METHODSOur approach is informed by Responsible Innovation and Inclusive Innovation theory and enacted through user-centred design. Findings are synthesised from analysis of 60 semi-structured interviews with farmers, advisors and extension officers. We additionally draw on observations as researchers in the multi-actor My Climate View development team, where extensive engagement separate to research activities has included agricultural and Indigenous stakeholders. RESULTS AND CONCLUSIONEngaging with a broad sample of potential target users enabled diverse and sometimes unexpected use cases. Customisation of interface parameters allowed the incorporation of tacit knowledge and positively affected the inclusivity of My Climate View, extending the value of the platform to growers of niche commodities outside of the original scope. Inclusivity in innovation can be impacted by diverse factors, including design team decisions, structural factors, budget and external factors. Requirements for inclusion and exclusion can emerge and evolve throughout a design process, supporting Responsible Innovation's framing of inclusivity alongside principles of reflexivity and responsiveness. SIGNIFICANCEThe findings enrich the evidence base for climate services and broader agricultural technology development processes by providing insights for those seeking greater impact by practicing inclusivity in innovation. We provide four implications for increasing inclusivity in the design of climate services: (1) Maximising customisation and avoiding prescriptive interpretation enables greater flexibility of use; (2) Sampling broadly within target users to uncover unanticipated values and opportunities for inclusion and exclusion; (3) It is important to embed efforts towards inclusion alongside processes of reflexivity; and (4) Responsible and inclusive approaches to climate services design are valuable even if brought in once development has commenced.