Search Results (7)

In computer vision, recognizing plant pictures has emerged as a multidisciplinary area of interest. In the last several years, much research has been conducted to determine the type of plant in each image automatically. The challenges in identifying the medicinal plants are due to the changes in the effects of image light, stance, and orientation. Further, it is difficult to identify the medicinal plants due to factors like variations in leaf shape with age and changing leaf color in response to varying weather conditions. The proposed work uses machine learning techniques and deep neural networks to choose appropriate leaf features to determine if the leaf is a medicinal or non-medicinal plant. This study presents a neural network design based on PSR-LeafNet (PSR-LN). PSR-LeafNet is a single network that combines the P-Net, S-Net, and R-Net, all intended for leaf feature extraction using the minimum redundancy maximum relevance (MRMR) approach. The PSR-LN helps obtain the shape features, color features, venation of the leaf, and textural features. A support vector machine (SVM) is applied to the output achieved from the PSR network, which helps classify the name of the plant. The model design is named PSR-LN-SVM. The advantage of the designed model is that it suits more considerable dataset processing and provides better results than traditional neural network models. The methodology utilized in the work achieves an accuracy of 97.12% for the MalayaKew dataset, 98.10% for the IMP dataset, and 95.88% for the Flavia dataset. The proposed models surpass all the existing models, having an improvement in accuracy. These outcomes demonstrate that the suggested method is successful in accurately recognizing the leaves of medicinal plants, paving the way for more advanced uses in plant taxonomy and medicine. Full article

Hindwing venation is one of the most important morphological features for the functional and evolutionary analysis of beetles, as it is one of the key features used for the analysis of beetle flight performance and the design of beetle-like flapping wing micro aerial vehicles. However, manual landmark annotation for hindwing morphological analysis is a time-consuming process hindering the development of wing morphology research. In this paper, we present a novel approach for the detection of landmarks on the hindwings of leaf beetles (Coleoptera, Chrysomelidae) using a limited number of samples. The proposed method entails the transfer of a pre-existing model, trained on a large natural image dataset, to the specific domain of leaf beetle hindwings. This is achieved by using a deep high-resolution network as the backbone. The low-stage network parameters are frozen, while the high-stage parameters are re-trained to construct a leaf beetle hindwing landmark detection model. A leaf beetle hindwing landmark dataset was constructed, and the network was trained on varying numbers of randomly selected hindwing samples. The results demonstrate that the average detection normalized mean error for specific landmarks of leaf beetle hindwings (100 samples) remains below 0.02 and only reached 0.045 when using a mere three samples for training. Comparative analyses reveal that the proposed approach out-performs a prevalently used method (i.e., a deep residual network). This study showcases the practicability of employing natural images—specifically, those in ImageNet—for the purpose of pre-training leaf beetle hindwing landmark detection models in particular, providing a promising approach for insect wing venation digitization. Full article

The current study was designed to assess the comparative morphology of eight olive cultivars with different geographical origins and diverse genetic backgrounds, introduced to a new climatic zone. The morphological parameters of eight (five exotic and three domestic) olive cultivars (Bari Zaitoon-1, Bari Zaitoon-2, Favolosa (FS-17), Koroneiki, Balkasar, Ottobratica, Leccino, and Arbequina) were compared at the experimental area of the Department of Botany, The Islamia University of Bahawalpur, Pakistan (29°24′0″ North, 71°41′0″ East, 401–421 feet above sea level). Plant height, number of leaves/15 cm shoot, leaf size characteristics (leaf length, leaf width, leaf area, and length/width ratio), leaf shape characteristics (margin, leaf axil, base, and apex angles), leaf pigments (Chlorophyll a, Chlorophyll b, total chlorophyll contents, and carotenoids), phyllotaxy, and leaf color and venation were recorded. The highest plant height (28 cm) was obtained by Bari Zaitoon-2 followed by Bari Zaitoon-1 (24 cm), both of which are domestic cultivar of Pakistan, while the shortest height (5 cm) was obtained by Koroneiki. Leccino displayed the highest average number of leaves (17.8) on main shoot, followed by BARI-2 (16.4) and the lowest score was from Balkasar (10.4). Leaf area ranged from 5.66 cm² (Bari Zaitoon-1) to 3.08 cm² (Koroneiki). The longest leaf length (5.74 cm) was found in Bari Zaitoon-1 and the shortest (4.04 cm) in Koroneiki, while the broadest leaves were found in Leccino (1.54 cm) and the narrowest (1.12 cm) in Koroneiki. Bari Zaitoon-2 led in leaf length to width ratio (4.058) followed by Bari Zaitoon-1 (3.772) with small lanceolate leaves hardly reaching the value of 4, with the lowest value illustrated by Leccino. The total chloroplast pigments were highest in FS-17 followed by Bari Zaitoon-1 and Bari Zaitoon-2, while the lowest was in Arbequina. Chlorophyll a was highest in Bari Zaitoon-1 followed by FS-17 and Balkasar, with the lowest rate in Arbequina. Chlorophyll b content of FS-17 was the highest whereas the Chlorophyll b and total chlorophyll contents in Arbequina were the lowest of all the cultivars. The highest value of total carotenoids was found in Balkasar followed by FS-17 with the lowest value in Arbequina. The phyllotaxy was categorized into three types, i.e., alternate, opposite, and whorled. The combination of two or more types was usually observed on the same branch. The whorl of four leaves was also present in rare cases. Leaf venation was both pinnate and reticulate. The leaf base of most (four) of the olive cultivars, i.e., Arbequina, Balkasar, Leccino and FS-17, were cuneate having acute, rounded, apiculate, and cuspidate leaf tips, respectively. The findings revealed remarkable variations in olive morphology, especially in the leaves and a successful record of the preliminary data of olive cultivars from the study area was made. The present research demonstrated that local olive cultivars have unique characteristics that differentiate them from imported cultivars. Thus, local cultivars provide novel genetic resources that should be conserved. Full article

At present, the external environment is full of crises and challenges. The practice of firms deploying slack resources in advance and actively coping with external disturbances has achieved good effect. But, the theoretical research process of organizational slack is relatively slow compared with practice. Therefore, this paper comprehensively applied a bibliometric method and traditional literature review method to carry out scientific econometric analysis on 958 papers from the WoS database. We visualized the results as knowledge maps and analyzed papers with the help of the knowledge graph. The research venation and evolution trend of organizational slack are sorted out from a longitudinal perspective. On this basis, we put forward the future development direction of organizational slack in line with emerging phenomena, mainly including: ① Clarifying the sources of organizational slack; ② Two new dimensions of defensiveness slack and strategic slack are proposed from functional attributes; ③ Based on the perspective of active response, we expand the research depth of firms to construct organizational resilience through organization slack to adapt to uncertain environments. The purpose of this paper is to provide new ideas for firms to make plans before turbulence occurs in highly uncertain environments. It provides a useful reference for the future development of organizational slack research and promotes the formation of a virtuous cycle of mutual promotion between theory and practice. Full article

Up to now, the taxonomic conflict of the Apocynaceae family has attracted the attention of scientists and researchers worldwide. Recently, this family was divided into five subfamilies. The present study aims to investigate the implication of interlacing macro-, micro-morphological, anatomical, and chemical characteristics of the leaves of eight Apocynaceae plants (Adenium obesum, Dipladenia boliviensis, Carissacarandas, Nerium oleander, Asclepias curassavica, Calotropisprocera, Acokanthera oblongifolia, and Thevetia neriifolia), and to provide valuable taxonomic differentiation of these species. The macro-morphological investigation includes shape, apex, base, and venation of leaves, while the micro-morphological study includes leaf epidermal cells, stomata, and trichomes. The anatomical features of the leaf blade were studied by scanning electron microscope (SEM). Additionally, the chemical composition of the silylated methanolic extract was analyzed by Gas chromatography–mass spectroscopy (GC-MS). Sixty-three compounds were characterized from the silylated extracts of the eight plants, where quinic acid, sucrose, D-pinitol, and D-(−)-fructopyranose were determined as major compounds. The Principal Component Analysis (PCA) based on the chemical composition revealed a significant chemical correlation among all species with the presence of sugars and amino acids, as well as phenolic acids and iridoid glycosides. The cluster analysis, based on all merged characters, showed that the eight species can be categorized into three clusters. The first cluster comprises A.obesum, A. curassavica, and T. neriifolia, while the second cluster contains D. boliviensis, N. oleander, A. oblongifolia, and C. carandas, and the third cluster consists of C. procera alone. This cluster revealed some similarities to the recent classification of Apocynaceae, while it showed inconsistency regarding A.obesum, C. procera, and N. oleander. Due to the obtained inconsistent data and observed variation among the studied species, further study is recommended for more characterization of these species, based on additional parameters, including molecular characteristics, particularly A.obesum, C. procera, and N. oleander. Full article

Quantities of multi-temporal remote sensing (RS) images create favorable conditions for exploring the urban change in the long term. However, diverse multi-source features and change patterns bring challenges to the change detection in urban cases. In order to sort out the development venation of urban change detection, we make an observation of the literatures on change detection in the last five years, which focuses on the disparate multi-source RS images and multi-objective scenarios determined according to scene category. Based on the survey, a general change detection framework, including change information extraction, data fusion, and analysis of multi-objective scenarios modules, is summarized. Owing to the attributes of input RS images affect the technical selection of each module, data characteristics and application domains across different categories of RS images are discussed firstly. On this basis, not only the evolution process and relationship of the representative solutions are elaborated in the module description, through emphasizing the feasibility of fusing diverse data and the manifold application scenarios, we also advocate a complete change detection pipeline. At the end of the paper, we conclude the current development situation and put forward possible research direction of urban change detection, in the hope of providing insights to the following research. Full article

Process systems engineering (PSE), after being proposed by Sargent and contemporary researchers, has been fast developing in various domains and research communities around the world in the last couple of decades, with energy systems engineering featuring a typical yet still fast propagating domain, and the Chinese PSE community featuring a typical community with its own unique challenges for applying PSE theory and methods. In this paper, development of energy systems engineering and process systems engineering in China is discussed, and Sargent’s impacts on these two fields are the main focus. Pioneering work conducted by Sargent is firstly discussed. Then, a venation on how his work and thoughts have motivated later researchers and led to progressive advances is reviewed and analyzed. It shows that Sargent’s idea of optimum design and his work on nonlinear programming and superstructure modelling have resulted in well-known methods that are widely adopted in energy systems engineering and PSE applications in tackling problems in China. Following Sargent’s pioneering ideas and conceptual design of the PSE mansion, future development directions of energy systems engineering are also discussed. Full article