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Citrus production : technological advancements and adaptation to changing climate
\"The citrus industry is one of the world's most important fruit production industries, but global climate change, pests, diseases, and improper handling are affecting plant yields. CitrusProduction: Technological Advancements and Adaptation to Changing Climate presents information on advancements in the citrus industry examining various aspects of citrus from its production to harvest. It looks at the challenges and approaches in stress tolerance improvements, increasing citrus crop productivity, and reducing postharvest losses. The book details taxonomy, genetic diversity, and metabolic and molecular responses in citrus crops, as well as abiotic and biotic stresses affecting citrus production. Featuring numerous full-color illustrations throughout, this book poses new harvesting techniques along with postharvest physiology of citrus fruits, devising strategies to prevent crop losses. Citrus Production: Technological Advancements and Adaptation to Changing Climate is an essential resource for researchers, academicians, and scientists looking to expand their knowledge of citrus, particularly horticulturists, food scientists, and botanists\"-- Provided by publisher.
BOOK
YOLO-v1 to YOLO-v8, the Rise of YOLO and Its Complementary Nature toward Digital Manufacturing and Industrial Defect Detection
Since its inception in 2015, the YOLO (You Only Look Once) variant of object detectors has rapidly grown, with the latest release of YOLO-v8 in January 2023. YOLO variants are underpinned by the principle of real-time and high-classification performance, based on limited but efficient computational parameters. This principle has been found within the DNA of all YOLO variants with increasing intensity, as the variants evolve addressing the requirements of automated quality inspection within the industrial surface defect detection domain, such as the need for fast detection, high accuracy, and deployment onto constrained edge devices. This paper is the first to provide an in-depth review of the YOLO evolution from the original YOLO to the recent release (YOLO-v8) from the perspective of industrial manufacturing. The review explores the key architectural advancements proposed at each iteration, followed by examples of industrial deployment for surface defect detection endorsing its compatibility with industrial requirements.
Journal Article
YOLO-v5 Variant Selection Algorithm Coupled with Representative Augmentations for Modelling Production-Based Variance in Automated Lightweight Pallet Racking Inspection
The aim of this research is to develop an automated pallet inspection architecture with two key objectives: high performance with respect to defect classification and computational efficacy, i.e., lightweight footprint. As automated pallet racking via machine vision is a developing field, the procurement of racking datasets can be a difficult task. Therefore, the first contribution of this study was the proposal of several tailored augmentations that were generated based on modelling production floor conditions/variances within warehouses. Secondly, the variant selection algorithm was proposed, starting with extreme-end analysis and providing a protocol for selecting the optimal architecture with respect to accuracy and computational efficiency. The proposed YOLO-v5n architecture generated the highest MAP@0.5 of 96.8% compared to previous works in the racking domain, with a computational footprint in terms of the number of parameters at its lowest, i.e., 1.9 M compared to YOLO-v5x at 86.7 M.
Journal Article
Sustainable Machine Vision for Industry 4.0: A Comprehensive Review of Convolutional Neural Networks and Hardware Accelerators in Computer Vision
As manifestations of Industry 4.0. become visible across various applications, one key and opportune area of development are quality inspection processes and defect detection. Over the last decade, computer vision architectures, in particular, object detectors have received increasing attention from the research community, due to their localisation advantage over image classification. However, for these architectural advancements to provide tangible solutions, they must be optimised with respect to the target hardware along with the deployment environment. To this effect, this survey provides an in-depth review of the architectural progression of image classification and object detection architectures with a focus on advancements within Artificially Intelligent accelerator hardware. This will provide readers with an understanding of the present state of architecture–hardware integration within the computer vision discipline. The review also provides examples of the industrial implementation of computer vision architectures across various domains, from the detection of fabric defects to pallet racking inspection. The survey highlights the need for representative hardware-benchmarked datasets for providing better performance comparisons along with envisioning object detection as the primary domain where more research efforts would be focused over the next decade.
Journal Article
Effects of board gender diversity and sustainability committees on environmental performance: a quantile regression approach
This study examines the effect of board gender diversity (BGD) and sustainability committees on environmental performance. Using a quantile regression approach and a sample of publicly listed firms in Italy, we find that BGD and sustainability committees have different effects on firms' environmental performance over different points of conditional distribution. This shows that BGD and sustainability committees have greater quantitative impact in firms performing better environmentally and are positively related to environmental performance. We further discover that large Italian firms that reach a critical mass of three female directors maintain a stronger attitude towards environmental sustainability. Overall, the results confirm that BGD and sustainability committees enhance board effectiveness and help promote sustainable environmental initiatives. This study provides empirical evidence from a context that has not yet been investigated. It further augments the literature by employing a quantile regression approach, mostly unexamined by previous studies.
Journal Article
A Review of the Real-Time Monitoring of Fluid-Properties in Tubular Architectures for Industrial Applications
The real-time monitoring of fluid properties in tubular systems, such as viscosity and flow rate, is essential for industries utilizing liquid mediums. Nowadays, most studies of the fluid characteristics are performed off-line using laboratory facilities that can provide accurate results, yet they do not match the demanded industrial pace. Off-line measurements are ineffective and time-consuming. The available real-time monitoring sensors for fluid properties are generally destructive methods that produce significant and persistent damage to the tubular systems during the installation process. Others use huge and bulky invasive instrument methods that generate considerable pressure reduction and energy loss in tubular systems. For these drawbacks, industries centered their attention on non-invasive and non-destructive testing (NDT) methodologies, which are installed on the outer tubular surface to avoid flow disturbance and desist shutting down systems for installations. Although these sensors showed excellent achievement for monitoring and inspecting pipe health conditions, the performance was not convincing for monitoring the properties of fluids. This review paper presents an overview of the real-time monitoring of fluid properties in tubular systems for industrial applications, particularly for pipe monitoring sensors, viscosity, and flow measurements. Additionally, the different available sensing mechanisms and their advantages, drawbacks, and potentials are discussed.
Journal Article
Domain Feature Mapping with YOLOv7 for Automated Edge-Based Pallet Racking Inspections
Pallet racking is an essential element within warehouses, distribution centers, and manufacturing facilities. To guarantee its safe operation as well as stock protection and personnel safety, pallet racking requires continuous inspections and timely maintenance in the case of damage being discovered. Conventionally, a rack inspection is a manual quality inspection process completed by certified inspectors. The manual process results in operational down-time as well as inspection and certification costs and undiscovered damage due to human error. Inspired by the trend toward smart industrial operations, we present a computer vision-based autonomous rack inspection framework centered around YOLOv7 architecture. Additionally, we propose a domain variance modeling mechanism for addressing the issue of data scarcity through the generation of representative data samples. Our proposed framework achieved a mean average precision of 91.1%.
Journal Article
Evaluating Green Technology Strategies for the Sustainable Development of Solar Power Projects: Evidence from Pakistan
Energy is the main element for a modern lifestyle that must be considered in economically reliable and sustainable development dialogues. The financial performance of solar power projects has become the main issue, especially in developing countries such as Pakistan, where it has gained the special attention of government and regulatory authorities. The present study evaluates green technology strategies for the sustainable development of solar power projects in Pakistan. We examine the moderating role of cost and riskiness of the methods between the nexus of capital budgeting techniques and the financial performance of solar power projects. The analysis is performed on data collected from 44 respondents (chief financial officers and chief executive officers) by accompanying an inclusive questionnaire survey. Partial least squares structural equation modeling (PLS-SEM) is used to assess the formulated suppositions. The results reveal that green technology strategies positively impact the sustainable development of solar power projects. The profitability index is a good source of higher financial performance of the solar power projects. The results further demonstrate that the cost and riskiness of the methods significantly moderate the nexus of capital budgeting techniques and the financial performance of solar power projects. These findings provide a valuable manual for policymakers, government institutions, and regulators to select the appropriate green technology strategy to increase cleaner production and sustainable development of solar power projects.
Journal Article
Sentinel-1A for monitoring land subsidence of coastal city of Pakistan using Persistent Scatterers In-SAR technique
Karachi is located in the southern part of Pakistan along the Arabian Sea coast. Relevant institutions are concerned about the possibility of ground subsidence in the city, contributing to the comparative sea-level rise. So yet, no direct measurement of the subsidence rate and its relation to city submergence danger has been made. SAR (Synthetic Aperture Radar) interferometry is a powerful method for obtaining millimeter-accurate surface displacement measurements. The Sentinel-1 satellite data provide extensive geographical coverage, regular acquisitions, and open access. This research used the persistent scatterer interferometry synthetic aperture radar (PS-InSAR) technology with Sentinel-1 SAR images to monitor ground subsidence in Karachi, Pakistan. The SARPROZ software was used to analyze a series of Sentinel-1A images taken from November 2019 to December 2020 along ascending and descending orbit paths to assess land subsidence in Karachi. The cumulative deformation in Line of Sight (LOS) ranged from − 68.91 to 76.06 mm/year, whereas the vertical deformation in LOS ranged from − 67.66 to 74.68 mm/year. The data reveal a considerable rise in subsidence from 2019 to 2020. The general pattern of subsidence indicated very high values in the city center, whereas locations outside the city center saw minimal subsidence. Overall, the proposed technique effectively maps, identifies, and monitors land areas susceptible to subsidence. This will allow for more efficient planning, construction of surface infrastructure, and control of subsidence-induced risks.
Journal Article
Crop diversification and saline water irrigation as potential strategies to save freshwater resources and reclamation of marginal soils—a review
Feeding 9 billion by 2050 is one of major challenges for researchers. Use of diversified crops, nonconventional water resources and rehabilitation of marginal lands are alternate options to produce more food to face climate change projections. Adaptation to climate change through climate smart agriculture practices, agroecology activities, and crop-based management packages can help transform the marginal lands from environmental burdens into productive and economic blocks. This review discusses the recent advancements on specialty group of alternate crops (oil seeds, legumes, cereals, medicinal, lignocellulose, and fruit crops) which can adapt in the marginal environments. Availability of alternate water resources (saline water, treated wastewater) for irrigation cannot be omitted. Crop diversification systems involving drought and salt-tolerant crops are likely to be the key to future agricultural and economic growth in the regions where salt-affected soils exist and/or saline aquifers are pumped for irrigation. These systems may tackle three main tasks: sustainable management of land resources and enhancement of per unit productivity; intensification of agroecological practices to increase soil fertility; and improving productivity of marginal lands for diversified climate smart crops. This review explores various aspects of marginal lands and selection of tolerant crop genotypes, crop diversification, and agroecological practices to maximize benefits.
Journal Article