Chen-Chiung Hsieh^1,*, Chun-An Chen¹, Wei-Hsin Huang²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072514 - 12 January 2026

Abstract Container transportation is pivotal in global trade due to its efficiency, safety, and cost-effectiveness. However, structural defects—particularly in grapple slots—can result in cargo damage, financial loss, and elevated safety risks, including container drops during lifting operations. Timely and accurate inspection before and after transit is therefore essential. Traditional inspection methods rely heavily on manual observation of internal and external surfaces, which are time-consuming, resource-intensive, and prone to subjective errors. Container roofs pose additional challenges due to limited visibility, while grapple slots are especially vulnerable to wear from frequent use. This study proposes a two-stage automated… More >

Xin Ma^1,2, Jin Lei^3,4,*, Chenying Pei⁴, Chunming Wu⁴

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-17, 2026, DOI:10.32604/cmc.2025.069353 - 09 December 2025

Abstract This study proposes a lightweight apple detection method employing cascaded knowledge distillation (KD) to address the critical challenges of excessive parameters and high deployment costs in existing models. We introduce a Lightweight Feature Pyramid Network (LFPN) integrated with Lightweight Downsampling Convolutions (LDConv) to substantially reduce model complexity without compromising accuracy. A Lightweight Multi-channel Attention (LMCA) mechanism is incorporated between the backbone and neck networks to effectively suppress complex background interference in orchard environments. Furthermore, model size is compressed via Group_Slim channel pruning combined with a cascaded distillation strategy. Experimental results demonstrate that the proposed model More >

Oleh Koshovyi^1,2,*, Janne Sepp¹, Valdas Jakštas³, Vaidotas Žvikas³, Karina Tolmacheva⁴, Igor Kireyev⁴, Jyrki Heinämäki¹, Ain Raal^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.11, pp. 2909-2925, 2024, DOI:10.32604/phyton.2024.056536 - 30 November 2024

Abstract Pineappleweed (Matricaria discoidea DC., Asteraceae) herb is an essential oil containing raw material with spasmolytic and anti-inflammatory activity. It is also rich in phenolics, which may be used in pharmaceutical practice. This study aimed to investigate the phenolic and amino acid composition and the hyporific and analgesic effects of the M. discoidea aqueous-ethanolic extract and its amino acid modifications. In addition, we developed a polyethylene oxide gel formulation with M. discoidea extracts for the 3D-printed oral solid dosage preparations. In M. discoidea extracts, 16 phenolic substances and 14 amino acids were established. The extract and its amino acid preparations More >

Heru Suryanto^1,2,*, Daimon Syukri³, Fredy Kurniawan⁴, Uun Yanuhar⁵, Joseph Selvi Binoj⁶, Sahrul Efendi², Fajar Nusantara², Jibril Maulana⁷, Nico Rahman Caesar⁵, Komarudin Komarudin²

Journal of Renewable Materials, Vol.12, No.9, pp. 1605-1624, 2024, DOI:10.32604/jrm.2024.054047 - 25 September 2024

Abstract Utilizing biomass waste as a potential resource for cellulose production holds promise in mitigating environmental consequences. The current study aims to utilize pineapple biowaste extract in producing bacterial cellulose acetate-based membranes with magnetic nanoparticles (Fe₃O₄ nanoparticles) through the fermentation and esterification process and explore its characteristics. The bacterial cellulose fibrillation used a high-pressure homogenization procedure, and membranes were developed incorporating 0.25, 0.50, 0.75, and 1.0 wt.% of Fe₃O₄ nanoparticles as magnetic nanoparticle for functionalization. The membrane characteristics were measured in terms of Scanning Electron Microscope, X-ray diffraction, Fourier Transform Infrared, Vibrating Sample Magnetometer, antibacterial activity, bacterial… More > Graphic Abstract

Samra Rehman¹, Muhammad Attique Khan¹, Majed Alhaisoni², Ammar Armghan³, Usman Tariq⁴, Fayadh Alenezi³, Ye Jin Kim⁵, Byoungchol Chang^6,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 697-714, 2023, DOI:10.32604/cmc.2023.035183 - 06 February 2023

Abstract Identifying fruit disease manually is time-consuming, expert-required, and expensive; thus, a computer-based automated system is widely required. Fruit diseases affect not only the quality but also the quantity. As a result, it is possible to detect the disease early on and cure the fruits using computer-based techniques. However, computer-based methods face several challenges, including low contrast, a lack of dataset for training a model, and inappropriate feature extraction for final classification. In this paper, we proposed an automated framework for detecting apple fruit leaf diseases using CNN and a hybrid optimization algorithm. Data augmentation is… More >

Mazen Mushabab Alqahtani¹, Ashit Kumar Dutta², Sultan Almotairi³, M. Ilayaraja⁴, Amani Abdulrahman Albraikan⁵, Fahd N. Al-Wesabi^6,7,*, Mesfer Al Duhayyim⁸

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 217-233, 2023, DOI:10.32604/cmc.2023.025280 - 22 September 2022

Abstract Recent developments in digital cameras and electronic gadgets coupled with Machine Learning (ML) and Deep Learning (DL)-based automated apple leaf disease detection models are commonly employed as reasonable alternatives to traditional visual inspection models. In this background, the current paper devises an Effective Sailfish Optimizer with EfficientNet-based Apple Leaf disease detection (ESFO-EALD) model. The goal of the proposed ESFO-EALD technique is to identify the occurrence of plant leaf diseases automatically. In this scenario, Median Filtering (MF) approach is utilized to boost the quality of apple plant leaf images. Moreover, SFO with Kapur's entropy-based segmentation technique More >

Mengyao Yan¹, Xianqi Zeng¹, Banghui Zhang¹, Hui Zhang², Di Tan¹, Binghua Cai¹, Shenchun Qu¹, Sanhong Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.1, pp. 193-208, 2023, DOI:10.32604/phyton.2022.023078 - 06 September 2022

Abstract The effect of soil nutrient content on fruit yield and fruit quality is very important. To explore the effect of soil nutrients on apple quality we investigated 200 fruit samples from 40 orchards in Feng County, Jiangsu Province. Soil mineral elements and fruit quality were measured. The effect of soil nutrient content on fruit quality was analyzed by artificial neural network (ANN) model. The results showed that the prediction accuracy was highest (R²= 0.851, 0.847, 0.885, 0.678 and 0.746) in mass per fruit (MPF), hardness (HB), soluble solids concentrations (SSC), titratable acid concentration (TA) and solid-acid ratio More >

Helong Yu, Xianhe Cheng, Ziqing Li, Qi Cai, Chunguang Bi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 711-738, 2022, DOI:10.32604/cmes.2022.020263 - 27 June 2022

Abstract To solve the problem of difficulty in identifying apple diseases in the natural environment and the low application rate of deep learning recognition networks, a lightweight ResNet (LW-ResNet) model for apple disease recognition is proposed. Based on the deep residual network (ResNet18), the multi-scale feature extraction layer is constructed by group convolution to realize the compression model and improve the extraction ability of different sizes of lesion features. By improving the identity mapping structure to reduce information loss. By introducing the efficient channel attention module (ECANet) to suppress noise from a complex background. The experimental… More >

Heru Suryanto^1,2,*, Bili Darnanto Susilo³, Jibril Maulana³, Aminnudin³, Uun Yanuhar⁴, Surjani Wonorahardjo^2,5, Husni Wahyu Wijaya^2,5, Abu Saad Ansari⁶

Journal of Renewable Materials, Vol.10, No.9, pp. 2455-2465, 2022, DOI:10.32604/jrm.2022.020478 - 30 May 2022

Abstract Waste is the main problem for the environment. Handling waste for various useful applications has a benefit for the future. This work has been studied for handling pineapple peel waste to make composite film bacterial cellulose nanocomposite membrane (BCNM) with addition graphite nanoplatelet (GNP). The concentration of GNP in the membrane influence the membrane properties. The bacterial cellulose (BC) pellicle was synthesized by using media from pineapple peel waste extract. BC pellicle is cleaned with water and NaOH solution to be free from impactors. BCNM is synthesized through the mechanical disintegration stage. The results of… More > Graphic Abstract

Piyush Kumar Gupta¹, D. Karthik Kumar², M. Thaveena³, Soumya Pandit¹, Somya Sinha⁴, R. Ranjithkumar^2,* , Walaa F. Alsanie⁵, Vijay Kumar Thakur^6,7,8,*

Journal of Renewable Materials, Vol.10, No.12, pp. 3093-3105, 2022, DOI:10.32604/jrm.2022.019335 - 30 May 2022

Abstract Custard apple is a dry land fruit. Its leaves exhibit different pharmacological activities. In the present study, both silver (Ag) nanoparticles and chitosan-coated Ag (Chi-Ag) nanoparticles were fabricated using the aqueous leaf extract of the custard apple plant. During preliminary phytochemical analysis, various types of phytocompounds were found in the aqueous leaf extract of the same plant. Next, both nanoparticles were physiochemically characterized. FTIR analysis exhibited the fingerprint vibrational peaks of active bioactive compounds in plant extract, Ag nanoparticles, and Chi-Ag nanoparticles. UV/Visible spectral analysis revealed the highest absorbance peak at 419 nm, indicating the More > Graphic Abstract