Development Of Processing Technology Research Articles

Classical Batch Distillation of Anaerobic Digestate to Isolate Ammonium Bicarbonate: Membrane Not Necessary!

The excessive mineralization of organic molecules during anaerobic fermentation increases the availability of nitrogen and carbon. For this reason, the development of downstream processing technologies is required to better manage ammonia and carbon dioxide emissions during the storage and land application of the resulting soil organic amendment. The present work investigated classical distillation as a technology for valorizing ammoniacal nitrogen (NH4+-N) in anaerobic digestate. The results implied that the direct isolation of ammonium bicarbonate (NH4HCO3) was possible when applying the reactive distillation to the food waste digestate (FWD) with a high content of NH4+-N, while the addition of antifoam to the agrowaste digestate (AWD) was necessary to be able to produce an aqueous solution of NH4HCO3 as the distillate. The reason was that the extraction of NH4HCO3 from the AWD required a higher temperature (>95 °C) and duration (i.e., steady state in batch operation) than the recovery of the inorganic fertilizer from the FWD. The titration method, when applied to the depleted digestate, offered the quickest way of monitoring the reactive distillation because the buffer capacity of the distillate was much higher. The isolation of NH4HCO3 from the FWD was attained in a transient mode at a temperature below 90 °C (i.e., while heating up to reach the desired distillation temperature or cooling down once the batch distillation was finished). For the operating conditions to be regarded as techno-economically feasible, they should be attained in the anaerobic digestion plant by integrating the heat harvested from the engines, which convert the biogas into electricity.

Development of a Low-carbon Sintering Process Technology and Its Application to a Pilot-scale Sintering Testing

Development of a Low-carbon Sintering Process Technology and Its Application to a Pilot-scale Sintering Testing

Application of CNN Classic Model in Modern Image Processing

As a deep learning model, convolutional neural network (CNN) has been widely used in the field of modern image processing and has shown excellent performance. From LeNet to AlexNet, to classic models such as VGGNet and ResNet, CNN has achieved remarkable success in tasks such as image classification, object detection and segmentation through multi-level feature extraction and automatic learning capabilities. This paper first explores the basic structure and working principle of CNN, analyzes the advantages and limitations of classic models, and reviews its specific applications in image processing. By introducing the optimization strategies of various models, it further explores the improvement path of CNN in the field of image processing, including model compression, lightweight design and the introduction of new network structures. In short, the continuous optimization of CNN has enabled it to show powerful performance in multiple complex tasks, promoted the rapid development of image processing technology, and provided strong support for applications in more fields.

Complex systems perspective in assessing risks in artificial intelligence.

In this article, we identify challenges in the complex interaction between artificial intelligence (AI) systems and society. We argue that AI systems need to be studied in their socio-political context to be able to better appreciate a diverse set of potential outcomes that emerge from long-term feedback between technological development, inequalities and collective decision-making processes. This means that assessing the risks from the deployment of any specific technology presents unique challenges. We propose that risk assessments concerning AI systems should incorporate a complex systems perspective, with adequate models that can represent short- and long-term effects and feedback, along with an emphasis on increasing public engagement and participation in the process.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Film image processing and production based on high-performance calculation

In film and television production, efficient and precise image processing is vital for achieving realistic visual effects. Therefore, exploring and applying advanced image processing technologies has become an essential method for elevating the production quality of film and television projects. This work investigates the application of artificial intelligence (AI) technology in the processing and production of animated images in film and television scenarios. By comparing the performance of standard Generative Adversarial Network (GAN), DenseNet, and CycleGAN models under different noise conditions, it is found that CycleGAN performs the best in image denoising and detail restoration. Experimental results demonstrate that CycleGAN achieves a Peak Signal-to-noise Ratio (PSNR) of 30.1dB and a Structural Similarity Index Measure (SSIM) of 0.88 under Gaussian noise conditions. Moreover, CycleGAN achieves a PSNR of 29.5dB and an SSIM of 0.85 under salt-and-pepper noise conditions. It outperforms the other models in both conditions. Additionally, CycleGAN’s mean absolute error is significantly lower than that of the other models. This work demonstrates that CycleGAN can more effectively handle complex noise and generate high-quality images under unsupervised learning conditions. These findings provide new directions for future image processing research and offer important references for model selection in practical applications. This work not only offers new perspectives on the development of animation image processing technology but also establishes a theoretical foundation for applying advanced AI techniques in film and television production. Through comparative analysis of various deep learning models, this work highlights the superior performance of CycleGAN under complex noise conditions. This advancement not only drives progress in image processing technology but also provides effective solutions for efficient production and quality enhancement of future film and television works.

Research on the Progress of Modulation Technology and Data Transmission Technology in Underwater Wireless Optical Communication

Recently, as an efficient data transmission method, underwater wireless optical communication has become one of the key research topics in the fields of military communication and underwater surveillance. Modulation technology and technology in the transmission process play a key role in the UWOC system, which directly affects the performance, accuracy and safety of the system. The advanced modulation techniques from Intensity Modulation (IM), Pulse Modulation, Quadrature Amplitude Modulation (QAM), and Quadrature Phase Shift Keying (QPSK) to the combination of multiple modulation techniques, as well as the development process of modulation technology in optical encryption, are summarized in this paper. In terms of data transmission technology, the technological progress process from simplex to full-duplex communication is summarized. Finally, a reference solution is proposed to solve the challenges in realizing the underwater communication goals of long-distance, high-speed, low-bit error rate, and large-capacity underwater communication at the same time, and future development is prospected.

Calibration of discrete meta-parameters of bamboo flour based on magnitude analysis and BP neural network.

In the research and development of technology and equipment for bamboo products deep processing, such as filling, drying, and medicinal use of bamboo flour (BF), the poor compaction and fluidity of BF materials entails the need for accurate discrete element model (DEM) and BF parameters to provide a reference for the simulation of BF processing operationsand the development of related equipment. The average particle size of the 5 types of BFs ranges from 0.136 mm to 0.293 mm, and the small particle size of BF particles causes to the number of BF particles in bamboo processing equipment to reach tens of millions or even billions. When conventional methods are used for simulation, ordinary computers cannot provide the required computing power. To address the aforementioned challenges, this paper proposes a calibration method for the discrete element contact parameters of BFs based on dimensional analysis and a back propagation (BP) neural network. Using particle scaling theory and dimensional analysis methods, the average particle size of the BF was increased to 1 mm, and the main discrete element contact parameters of the five types of BF to be tested were used as input layers. The injection method and sidewall collapse method were used to obtain the angle of repose (AR) as the output layer. Fifty groups were randomly selected using MATLAB for EDEM simulation, and the simulation results were trained using the BP neural network algorithm; an ideal neural network model was obtained, the discrete element parameters of different BFs were predicted, and physical experiments were performed to verify two types of AR and mold hole compression under calibrated parameters. The relative error between the simulated AR obtained through calibration parameters and the physical experimental values is less than 2.3%. Through BF parameter validity verification, the simulated maximum compression displacement and compression ratio after stabilization were 34.81 mm and 0.477, which were close to the actual experimental results of 34.77 mm and 0.461, respectively, verifying the accuracy of the neural network prediction model. The research results provide a reference for the simulation of BF processing operations and the development of related equipment.

Different drying methods' effects on the nutritional components and flavor of fruits

With the continuous development of food processing technologies, drying techniques have become increasingly important in fruit processing. Different drying methods have significant impacts on the nutritional components and flavor of fruits, directly affecting the nutritional value and market competitiveness of the products. This paper reviews the principles, technical characteristics, and effects of four main drying technologies—hot air drying, freeze drying, vacuum drying, and microwave drying—on the nutritional components and flavor of fruits. By comparing the retention effects of these drying methods on vitamins, minerals, dietary fibers, and antioxidants, the paper explores future research directions and suggests technical optimization strategies. The study indicates that different drying technologies have varying advantages and disadvantages in terms of nutrient retention, flavor preservation, and drying efficiency. Strategies such as multi-factor optimization, technological combinations, and exploration of new drying technologies are proposed to provide valuable references and guidance for the fruit processing industry.

Current Status of Green Hydrogen Production Technology: A Review

As a clean energy source, hydrogen not only helps to reduce the use of fossil fuels but also promotes the transformation of energy structure and sustainable development. This paper firstly introduces the development status of green hydrogen at home and abroad and then focuses on several advanced green hydrogen production technologies. Then, the advantages and shortcomings of different green hydrogen production technologies are compared. Among them, the future source of hydrogen tends to be electrolysis water hydrogen production. Finally, the challenges and application prospects of the development process of green hydrogen technology are discussed, and green hydrogen is expected to become an important part of realizing sustainable global energy development.

Naked-eye light field display technology based on mini/micro light emitting diode panels: a systematic review and meta-analysis

The light field display technology based on panel light modulation has obvious industrial advantages. However, light field displays still causes discomfort for users in practical applications, due to issues such as angle of view, number of viewpoints, and crosstalk, etc. As a new type of high performance 2D display technology, mini/micro light emitting diode (MLED) has the potential to provide higher quality 3D display effects, but it may also bring new technological challenges. This paper provides a detailed investigation of technical principles and the latest research progress in light field display technology based on panel light modulation, and analyzes the industrial and academic research difficulties, which are brought about by the combination of MLED and naked-eye light field display. This paper is the first to complete a technical review specifically focused on MLED and naked-eye light field display, which is expected to accelerate the technological development and application process of naked-eye light field display based on MLED panels.

Hydrophobic surface texture air-liquid phase composite assisted laser processing and tribological properties

In order to improve the surface hydrophobicity and tribological properties of 304 stainless steel, this study used laser processing technology to prepare three types of surface textures (CSA, CM2, CM5) in an air and air–liquid composite environment. By testing the surface quality, wettability and tribological properties of the texture, it was found that the surface quality and interfacial friction control ability of CSA were poor due to the influence of the processing environment. However, due to the air–liquid composite assisted laser preparation, while using the air medium laser processing technology to ensure the texture depth, the scattering effect of bubbles and the influence of negative pressure on the solid–liquid interface during the liquid phase assisted laser processing remove the oxide recast layer and burr on the surface of the sample, and improve the surface quality of the texture, thereby improving the surface friction behavior of the sample. This study promotes the development of surface texture laser processing technology and broadens the application field of 304 stainless steel.

Improving the Quality of Digital Images on Identity Cards Using Contrast Stretching and Retinex Methods

Enhancing the image quality of the Indonesian Identity Card is crucial to ensure the clarity and accuracy of information in various applications, such as identity verification, administration, and security. This study aims to improve the digital image quality of Identity Card using the Contrast Stretching and Retinex methods. Contrast Stretching is employed to enhance image contrast, while the Retinex method is used to maintain and improve the clarity of colors and image details. The implementation of these methods is carried out using Python. The test results show that these methods are effective in improving the quality of Identity Card images, making the information on the images clearer and easier to read. This research contributes to the development of more advanced image processing technology, which can be applied to various verification and administrative needs that require high reliability.

Evolution and future directions of Artificial Intelligence Generated Content (AIGC): A comprehensive review

Artificial Intelligence Generated Content (AIGC) has rapidly evolved, revolutionizing the creation of text, images, audio, and video content. Despite these advancements, research on the development process of AIGC technology remains scarce, necessitating a systematic discussion of its current state and future directions. So this paper delves into the significant advancements and foundational technologies driving AIGC, emphasizing the contributions of state-of-the-art models such as DALL-E 3 [1] and Sora [2]. We analyze the evolution of generative models from single-modal approaches to the current multimodal generative models. The paper further explores the application prospects of AIGC across various domains such as office work, art, education, and film, while addressing the existing limitations and challenges in the field. We propose potential improvement directions, including more efficient model architectures and enhanced multimodal capabilities. Emphasis is placed on the environmental impact of AIGC technologies and the need for sustainable practices. Our comprehensive review aims to provide researchers and professionals with a deeper understanding of AIGC, inspiring further exploration and innovation in this transformative domain.

A comprehensive review of the application of NLP technology in language learning

The rapid development of Natural Language Processing (NLP) technology has provided new perspectives and tools for the acquisition of second languages. As our world becomes increasingly interconnected, the role of NLP in facilitating language learning has become more prominent. This paper reviews the multifaceted applications of NLP technology in language learning, including auxiliary teaching functions such as reading assistance, writing feedback, oral interaction, and personalized learning. These applications have significantly enhanced language learners' abilities in vocabulary acquisition, grammatical application, pronunciation accuracy, and reading comprehension through real-time feedback, enhanced interactivity, and promotion of cultural understanding. Despite the immense potential of NLP technology in second language learning, challenges such as technical accuracy, cultural adaptability, and data privacy exist. This paper proposes strategies, such as ensuring technical accuracy, curating diverse datasets and safeguarding data privacy to address these challenges. Looking forward, the future development of NLP technology in second language education holds great promise. As NLP continues to evolve, it is expected to contribute to more personalized, effective, and accessible language learning solutions. This paper aims to provide valuable references and insights for educators, technology developers, and policymakers, enabling them to harness the transformative potential of NLP in language education and to navigate the future of educational technology with confidence and foresight.

Multi-Scale Feature Attention Fusion for Image Splicing Forgery Detection

Image splicing is a widely occurrence image tampering technology. With the rapid development of digital image processing technology, detecting image splicing forgery has become significantly challenging. Although various methods have been devised to identify such tampered images, existing approaches have not achieved optimal performance due to limitations in effectively leveraging feature maps of different scales. To address this issue, we propose a novel method for image splicing forgery detection called multi-scale feature attention fusion network (MFAF-Net). We propose a multi-scale atrous feature attention (MAFA) module designed to capture rich contextual features for multi-scale high-level feature fusion. Additionally, we present the multi-branch attention mechanism (MBAM) module to fuse contextual information from various branches for low-level features. This integration enhances the capability of low-level features to produce more refined pixel-level attention. We employ the weighted binary cross-entropy loss and dice loss in the MFAF-Net to overcome the imbalance between positive and negative samples. Extensive experiments demonstrate that the proposed MFAF-Net outperforms state-of-the-art methods. Robustness experiments also show our model exhibits image splicing forgery detection robustness under common attacks.

Behavioral and toxicological impacts of bio-derived oils in aqueous spills

There is an increasing global demand for, and transportation of, goods classified as Hazardous and Noxious Substances (HNS), including bio-derived oils and chemicals. With the increasing variety of bio-feedstocks and the development of processing technologies, the physical and chemical properties of commercially available and transported bio-derived oils vary significantly. The objective of this work was to analyze and compare the physical and chemical characteristics, behaviour, and risks of several bio-derived oils (four vegetable oils, one biodiesel, and two pyrolysis oils) and one petrol diesel when spilled into both fresh and salt water system. The laboratory results indicated that the vegetable oils and biodiesel remained buoyant and resulted in low total organic carbon (TOC) in water when spilled, similar behaviour to petrol diesel. However, the two pyrolysis oils exhibited remarkably different behaviours. The two oils sunk directly in the water and then rapidly dissolved the organic components into the water when mixed. This resulted in a high TOC (100 times higher than other types of oil) and an altered water chemistry, leaving a large portion of water-insoluble portion (35.0 wt% of pyrolysis oils) remaining at the water bottom. Initial Microtox findings indicated that water samples contaminated with pyrolysis oils and biodiesel (similar to petrol diesel) exhibited increased aqueous toxicity towards Vibrio fischeri. Further biological tests are required to understand their ecological risks. This work provides insights to the challenges and knowledge gaps on the fate, behaviour and risk of emerging bio-derived oils in water, while supporting HNS emergency response and remediation measures.

Abstract Cyclic Functional Relation and Taxonomies of Cyclic Signals Mathematical Models: Construction, Definitions and Properties

This work is devoted to the procedure of the construction of an abstract cyclic functional relation, which summarizes and extends the known results for a cyclically correlated random process and a cyclic (cyclically distributed) random process to the case of arbitrary cyclic functional relations. Two alternative definitions of the abstract cyclic functional relation are given, and the fundamental properties of its cyclic and phase structures are presented. The theorem on the invariance of cyclicity attributes of an abstract cyclic functional relation to shifts of its argument, and which are determined by the rhythm function of this functional relation, is formulated and proved. This theorem gives the sufficient and necessary conditions that the rhythm function of an abstract cyclic functional relation must satisfy. By specifying the range of values and attributes of the cyclicity of an abstract cyclic functional relation, the definitions of important classes of cyclic functional relations are formulated. A deductive approach to building a wide system of taxonomies of classes of deterministic, stochastic, fuzzy and interval cyclic functional relations as potential mathematical models of cyclic signals is demonstrated. A comparative analysis of an abstract cyclic functional relation with the known mathematical models of cyclic signals was carried out. The results obtained in the article significantly expand and systematize the mathematical tools of the description of cyclic signals and are the basis for the development of effective model-based technologies for processing and computer simulation of signals with a cyclic space-time structure.

Current Status and Trends in Shale Oil and Gas Drilling Engineering Technology Development at Home and Abroad

Abstract Shale oil and gas is an important component of unconventional oil and gas, and the United States has achieved energy independence through the shale revolution. China has abundant unconventional oil and gas resources, and the vigorous development of shale oil and gas is a necessary path for the development of China’s oil and gas industry. By systematically analyzing the developmental characteristics of shale oil and gas major countries, represented by North America, this study compares domestic and foreign shale oil and gas drilling engineering technologies from the perspectives of development process, well construction cycle, drilling parameters, and other aspects. It clarifies the advantages and challenges of Chinese shale oil and gas drilling engineering technology and provides targeted recommendations. The drilling mode for shale oil and gas in China has progressed from single horizontal wells to large-scale platform factory operations, significantly reducing costs and increasing efficiency. However, due to the complex geological conditions of shale formations and poor surface environment, China’s shale oil and gas wells have a horizontal section length about 1000 meters shorter than those in North America, and the well construction cycle is 2-3 times longer. There are still certain gaps in drilling efficiency and operating costs compared to foreign countries. By systematically analyzing the development process and parameter characteristics of shale oil and gas drilling engineering technology at home and abroad, this study clarifies the current status of drilling engineering technology, providing references for the integration and promotion of mature technologies, demonstration of key core technology breakthroughs, and exploration of cutting-edge technology research and development.

Construction of the technological process and design development of a multifunctional unit for processing vital soybeans with ultrasound. Feasibility of water-crude suspension

Cereals and legumes have a porous structure, being an inert carrier during mass exchange processes; they contain voids in the form of pores and stomata, on the surface of which there are foreign extractable substances in a solid state, in particular, trypsin and urease inhibitor proteins. These substances, due to their harmful effect on the final product, are subject to removal by extraction. One of the methods for inactivating anti-nutritional substances is ultrasonic treatment of soybeans.The article discusses the technology of inactivating inhibitors that worsen food and protein value of vital soybeans. The developed technology was aimed at dissolving a solid substance - soybean inhibitor protein in a liquid, carried out due to molecular diffusion, intensifying the processes of mass transfer and mass return. When creating a suspension by mixing the solid (crushed soybean grain) and liquid (water) phases, water molecules, which are a solvent, penetrate under the action of capillary forces into the pores and stomata of the treated body, begin to penetrate. On this basis, technological directions of research have been established, a sequence has been built and the physical essence of operations has been substantiated, consisting of four main ones - grinding soybean grain, creating a “water-soybean” suspension, ultrasonic (US) treatment of soybeans, drying. As a result of the conducted research, optimal technological parameters have been established for intensifying the process of inactivation of anti-nutritional substances contained in native soybeans: the degree of grinding of soybean grains is 0.5-1.0 mm; the ratio of water-soy suspension (1:1). The efficiency of the developed technological process will be factors affecting the quality of the resulting products, the duration and energy intensity of the process, resource conservation, simplicity of design and low cost of manufacture, the possibility of automation.

COMPUTER SIMULATION OF THE STRESS-STRAIN STATE OF BAR BLANKS MADE OF ALLOY 7075

The article presents a study of the characteristics and technological parameters of bar blanks made of aluminum alloy 7075, depending on the temperature and the forming process. The main goal is to determine the stress-strain state at various temperatures during the production of blanks, which contributes to understanding the mechanism of formation of the structure and properties of bar blanks. To do this, a computer simulation of the process based on the finite element method is used, using the Forge3D software environment. The results obtained confirm the uneven structure in the volume of workpieces, with a pronounced intensity of deformation in the surface layers. The formation of workpieces at different temperatures (200 and 250 °C) showed differences in stress intensity and strain rate, which is important for understanding the processes of formation of microstructure and material properties. Special attention is paid to the influence of temperature on the formation of stresses in the rods, as well as their distribution in thickness and length. The results obtained can be used to optimize the technological parameters of the aluminum alloy forming process in order to improve the quality of the final product and production efficiency. In general, the scientific conclusions of this study contribute to the further development of aluminum alloy processing technologies and their application in various industries. Keywords: computer modeling, finite element method, numerical model, processing technology, Forge3D, deformation characteristics, microstructure formation process.