Processing Techniques Research Articles

Enhancing mechanical performance of kenaf fiber reinforced polymer composites: influence of fiber characteristics and processing techniques

Enhancing mechanical performance of kenaf fiber reinforced polymer composites: influence of fiber characteristics and processing techniques

Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review

ObjectiveTo conduct a systematic review of the computer vision applications that detect, diagnose, or analyse tuberculosis (TB) pathology or bacilli using digitised human lung tissue images either through automatic or semi-automatic methods. We categorised the computer vision platform into four technologies: image processing, object/pattern recognition, computer graphics, and deep learning. In this paper, the focus is on image processing and deep learning (DL) applications for either 2D or 3D digitised human lung tissue images. This review is useful for establishing a common practice in TB analysis using human lung tissue as well as identifying opportunities for further research in this space. The review brings attention to the state-of-art techniques for detecting TB, with emphasis on the challenges and limitations of the current techniques. The ultimate goal is to promote the development of more efficient and accurate algorithms for the detection or analysis of TB, and raise awareness about the importance of early detection.DesignWe searched five databases and Google Scholar for articles published between January 2017 and December 2022 that focus on Mycobacterium tuberculosis detection, or tuberculosis pathology using digitised human lung tissue images. Details regarding design, image processing and computer-aided techniques, deep learning models, and datasets were collected and summarised. Discussions, analysis, and comparisons of state-of-the-art methods are provided to help guide future research. Further, a brief update on the relevant techniques and their performance is provided.ResultsSeveral studies have been conducted to develop automated and AI-assisted methods for diagnosing Mtb and TB pathology from digitised human lung tissue images. Some studies presented a completely automated method of diagnosis, while other studies developed AI-assisted diagnostic methods. Low-level focus areas included the development of a novel μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu$$\\end{document}CT scanner for soft tissue image contract, and use of multiresolution computed tomography to analyse the 3D structure of the human lung. High-level focus areas included the investigation the effects of aging on the number and size of small airways in the lungs using CT and whole lung high-resolution μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu$$\\end{document}CT, and the 3D microanatomy characterisation of human tuberculosis lung using μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\upmu$$\\end{document}CT in conjunction with histology and immunohistochemistry. Additionally, a novel method for acquiring high-resolution 3D images of human lung structure and topology is also presented.ConclusionThe literature indicates that post 1950s, TB was predominantly studied using animal models even though no animal model reflects the full spectrum of human pulmonary TB disease and does not reproducibly transmit Mtb infection to other animals (Hunter, 2011). This explains why there are very few studies that used human lung tissue for detection or analysis of Mtb. Nonetheless, we found 10 studies that used human tissues (predominately lung) of which five studies proposed machine learning (ML) models for the detection of bacilli and the other five used CT on human lung tissue scanned ex-vivo.

Optimization of High-Frequency Trading Strategies Using Deep Reinforcement Learning

This study presents a new method for optimising high-risk trading (HFT) strategies using deep learning (DRL). We propose a multi-time DRL framework integrating advanced neural network architectures with sophisticated business data processing techniques. The framework employs a combination of convolutional neural networks for manual order analysis, short-term memory networks for time series processing, and a multi-head listening mechanism for body fusion. We formulate the HFT problem based on Markov Decision Processes and use the Proximal Policy Optimization algorithm for training. The model is evaluated using tick-by-tick data from the NASDAQ exchange, including ten liquid stocks in 6 months. The experimental results show the superiority of our method, achieving a Sharpe ratio of 3.42, outperforming the learning model and machine learning based on benchmarks up to 33%. The proposed strategy has demonstrated strong performance across a wide range of regulatory markets and has shown potential for strategic objectives. Sensitivity analysis confirms the model's stability across a range of hyperparameters. Our findings suggest that the DRL-based approach can improve HFT performance and provide better market adaptation and risk management. This research leads to the continuous evolution of algorithmic trading strategies and shows the potential of AI-driven approaches in financial markets.

Three-Dimensional Hullform Reconstruction from Two-Dimensional Drawings Based on Image Processing Techniques

Abstract Repair shipyards sometimes need three-dimensional geometry for repairs and retrofits. However, they often create models manually from two-dimensional drawings provided by ship owners. In this case, human error leads to inaccuracies, making the process time-consuming and laborious. Therefore, there is a need for research on efficient three-dimensional hullform reconstruction from two-dimensional drawings. This study proposed a method to automatically extract points from two-dimensional lines and visualize them in three dimensions. The proposed method consists of three steps. The first step is a point extraction through image processing, which uses a starting point search algorithm to access overlapping or intersection lines and extracts the points on the lines in the drawing by searching for paths between the starting point and the end point entered by the user. The second step is the transformation of the extracted data, which transforms the points based on pixel coordinate into 3D points through coordinate transformation and scaling by utilizing the stored line data and three-dimensional coordinate information. The last step is to visualize the transformed data as a real three-dimensional model with point visualization. This study demonstrates that the proposed method can be effectively utilized by detecting two-dimensional lines and reconstructing the hullform in three dimensions.

Integrating dynamic high-throughput phenotyping and genetic analysis to monitor growth variation in foxtail millet

BackgroundFoxtail millet [Setaria italica (L.) Beauv] is a C4 graminoid crop cultivated mainly in the arid and semiarid regions of China for more than 7000 years. Its grain highly nutritious and is rich in starch, protein, essential vitamins such as carotenoids, folate, and minerals. To expand the utilisation of foxtail millet, efficient and precise methods for dynamic phenotyping of its growth stages are needed. Traditional foxtail millet monitoring methods have high labour costs and are inefficient and inaccurate, impeding the precise evaluation of foxtail millet genotypic variation.ResultsThis study introduces a high-throughput imaging system (HIS) with advanced image processing techniques to enhance monitoring efficiency and data quality. The HIS can accurately extract a range of key growth feature parameters, such as plant height (PH), convex hull area (CHA), side projected area (SPA) and colour distribution, from foxtail millet images. Compared with traditional manual measurements, this HIS improved data quality and phenotyping of the key foxtail millet growth traits. High-throughput phenotyping combined with a genome-wide association study (GWAS) revealed genetic loci associated with dynamic growth traits, particularly plant height (PH), in foxtail millet. The loci were linked to genes involved in the gibberellic acid (GA) synthesis pathway related to PH.ConclusionThe HIS developed in this study enables the efficient and dynamic monitoring of foxtail millet phenotypic traits. It significantly improves the quality of data obtained for phenotyping key growth traits. The integration of high-throughput phenotyping with GWAS provides new insights into the genetic underpinnings of dynamic growth traits, particularly plant height, by identifying associated genetic loci in the GA synthesis pathway. This methodological advancement opens new avenues for the precise phenotyping and exploration of genetic resources in foxtail millet, potentially enhancing its utilisation.

Processing, Value Addition and Post-Harvest Technology of Tomato: A Scoping Review on Global and Indian Perspective

India, with its favorable climatic conditions, is a major producer of tomatoes, ranking second globally. However, the tomato processing sector in India is underdeveloped, with only 1% of the produce being processed compared to developed nations such as Italy (64.02%), Spain (39.41%) and the United States (10.34%). Of the more than 180 million tonnes of tomatoes produced annually, around 40 million tonnes are processed. India's substantial tomato output, which occurs primarily in the winter, has made it a prominent participant in the global tomato processing industry. This would help the Indian market utilize tomato-based goods throughout the off-season. Lycopene, a beneficial compound, is found to be higher in processed tomato products compared to fresh tomatoes. Prominent companies in the Indian tomato processing industry include Hindustan Unilever, Nestle India, Mother Dairy, and Dabur India. Despite the potential, the sector faces challenges such as inadequate processing facilities and limited varieties suitable for processing, leading to substantial post-harvest losses. The demand for tomato-processed products in India has been increasing at 30% annually in recent years, with a rising variety of products being offered. Increased support, improved supply chain management, and adoption of advanced processing techniques could reduce wastage, add value, and enable India to become a prominent player in the global tomato processing industry. With the adoption of modern technologies such as automated sorting, grading, and cold storage facilities, the efficiency of the tomato processing industry can improve. This would reduce post-harvest losses and ensure better quality control.

Unravelling the Electrical Field Induced Ion Migration in Flexible OLEDs with PEDOT:PSS Electrodes.

The development of flexible organic light-emitting didoes (FOLEDs) has spurred the research on flexible transparent electrodes (FTEs). Poly(3,4-ethylenedioxythiophene):polystyrenesulfonate (PEDOT:PSS) is one of the most attractive FTEs due to its adjustable conductivity and compatibility with low-cost and large-scale solution processing techniques. Significantly, highly efficient FOLEDs have been achieved with modified PEDOT:PSS FTEs. However, the intrinsic mechanisms that contribute to device degradation of FOLEDs utilizing PEDOT:PSS FTEs have not yet been fully elucidated. In this work, three ionic liquids (ILs) are used to enhance the electrical conductivity and mechanical flexibility of PEDOT:PSS FTEs. Simultaneously, the influence of the electric field induced ion migration from PEDOT:PSS FTEs on the operational stability of FOLEDs is unraveled. We find that the ILs with larger ionic radii and higher steric hindrance are beneficial to suppressing the electrical field induced ion migration and improving the operational stability of FOLEDs. Finally, large-area and high-performance FOLEDs are achieved based on the IL of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide modified PEDOT:PSS FTEs, which demonstrate a high current efficiency of 98.1 cd/A and a longer lifetime of 66.7 min. This finding may promote the practical application of PEDOT:PSS FTEs in flexible optoelectronics.

Comparing inpainting techniques for urban object restoration from orbital images

Abstract. Based on the comparison of three established inpainting techniques, namely Criminisi, Beltamio, and Galerne and Leclaire, our study aimed to identify the most effective method for road restoration after extraction and detection using a Mathematical Morphology operators combined with hybrid techniques of digital image processing in remote sensing images. While all techniques were evaluated based on both visual analysis and quantitative metrics, the Criminisi approach emerged as the better choice. Despite introducing some additional noise, this technique demonstrated superior performance in terms of Completeness and overall Quality, achieving approximately 95.23% and 94.56%, respectively. Its ability to accurately reconstruct linear geometries while effectively removing existing noise highlighted its suitability for road restoration tasks.

Comprehensive Study of Stereolithography and Digital Light Processing Printing of Zirconia Photosensitive Suspensions

Zirconia ceramics are used in a wide range of applications, including dental restorations, bioimplants, and fuel cells, due to their accessibility, biocompatibility, chemical resistance, and favorable mechanical properties. Following the development of 3D printing technologies, it is possible to rapidly print zirconia-based objects with high precision using stereolithography (SLA) and digital light processing (DLP) techniques. The advantages of these techniques include the ability to print multiple objects simultaneously on the printing platform. To align with the quality standards, it is necessary to focus on optimizing processing factors such as the viscosity of the suspension and particle size, as well as the prevention of particle agglomeration and sedimentation during printing, comprising the choice of a suitable debinding and sintering mode. The presented review provides a detailed overview of the recent trends in preparing routes for zirconium oxide bodies; from preparing the suspension through printing and sintering to characterizing mechanical properties. Additionally, the review offers insight into applications of zirconium-based ceramics.

Detection of Ovarian Tumors Using TVUS Imaging and Segmentation Techniques

Ovarian most cancers remains a giant health subject due to its regularly asymptomatic development until superior stages, where treatment options are confined. Early detection is critical for enhancing affected person outcomes and survival costs. This observe proposes a comprehensive technique leveraging superior photograph processing techniques for the early detection and category of ovarian tumors the usage of trans vaginal ultrasound (TVUS) snap shots. The method starts with preprocessing steps which include median filtering to do away with noise artifacts inclusive of salt and pepper noise from ultrasound photos. Ultimately, picture enhancement techniques are applied to enhance contrast and intensity, observed through binary sample evaluation to signify texture features vital for tumor identification. Photo segmentation is performed the use of okay- manner clustering and gray degree Co-prevalence Matrix (GLCM) analysis to isolate and analyze areas of interest within the ovarian photos. A Convolutional Neural community (CNN) is then hired for correct classification of ovarian tumors as regular, benign, or malignant primarily based on the extracted functions. This approach not handiest enhances the diagnostic accuracy but also minimizes affected person publicity to ionizing radiation, making it appropriate for ordinary medical applications. The proposed methodology represents a considerable advancement within the discipline of ovarian cancer detection, presenting a non-invasive and green way to evaluate ovarian health and facilitate timely intervention. Destiny research directions include refining the set of rules’s performance with large datasets and exploring additional imaging modalities for complete ovarian fitness evaluation.

Dual Energy Metal Artifact Reduction for Iodine-125 Seed Identification in Postimplant CT after Prostate Brachytherapy.

To assess the metal artifact reductions of dual-energy computed tomography (DECT) high-energy virtual monochromatic images (VMI) combined with the single energy metal artifact reduction (SEMER) (CANON MEDICAL SYSTEMS, Otawara, Japan) processing techniques for iodine (I)-125 seed identification in postimplant computed tomography (CT) after prostate brachytherapy. Dual-energy acquisition with fast tube voltage switching was performed on a prostate phantom with simulated seeds and six clinical cases treated with I-125 prostate brachytherapy. The images were retrospectively reconstructed at VMI energy levels of 65-200 keV and with and without SEMAR (SEMAR and non-SEMAR images). To estimate seed swelling, the caliber of iodine-125 seed was calculated as the full width at half maximum. The metal artifacts were evaluated using the artifact index (AI). The dose distributions were calculated and were compared among the high-energy VMI (SEMAR and non-SEMAR images) and low-energy VMI (SEMAR images). The blooming artifacts decreased at higher energy levels. In addition, the SEMAR process markedly reduced AI, which helped reduce overestimation of high dose ranges in the treatment planning dose map. The locations and number of iodine-125 seed were clearly identified in the dose distribution map of the treatment planning using 200keV VMI with SEMAR. The high-energy VMI of the dual energy CT in combination with SEMAR is appropriate for the postimplant planning process of I-125 prostate brachytherapy.

Utilizing Multiple Triboelectric Nanogenerator Sensors and Signal Processing Technology for Monitoring Periodic Leg Movements of Sleep

High-quality sleep is essential for both physiological and cognitive functions. However, periodic leg movements of sleep (PLMS), an involuntary phenomenon during sleep, affects millions of people worldwide, contributing to sleep fragmentation and functional impairments. The accurate monitoring of PLMS is important for identifying and addressing these issues. Traditional methods, such as polysomnography (PSG), which monitor the bare tibialis muscle movements in clinical environments, may not adequately reflect the natural sleep patterns at home. They are costly and unsuitable for long-term studies. In recent years, there has been growing interest in using flexible sensors for sleep monitoring. Previous studies have applied triboelectric nanogenerators (TENGs) as flexible sensors to detect muscle movements during sleep. However, distinguishing true PLMS from false signals caused by external factors, such as blankets, remains a challenge. This study proposes a method using three TENG sensors placed on the dorsum, ankle, and tibialis, respectively, along with signal processing techniques to enhance the accuracy of PLMS detection. This study provides a cost-effective, comfortable method for PLMS monitoring, with the potential for widespread use in home-based sleep studies and long-term care in the future.

Cold plasma technology: does it have a place in food processing?

In recent years, there has been a growing demand for alternative food processing technologies that can improve food safety while preserving the nutritional quality of food products. Traditional thermal processing methods can lead to nutrient loss and degradation, prompting the exploration of novel approaches. Cold plasma (CP) technology, an emerging non-thermal food processing technique, has gained significant attention for its potential in the food industry. We provide herein, an introduction to CP and an overview of the technology, highlighting its potential advantages in safety, efficiency, and environmental friendliness.

From Waste to Strength: A Comprehensive Review on Using Fly Ash in Composites with Enhanced Mechanical Properties

This article explores the diverse applications of fly ash (FA), a by-product generated during the combustion of coal. The introductory segment thoroughly comprehends the origins, composition, and widespread occurrence of FA. FA, which comprises an estimated 38% of worldwide power generation, frequently encounters disposal and storage obstacles on account of its classification as non-hazardous waste in the majority of countries. The environmental issues linked to the dispersal of FA are underscored in the problem statement, which further emphasizes the urgency for sustainable alternatives. Due to the fugitive emissions and potential health hazards associated with metal melting in FA, it is critical to investigate novel applications and disposal techniques immediately. Environmental sustainability is a primary focus of research, with the development of synthetic FA composites being one such alternative. The analysis presents significant findings that underscore the wide-ranging applications of FA. These applications include its utilization as a filler in composites, as well as its incorporation into cement and geo-polymerization processes. Notably, (10-20) wt. % Nano-FA enhances epoxy-based composites, showcasing remarkable improvements in tensile strength, flexural strength, and impact resistance. In thermoplastic composites, substantial enhancements occur within the (5–10) wt. % FA range, but exceeding optimal ranges weakens matrix-fiber interaction, leading to diminishing returns. The article emphasizes the criticality of FA in improving the mechanical and thermodynamic characteristics of substances, specifically within the domain of composites. The investigation into FA nanoparticles, including their processing techniques and surface treatments, unveils encouraging prospects for enhancing material characteristics.

MENGOPTIMALKAN KAPABILITAS INOVASI, KOMPETENSI DAN BUDAYA CATUR PURUSA ARTHA DALAM ERA DIGITAL: PERAN KINERJA UMKM

This study aims to determine the effect of innovation capability variables, competence, and catur purusa artha on the performance of MSMEs in Bali Province. The respondent data sampled in this study were MSMEs in Bali Province using a questionnaire method using 100 MSME samples calculated using the Slovin formula. In contrast, the data processing and analysis techniques used SPSS software. The findings of this study indicate that: 1) Innovation capability does not have a significant effect on the performance of MSMEs, 2) Competence has a positive and significant effect on the performance of MSMEs, 3) Catur Purusa Artha has a positive and significant effect on the performance of MSMEs.

Semi-automated title-abstract screening using natural language processing and machine learning

BackgroundTitle-abstract screening in the preparation of a systematic review is a time-consuming task. Modern techniques of natural language processing and machine learning might allow partly automatization of title-abstract screening. In particular, clear guidance on how to proceed with these techniques in practice is of high relevance.MethodsThis paper presents an entire pipeline how to use natural language processing techniques to make the titles and abstracts usable for machine learning and how to apply machine learning algorithms to adequately predict whether or not a publication should be forwarded to full text screening. Guidance for the practical use of the methodology is given.ResultsThe appealing performance of the approach is demonstrated by means of two real-world systematic reviews with meta analysis.ConclusionsNatural language processing and machine learning can help to semi-automatize title-abstract screening. Different project-specific considerations have to be made for applying them in practice.

Subcortical Aphasia: An Update.

This review aims to rediscuss the leading theories concerning the role of basal ganglia and the thalamus in the genesis of aphasic symptoms in the absence of gross anatomical lesions in cortical language areas as assessed by conventional neuroimaging studies. New concepts in language processing and modern neuroimaging techniques have enabled some progress in resolving the impasse between the current dominant theories: (a) direct and specific linguistic processing and (b) subcortical structures as processing relays in domain-general functions. Of particular interest are studies of connectivity based on functional magnetic resonance imaging (MRI) and tractography that highlight the impact of white matter pathway lesions on aphasia development and recovery. Connectivity studies have put into evidence the central role of the arcuate fasciculus (AF), inferior frontal occipital fasciculus (IFOF), and uncinate fasciculus (UF) in the genesis of aphasia. Regarding the thalamus, its involvement in lexical-semantic processing through modulation of the frontal cortex is becoming increasingly apparent.

Consumer Safety and Pesticide Residues: Evaluating Mitigation Protocols for Greengrocery

The application of pesticides remains a necessary measure for pest management in agriculture, particularly in the cultivation of fruits and vegetables. After harvest, the presence of pesticide residues in greengrocery (fruits and vegetables) is significantly influenced by various factors, including storage conditions, handling practices, and subsequent processing methods. The mitigation of these residues to levels compliant with regulated maximum thresholds ensures the safety of raw and processed fruits and vegetables for consumption. A contemporary survey of pesticide residues in greengrocery has gathered considerable attention from consumers, driven by concerns over the potential health risk of pesticide exposure. Consequently, consumers want to be extensively informed about household processing techniques to minimize associated risks. Meanwhile, a critical question arises: does household processing effectively eliminate pesticide residues? A comprehensive review of the literature reveals that conventional methods, such as washing and soaking, offer only limited reduction in residue levels, while emerging treatments, suitable both at household and industrial scale, demonstrate increased efficiency in residues mitigation. This study aims to emphasise the ubiquitous use of pesticides in crop cultivation while providing recommendations for the implementation of efficient treatment protocols to address residue concerns. Following upon available evidence and database mining, the worldwide purpose must be to outline agriculturally and economically viable strategies that prioritize both the health and safety of consumers, as well as the green cultivation and processing of fruits and vegetables.

Ultrasonic Total Focusing Method Technology in Carbon Steel Butt Weld Application

Carbon steel butt welds are widely used in aircraft carrier, shipbuilding, railway, aerospace and other industries. As a new technology of ultrasonic non-destructive testing, Total Focusing Method (TFM) technology is a method of image reconstruction in which the value of each constituent datum of the image results from focused ultrasound. TFM may also be understood as a broad term encompassing a family of processing techniques for image reconstruction from full matrix capture (FMC). This paper compares resolution and focus between TFM and conventional phased array technology, by using phased array test block type B. The paper also introduces the testing system, including equipment, probe, wedge, calibration block as per ASME, PC analysis software, for detection of 21mm thickness carbon steel welds. In order to improve the defect detection ability, a customized software on board was designed based on TFM technology, and an appropriate propagation mode was adopted for different types of defects, such as longitudinal cracks on surface, lack of fusion, porosities, slag inclusions. The test results showing that compared with conventional phased array technology, the defect information such as length and depth detected by TFM are nearer to the actual situation, and the shape is closer to the physical one. TFM technology has more advantages in quantitative and qualitative capabilities in testing carbon steel butt welds, and can meet the requirements of on-site testing.

Surveying the Use of Social Media Data and Natural Language Processing Techniques to Investigate Natural Disasters

Surveying the Use of Social Media Data and Natural Language Processing Techniques to Investigate Natural Disasters