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Deep Learning-Based Trees Disease Recognition and Classification Using Hyperspectral Data

computers, Materials & Continua 2023年第10期77卷 681-697页

作者： Uzair Aslam Bhatti Sibghat Ullah Bazai Shumaila Hussain Shariqa Fakhar Chin Soon Ku Shah Marjan Por Lip Yee Liu Jing College of Information and Communication Engineering Hainan UniversityHaikou570228China Department of Computer Engineering Balochistan University of Information TechnologyEngineeringand Management Sciences(BUITEMS)QuettaPakistan Department of Computer Science Sardar Bahadur Khan Women’s UniversityQuettaPakistan Department of Computer Science Universiti Tunku Abdul RahmanKampar31900Malaysia Department of Software Engineering Balochistan University of Information TechnologyEngineeringand Management Sciences(BUITEMS)QuettaPakistan Faculty of Computer Science and Information Technology University of MalayaKuala Lumpur50603Malaysia

Crop diseases have a significant impact on plant growth and can lead to reduced *** methods of disease detection rely on the expertise of plant protection experts,which can be subjective and dependent on individual experience and *** address this,the use of digital image recognition technology and deep learning algorithms has emerged as a promising approach for automating plant disease *** this paper,we propose a novel approach that utilizes a convolutional neural network(CNN)model in conjunction with Inception v3 to identify plant leaf *** research focuses on developing a mobile application that leverages this mechanism to identify diseases in plants and provide recommendations for overcoming specific *** models were trained using a dataset consisting of 80,848 images representing 21 different plant leaves categorized into 60 distinct *** rigorous training and evaluation,the proposed system achieved an impressive accuracy rate of 99%.This mobile application serves as a convenient and valuable advisory tool,providing early detection and guidance in real agricultural *** significance of this research lies in its potential to revolutionize plant disease detection and management *** automating the identification process through deep learning algorithms,the proposed system eliminates the subjective nature of expert-based diagnosis and reduces dependence on individual *** integration of mobile technology further enhances accessibility and enables farmers and agricultural practitioners to swiftly and accurately identify diseases in their crops.

关键词： Plant disease Inception v3 CNN crop diseases

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Assessment of ingestion dose from 226Ra, 228Ra, and 40K in vegetables consumed in Koya district, Iraq

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Environmental science and Pollution Research 2025年第19期32卷 11972-11980页

作者： Saleh, Dedawan Salam Salh, Hemn Smail, Jahfer Majeed Ahmad, Saddon Taha Department of Physics Faculty of Science and Health Koya University Kurdistan Region KoyaKOY45 Iraq Department of Computer Engineering College of Engineering Knowledge University Erbil44001 Iraq Faculty of Medicine Koya University KoyaKOY45 Iraq

The present work comprises the measurement of activity concentrations of three radionuclides, 22⁶Ra, 228Ra, and 4⁰K in 33 species of vegetables commonly used in Koya district, the Iraqi Kurdistan region. The analysis of the samples was performed with high purity germanium (HPGe) gamma spectrometry. Among the analyzed samples, mushrooms presented the highest activity concentrations of 22⁶Ra (3.34 ± 1.18 Bq·kg⁻1), 228Ra (1.24 ± 0.5 Bq·kg⁻1), and 4⁰K (1481.93 ± 14.46 Bq·kg⁻1) while legumes had the lowest levels of these radionuclides. The estimated annual effective dose from the consumption of these vegetables was computed to be 97.216 µSv·y⁻1 and this is much lower than the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) global reference level of 290 µSv·y⁻1. Therefore, it can be concluded that the radiological risk from the consumption of vegetables in this area is very low thus giving a reassurance to the people on the safety implication on the radiological health hazards. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Radiation effects

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A novel network intrusion detection method based on metaheuristic optimisation algorithms

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Journal of Ambient Intelligence and Humanized Computing 2023年第6期14卷 7575-7592页

作者： Ghanbarzadeh, Reza Hosseinalipour, Ali Ghaffari, Ali Faculty of Science and Engineering Southern Cross University Gold Coast Australia Department of Computer Engineering Heris Branch Islamic Azad University Heris Iran Department of Computer Engineering Tabriz Branch Islamic Azad University Tabriz Iran

The growing use of the Internet with its vulnerabilities has necessitated the adoption of Intrusion Detection Systems (IDS) to assure security. IDSs are protective systems that detect outsider infiltrations, unauthorised accesses and malfunctions occurring in computer networks. Intrusions can be detected and reported to the network administrator by IDSs using various pieces of information such as port scanning and irregular traffic detection. Intrusion detection is a classification problem, and identifying effective features is an essential aspect of classification methods. Standard methods used for classification are neural networks, fuzzy logic, data mining techniques and metaheuristics. One of the novel metaheuristic algorithms introduced to address optimisation problems is the Horse herd Optimisation Algorithm (HOA). This paper introduces a new approach on the basis of HOA for network intrusion detection. The new method uses horse behaviours in the herd to select effective features to detect intrusions and interactions between features. For the purpose of the new approach, HOA is first updated into a discrete algorithm using the floor function. The binarised algorithm is then converted into a quantum-inspired optimiser by integrating the concepts of quantum computing with HOA to improve the social behaviours of the horses in the herd. In quantum computing, Q-bit and Q-gate aid in striking a greater balance between the exploration and exploitation processes. The resulting algorithm is then converted into a multi-objective algorithm, where the objectives can be chosen from a set of optimal solutions. The new algorithm, MQBHOA, is then used for intrusion detection in computer networks, which is a multi-objective optimisation problem. For the classification, the K-Nearest Neighbour (KNN) classifier is applied. To evaluate the new algorithm’s performance, two data sets, NSL-KDD (Network Security Laboratory—Knowledge Discovery and Data Mining) and CSE-CIC-IDS2018, are

关键词： Feature Selection

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Implementation of Secure and Verifiable Access Control Procedures using the NTRU Cryptosystem to Store Big Data in the Cloud Environment

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Recent Patents on engineering 2025年第2期19卷 57-70页

作者： Babu B, Ravindra Saxena, Swati Widjaja, Gunawan Vinodha D, Vedha Omarov, Batyrkhan Ramaiah, Gurumurthy B. Vats, Prashant Adama Ethiopia Department of Computer Science KCG College of Technology Chennai India Universitas Krisnadwipayana Jawa Barat 13077 Indonesia Department of Electronics and Communication Engineering JCT College Of Engineering and Technology Pichanur Coimbatore India International University of Tourism and Hospitality Turkistan Kazakhstan Technical and Vocational Training Institute Addis Ababa Ethiopia Department of Computer Science and Engineering Faculty of Engineering and Technology SGT University Haryana Gurugram India

Background: Due to their complexity and size, deploying ciphertexts for clouds is considered the most useful approach to accessing large data stores. Methods: However, access to a user's access legitimacy and improving a decrypted text on the cloud depending on an improved access policy (AP) specified by the data owner are the key challenges for making large data storage realistic and effective in clouds. The traditional ways either totally remove the problem of AP development or offer renewal to arbiter power, but in real-time, enhancing the AP is essential to maximising security and handling agility. Results: In this patent paper, a safe and verifiable access control program characterised by the NTRU cryptographic system for large storage of data in the clouds is proposed. Primarily, an improved NTRU decryption protocol to deal with the decryption failures of the prime NTRU is established, and in addition, the program is analysed for its security strength and computational performance. When a new AP is specified by the data owner, the cloud server allows the program to improve ciphertext and allows the owner to verify the upgrade to oppose the cloud's fraudulent behaviour. Conclusion: It enables (i) checking the user's legitimacy to access the data owner and qualified users, and (ii) allowing the user to verify the data provided by other users for the recovery of the right user. Strong analysis can prevent and block delinquency from various attacks, namely the collusion attack that could potentially target fraud users. © 2025 Bentham science Publishers.

关键词： Cloud security

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Proposed 3D chaos-based medical image cryptosystem for secure cloud-IoMT eHealth communication services

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Journal of Ambient Intelligence and Humanized Computing 2024年第1期15卷 1-28页

作者： El-Shafai, Walid Khallaf, Fatma El-Rabaie, El-Sayed M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electrical Engineering Faculty of Engineering Ahram Canadian University Giza 6th October City Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Riyadh84428 Saudi Arabia

Medical image encryption is a mandatory process in various healthcare, Internet of Medical Things (IoMT) and cloud services. This paper provides a robust cryptosystem based on a 3D chaotic map for the medical image encryption in secure IoMT and cloud services. The proposed encryption method depends on a 3D chaotic map. With this map, a nonlinear ciphering process is implemented for pixel value diffusion and position permutation. Five operations are conducted in the suggested cryptosystem on the medical images to be transmitted in order to attain a high security level. These operations are 3D chaos generation, chaos histogram equalization, row rotation, column rotation, and XOR operation. To validate the suggested cryptosystem, different medical images with different characteristics are tested. Moreover, the suggested cryptosystem and more recent state-of-the-art security systems are discussed and analyzed in a comparative study. Different assessment parameters are adopted to assess the suggested cryptosystem, which reveals high security performance. The simulation outcomes show that the suggested cryptosystem is trustworthy. Furthermore, it offers high robustness levels and recommended security levels for utilization in healthcare, IoMT and cloud service applications. It is observed that the amount of average entropy obtained by the proposed 3D chaos cryptosystem is 7.95 which is very close to its best value of 8, and the average NPCR value is 99.62% which is also much close to its supreme value of 99.60%. In addition, all other results scored for the test evaluation parameters on the suggested cryptosystem are superior to those of the traditional security systems. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022.

关键词： Cryptography

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New exact solutions of the Mikhailov-Novikov-Wang equation via three novel techniques

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Journal of Ocean engineering and science 2023年第1期8卷 103-110页

作者： Arzu Akbulut Melike Kaplan Mohammed K.A.Kaabar Mathematics-Computer Department Art-Science FacultyEski¸s ehir Osmangazi UniversityEski¸s ehirTurkey Department of Computer Engineering Engineering and Architecture FacultyKastamonu UniversityKastamonuTurkey Institute of Mathematical Sciences Faculty of ScienceUniversity of MalayaKuala Lumpur 50603Malaysia

The current work aims to present abundant families of the exact solutions of Mikhailov-Novikov-Wang equation via three different *** adopted methods are generalized Kudryashov method(GKM),exponential rational function method(ERFM),and modified extended tanh-function method(METFM).Some plots of some presented new solutions are represented to exhibit wave *** results in this work are essential to understand the physical meaning and behavior of the investigated equation that sheds light on the importance of investigating various nonlinear wave phenomena in ocean engineering and *** equation provides new insights to understand the relationship between the integrability and water waves’phenomena.

关键词： Exact solutions Generalized Kudryashov method Modified extended tanh-function method Symbolic computation PDEs

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Banana Leaf Disease Detection using Advanced Convolutional Neural Network

Banana Leaf Disease Detection using Advanced Convolutional N...

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2023 International Conference on Sustainable Computing and Smart Systems, ICSCSS 2023

作者： Mohanraj, E. Hariharan, R. Keerthana, S. Cavin, K.B. Faculty of Computer Science and Engineering K S Rangasamy College of Technology Department of Computer Science and Engineering Tiruchengode India Computer Science and Engineering K S Rangasamy College of Technology Department of Computer Science and Engineering Tiruchengode India

ISBN: (纸本)9798350333602

Any plant's ability to grow disease-free is crucial for both the environment and human existence. Nevertheless, various diseases, viruses, and fungi affect the plant and highly influence the yield quality and production quantity. If the disease and its origin are not appropriately diagnosed, illness control procedures might be a waste of effort and resources, causing additional plant losses. Plant disease tracking by manual process is quite challenging. It requires a considerable amount of work, expertise in plant diseases, and protracted processing durations. Traditional neural networks require a large number of parameters to train effectively, which can make them slow and computationally expensive. The previous study includes the leaf disease detection performed by CNN, R-CNN, and SVM models. Using the Faster R-CNN, which outperforms other models in terms of computation time and accuracy, this study intends to develop a banana leaf disease detection system. © 2023 IEEE.

关键词： Object detection

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Automatic Timbre Transformation using Enhanced Diffusion Model

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IEEE Access 2025年 13卷 91642-91654页

作者： Wu, Cheng-Han Cheewaprakobkit, Pimpa Shih, Timothy K. Lin, Yu-Cheng Liu, Bing-Ze National Central University Department of Computer Science and Information Engineering Taoyuan City32001 Taiwan Asia Pacific International University Faculty of Information Technology Saraburi18180 Thailand Yuan-Ze University Department of Computer Science and Engineering Taoyuan City32003 Taiwan

We present a novel timbre transfer model that uses an enhanced diffusion architecture to convert music from various instruments into Erhu timbre. The Erhu, a traditional Chinese instrument, is difficult to simulate due to its rich vibrato and smooth note transitions. Existing Musical Instrument Digital Interface systems struggle to capture its nuanced dynamics. Our model integrates a Pitch Encoder, a Loudness Encoder, and a Diffusion Decoder. The encoders extract pitch features and dynamic loudness variations, guiding the decoder in generating realistic Erhu timbre. By extracting general musical features, the system generalizes to unseen input types without retraining. Evaluations based on pitch accuracy, cosine similarity, and Fréchet Audio Distance show that our model achieves 96% pitch accuracy and high fidelity in Erhu timbre reproduction. This study demonstrates the potential of diffusion-based timbre transfer models in music generation and provides new directions for future work on both music generation and timbre transfer. © 2013 IEEE.

关键词： Deep learning

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Effect of Graphite Addition on Microstructure, Mechanical Properties and Thermal Properties of Injection Molded AZ91D Alloy+1

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Materials Transactions 2024年第4期65卷 374-380页

作者： Hideshima, Yasutoshi Maeda, Fumiya Fukuta, Tadao Ozaki, Koichi Course of Advanced Systems Engineering Graduate School of Computer Science and Systems Engineering Okayama Prefectural University Soja719-1197 Japan Process Technology Development Department Technology Development Division Seiko Epson Corp. Suwa399-0211 Japan Department of Systems Engineering Faculty of Computer Science and Systems Engineering Okayama Prefectural University Soja719-1197 Japan

Magnesium chips were coated with a high concentration of graphite using a binder and were used as the raw material for injection molding. The microstructure of the magnesium injection-molded product with added graphite exhibited a dispersion of needle-like graphite particles. No significant voids were observed at the interfaces between the graphite and the matrix. The addition of more than 0.5 mass% graphite decreased the proof stress and tensile strength of the injection-molded products. The Young’s modulus of the graphite-added products tended to decrease with an increase in the graphite content, which is consistent with the lower limit of the rule of mixtures. The thermal conductivity of the 6.9 mass% graphite-added product increased compared with that of the AZ91D magnesium alloy and the coefficient of linear thermal expansion decreased. Both values are within a range that satisfied the rules of mixtures. © 2024 The Japan Institute of Metals and Materials.

关键词： Thermal expansion

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Bi_(2)O_(2)Se nanoplates for broadband photodetector and full-color imaging applications

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Nano Research 2023年第5期16卷 7638-7645页

作者： Han Wang Songqing Zhang Xingxuan Wu Huijia Luo Junliang Liu Zesheng Mu Ruirui Liu Guang Yuan Yujun Liang Jin Tan Yongling Ren Wen Lei Department of Electrical Electronic and Computer EngineeringThe University of Western AustraliaCrawley 6009Australia Department of Electronic Engineering School of IOT engineeringJiangnan UniversityWuxi 214122China College of Information Science and Engineering Ocean University of ChinaQingdao 266100China Faculty of Materials Science and Chemistry China University of GeosciencesWuhan 430074China

Broadband light detection and sensing are widely applied in modern *** a promising candidate for next-generation two-dimensional(2D)optoelectronic material,bismuth oxyselenide(Bi_(2)O_(2)Se)nanoplates exhibit many prospects in the application of visible light detection due to their peculiar *** this work,we report the photodetection performance of single-crystal 2D Bi_(2)O_(2)Se nanoplates grown on SiO_(2)based on a ternary-alloy growth model by utilizing chemical vapor deposition(CVD).The Bi_(2)O_(2)Se nanoplates were found to have an even and uniform square shape with side lengths up to 15μm and an approximate thickness of 15 nm.A visible-light photodetector was fabricated based on a CVD-grown Bi_(2)O_(2)Se nanoplate,and characterized by a set of illumination experiments using a 400 nm laser at temperatures ranging from 77 to 370 *** device exhibited superior performance at the temperature of 77 K,with a responsivity of 523 A/W,a specific detectivity of 1.37×10^(11)Jones,a response time of 0.2175 ms,an external quantum efficiency of 162,119.44%,resulting in high-quality and fullcolor imaging in the visible *** results indicate that the single-crystalline Bi_(2)O_(2)Se nanoplates have excellent potential in broadband photodetection and non-cryogenic imaging.

关键词： two-dimensional(2D)nanomaterial Bi_(2)O_(2)Se nanoplates chemical vapor deposition broadband light detection full-color imaging

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