Yangjian Si^1,2, Yujie Wei^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011974

Abstract Edge cracking represents one of the most prominent damage modes in engineering practice and hence receives immense attention from academic societies. When branched cracks or multiple cracks are present at the edge, their propagation may be affected by the interaction between the cracks. In this talk, we may cover the elasticity of a cracked half-plane with two typical scenarios: a double branched crack with two rays emanating from one point on the edge and two edge cracks spaced by a certain distance (Kalthoff–Winkler cracks). By adopting the combination of the Schwartz-Christoffel conformal mapping and the… More >

Songnan Yang¹, Miao Zhang¹, Rongrong Yao¹, Liangyu Chen¹, Weixuan Cong¹, Dan Yao², Jian Zhang^1,3, Jun Zhang^1,*, Xueying Li^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.9, pp. 2209-2225, 2024, DOI:10.32604/phyton.2024.055046 - 30 September 2024

Abstract The high isoflavones content of soybeans is an important breeding goal due to the demonstrated benefits of isoflavones to human health and their association with plant resistance. In this study, quantitative trait loci (QTL) mapping for soybean isoflavone aglycones, including daidzin, glycerin, and genistin, and total isoflavones content was performed in a population of 178 F_2:6 recombinant inbred lines (RILs) which was generated from a cross between varieties Jinong 17 and Jinong 18. A genetic linkage map covering 1248 cM was constructed using the simple sequence repeat (SSR) molecular markers. The results revealed 22 isoflavone-related QTLs,… More >

Shilpa Suman¹, Abhishek Rawat^2,*, Anil Kumar³, S. K. Tiwari⁴

Revue Internationale de Géomatique, Vol.33, pp. 363-381, 2024, DOI:10.32604/rig.2024.053981 - 18 September 2024

Abstract In this study, the impact of the training sample selection method on the performance of fuzzy-based Possibilistic c-means (PCM) and Noise Clustering (NC) classifiers were examined and mapped the cumin and fennel rabi crop. Two training sample selection approaches that have been investigated in this study are “mean” and “individual sample as mean”. Both training sample techniques were applied to the PCM and NC classifiers to classify the two indices approach. Both approaches have been studied to decrease spectral information in temporal data processing. The Modified Soil Adjusted Vegetation Index 2 (MSAVI-2) and Class-Based Sensor… More >

Emre Ozsahin^1,*, Huseyin Sarı², Duygu Boyraz Erdem², Mikayil Ozturk²

Revue Internationale de Géomatique, Vol.33, pp. 341-361, 2024, DOI:10.32604/rig.2024.054197 - 13 September 2024

Abstract This study assessed and mapped the spatial distribution of soil types and properties developed under the forest cover of the Strandzha Mountains of Türkiye. The study was conducted on a micro-scale in the riparian zone of the Balaban River, which characterizes the soils distributed in the mountainous area. The effect of environmental factors on the spatial distribution of soil types and properties was also determined. To gather data, soil sampling, laboratory analysis, data processing and mapping were sequentially performed. These data were analyzed using the Geographical Information System (GIS) based Random Forest (RF) machine learning… More > Graphic Abstract

Mohamed Rabik Mohamed Ismail¹, Muthuramalingam Thangaraj^1,*, Khaja Moiduddin^2,*, Zeyad Almutairi^2,3, Mustufa Haider Abidi²

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4263-4279, 2024, DOI:10.32604/cmc.2024.055271 - 12 September 2024

Abstract The measurement and mapping of objects in the outer environment have traditionally been conducted using ground-based monitoring systems, as well as satellites. More recently, unmanned aerial vehicles have also been employed for this purpose. The accurate detection and mapping of a target such as buildings, trees, and terrains are of utmost importance in various applications of unmanned aerial vehicles (UAVs), including search and rescue operations, object transportation, object detection, inspection tasks, and mapping activities. However, the rapid measurement and mapping of the object are not currently achievable due to factors such as the object’s size,… More >

Ahmad Nahar Quttoum^1,*, Muteb Alshammari²

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4577-4601, 2024, DOI:10.32604/cmc.2024.054102 - 12 September 2024

Abstract Cloud Datacenter Network (CDN) providers usually have the option to scale their network structures to allow for far more resource capacities, though such scaling options may come with exponential costs that contradict their utility objectives. Yet, besides the cost of the physical assets and network resources, such scaling may also impose more loads on the electricity power grids to feed the added nodes with the required energy to run and cool, which comes with extra costs too. Thus, those CDN providers who utilize their resources better can certainly afford their services at lower price-units when… More >

Maan Habib^1,*, Ahed Habib², Mohammad Abboud³

Revue Internationale de Géomatique, Vol.33, pp. 247-271, 2024, DOI:10.32604/rig.2024.053857 - 07 August 2024

Abstract Digital elevation models (DEMs) are essential tools in environmental science, particularly for hazard assessments and landscape analyses. However, their application across multiple environmental hazards simultaneously remains in need for a multi-aspect critical assessment to promote their effectiveness in comprehensive risk management. This paper aims to review and critically assess the application of DEMs in mapping and managing specific environmental hazards, namely floods, landslides, and coastal erosion. In this regard, it seeks to promote their utility of hazard maps as key tools in disaster risk reduction and environmental planning by employing high-resolution DEMs integrated with advanced More >

Pengcheng Li^1,2,#, Tianze Zhu^1,#, Yunyun Wang^1,2, Shuangyi Yin¹, Xinjie Zhu¹, Minggang Ji¹, Wenye Rui¹, Houmiao Wang¹, Zefeng Yang^1,2,*, Chenwu Xu^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.7, pp. 1441-1453, 2024, DOI:10.32604/phyton.2024.052219 - 30 July 2024

Abstract The nutritional composition and overall quality of maize kernels are largely determined by the key chemical components: protein, oil, and starch. Nevertheless, the genetic basis underlying these nutritional quality traits during grain filling remains poorly understood. In this study, the concentrations of protein, oil, and starch were studied in 204 recombinant inbred lines resulting from a cross between DH1M and T877 at four different stages post-pollination. All the traits exhibited considerable phenotypic variation. During the grain-filling stage, the levels of protein and starch content generally increased, whereas oil content decreased, with significant changes observed between… More >

Loghman Khodakarami^*

Revue Internationale de Géomatique, Vol.33, pp. 221-246, 2024, DOI:10.32604/rig.2024.050908 - 15 July 2024

Abstract Urban areas globally are escalating contributors to carbon dioxide (CO) emissions, challenging sustainable development. This study proposes a novel micro-scale approach utilizing GIS to quantify CO emission spatial distribution, enhancing urban sustainability assessment. Employing a “bottom-up” methodology, emissions were calculated for various sources, revealing Isfahan’s urban area emits 13,855,525 tons of CO annually. Major contributors include stationary and mobile sources such as power plants (50.61%), road and rail transport (17.18%), and residential sectors (21.78%). Spatial distribution mapping showed that 81.68% of CO emissions originate from stationary sources, notably power plants. Furthermore, mobile sources, including road More >

Muhammad S. Alam^1,5,*, Farhan B. Mohamed^1,3, Ali Selamat², Faruk Ahmed⁴, AKM B. Hossain^6,7

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 417-436, 2024, DOI:10.32604/iasc.2024.051999 - 11 July 2024

Abstract Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems. The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed. This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence. An annotated image dataset trains the proposed system and predicts the camera pose in real-time. The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera More >