Plant Disease Prognosis Using Spatial-Exploitation-Based Deep-Learning Models by Jayavani Vankara, Sekharamahanti S. Nandini, Murali Krishna Muddada, N. Satya Chitra Kuppili, K Sowjanya Naidu

“…Several techniques and technologies have been developed to aid in the diagnosis, management, and eventual eradication of plant diseases. The efficient and accurate identification of plant diseases could be aided by the development of a quick and accurate model. …”
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Green Chemistry Method for Analyzing Bisphenol A in Milk by Angela M. Encerrado Manriquez, Wen-Yee Lee

“…It is critical to have an effective and efficient process for monitoring the presence of BPA in milk to protect children’s health. …”
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A Conceptual Framework for a Latest Information-Maintaining Method Using Retrieval-Augmented Generation and a Large Language Model in Smart Manufacturing: Theoretical Approach and... by Hangseo Choi, Jongpil Jeong

“…In the modern manufacturing environment, the ability to collect and refine data in real time to deliver high-quality data is increasingly important in maintaining a competitive advantage and operational efficiency. …”
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Object Re-Identification Based on Federated Incremental Subgradient Proximal Optimization by Li Kang, Chuanghong Zhao, Jianjun Huang

“…FedISP effectively alleviates weight divergence and low communication efficiency issues through incremental sub-gradient proximal methods and ring topology, ensuring stable model convergence and efficient communication. …”
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Proof of storage with corruption identification and recovery for dynamic group users by Tao JIANG, Hang XU, Liangmin WANG, Jianfeng MA

“…The outsourced storage mode of cloud computing leads to the separation of data ownership and management rights of data owners, which changes the data storage network model and security model.To effectively deal with the software and hardware failures of the cloud server and the potential dishonest service provider and also ensure the availability of the data owners’ data, the design of secure and efficient data availability and recoverability auditing scheme has both theoretical and practical importance in solving the concern of users and ensuring the security of cloud data.However, most of the existing studies were designed for the security and efficiency of data integrity or recoverability schemes, without considering the fast identification and reliable recovery of damaged data under dynamic group users.Thus, to quickly identify and recover damaged data, a publicly verifiable proof of storage scheme was proposed for dynamic group cloud users.The designed scheme enabled a trusted third-party auditor to efficiently identify the damaged files through a challenge-response protocol and allowed the cloud storage server to effectively recover them when the degree of data damage is less than an error correction ability threshold.The scheme combined association calculation and accumulation calculation, which effectively reduced the number of calculations for the identification of damaged data.By combining erasure coding and shared coding technology, the scheme achieved effective recovery of damaged data of dynamic group users.At the same time, the scheme also supported dynamic user revocation, which ensured the integrity audit and reliable recovery of the collective data after user revocation.The network model and threat model of the designed scheme were defined and the security of the scheme under the corresponding security model was proved.Through the prototype implementation of the scheme in the real environment and the modular performance analysis, it is proved that the proposed scheme can effectively identify the damaged data and reliably recover the cloud data when the data is damaged.Besides, compared with other schemes, it is also proved that the proposed scheme has less computational overhead in identifying and recovering damaged data.…”
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Development of 6D Electromagnetic Actuation for Micro/Nanorobots in High Viscosity Fluids for Drug Delivery by Maki K. Habib, Mostafa Abdelaziz

“…The primary objective is to overcome limitations in the actuation efficiency, trajectory stability, and accurate path-tracking of MNRs. …”
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Hybrid Models for Forecasting Allocative Localization Error in Wireless Sensor Networks by Guo Li, Hongyu Sheng

“…The results indicate that the proposed hybrid models significantly improve the prediction of ALE, leading to more efficient node deployment and better network management. …”
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Applications of Industry 4.0 Technologies in Warehouse Management: A Systematic Literature Review by Lihle N. Tikwayo, Tebello N. D. Mathaba

“…<i>Results:</i> Improved process efficiency, the availability of real-time data, added competitive advantage and the ability to integrate business activities digitally are the top four most important benefits of implementing Industry 4.0 technologies and decision support systems in warehouse management. …”
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Spatial and Channel Attention Integration with Separable Squeeze-and-Excitation Networks for Image Classifications by Nazmul Shahadat, Shleshma Regmi, Anup Rijal

“…By decoupling spatial and channel attention modules, our model achieves efficient computation and alleviates overfitting. Furthermore, we introduce a novel separable strategy in the SE block, enabling effective feature re-calibration across space with reduced computational cost. …”
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Skin-adaptive nanofiber-based adhesive electronics with octopus-like 3D suction cups for enhanced transdermal delivery by Minwoo Song, Hyoung-Ki Park, Minjin Kim, Gui Won Hwang, Jihun Son, Gyun Ro Kang, Jihyun Lee, Changhyun Pang

“…To further enhance the TDD efficiency, we integrated a conductive layer into the CNFs-OIA. …”
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A Lightweight Dual-Branch Complex-Valued Neural Network for Automatic Modulation Classification of Communication Signals by Zhaojing Xu, Youchen Fan, Shengliang Fang, You Fu, Liu Yi

“…Additionally, LDCVNN achieves a better balance between efficiency and performance across other datasets.…”
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Deep Learning-Based Performance Prediction of Electric Submersible Pumps Under Viscous and Gas–Liquid Flow Conditions by Haiwen Zhu, Hong Yu, Qiang Sun, Qiuchen Wang, Haorong Jing, Rakhymzhan Abdikadyrov

“…The findings demonstrate the advantages of machine learning over traditional methods, including an enhanced prediction accuracy, practical guidelines for efficient parameter tuning, and the ability to address incomplete pump curve data. …”
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Intelligent Robot in Unknown Environments: Walk Path Using Q-Learning and Deep Q-Learning by Mouna El Wafi, My Abdelkader Youssefi, Rachid Dakir, Mohamed Bakir

“…Autonomous navigation is essential for mobile robots to efficiently operate in complex environments. This study investigates Q-learning and Deep Q-learning to improve navigation performance. …”
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MRP-YOLO: An Improved YOLOv8 Algorithm for Steel Surface Defects by Shuxian Zhu, Yajie Zhou

“…Secondly, the design of Dynamic Conv and C2f-OREPA enables the model to efficiently reduce the demand for computational resources while maintaining high performance. …”
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TAX AND DEBT STRATEGY OF FISCAL REGULATION OF THE TRANSITIVE ECONOMY by V. K. Giraev

“…Social expenditures, which are not secured by tax revenues and/or state borrowing, definitely needs to be reviewed in accordance with criteria of fiscal adequacy, economic efficiency, and social justice.…”
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Optimal Selection of Extensively Used Non-Isolated DC–DC Converters for Solar PV Applications: A Review by Khan Mohammad, M. Saad Bin Arif, Muhammad I. Masud, Mohd Faraz Ahmad, Mohammed Alqarni

“…However, it faces challenges due to its inherently low output voltage and non-linear characteristics, which limit its efficiency and performance. These limitations necessitate the use of DC–DC converters to optimize voltage levels and ensure efficient energy transfer, making them a crucial component in PV systems. …”
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FODIT: A Filter-Based Module for Optimizing Data Storage in B5G IoT Environments by Bruno Ramos-Cruz, Francisco J. Quesada-Real, Javier Andreu-Pérez, Jessica Zaqueros-Martinez

“…FODIT leverages probabilistic data structures, specifically filters, to improve storage efficiency and query performance. We hypothesize that applying these structures can significantly reduce redundancy and accelerate data access in resource-constrained IoT deployments. …”
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Robust optimization for smart demand side management in microgrids using robotic process automation and grey wolf optimization by Bin Chen, Zeke Li, Bijing Liu, Haiwei Fan, Qiutian Zhong

“…These findings underscore the framework’s ability to adapt to diverse stakeholder objectives and highlight its potential to revolutionize demand-side energy management, fostering efficient and sustainable microgrid operations.…”
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J-Aggregates of Amphiphilic Cyanine Dyes for Dye-Sensitized Solar Cells: A Combination between Computational Chemistry and Experimental Device Physics by M. S. A. Abdel-Mottaleb, Mohamed M. S. Abdel-Mottaleb, Hoda S. Hafez, Mona Saif

“…These aggregates are known to exhibit outstanding optical properties of J-aggregates, namely, efficient exciton coupling and fast exciton energy migration, which are essential for building up artificial light harvesting to the photovoltaic device. …”
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Predicting the Performance of Students Using Deep Ensemble Learning by Bo Tang, Senlin Li, Changhua Zhao

“…Universities and schools rely heavily on the ability to forecast student performance, as it enables them to develop efficient strategies for enhancing academic results and averting student attrition. …”
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