Visual explanation method for reversible neural networks by Xinying MU, Bingbing SONG, Fanxiao LI, Yisen ZHENG, Wei ZHOU, Yunyun DONG

“…The issue of model explainability has gained significant attention in understanding the vulnerabilities and anonymous decision-making processes inherent in deep neural networks (DNN).While there has been considerable research on explainability for traditional DNN, there is a lack of exploration on the operation mechanism and explainability of reversible neural networks (RevNN).Additionally, the existing explanation methods for traditional DNN are not suitable for RevNN and suffer from issues such as excessive noise and gradient saturation.To address these limitations, a visual explanation method called visual explanation method for reversible neural network (VERN) was proposed for RevNN.VERN leverages the reversible property of RevNN and is based on the class-activation mapping mechanism.The correspondence between the feature map and the input image was explored by VERN, allowing for the mapping of classification weights of regional feature maps to the corresponding regions of the input image.The importance of each region for model decision-making was revealed through this process, which generates a basis for model decision-making.Experimental comparisons with other explanation methods on generalized datasets demonstrate that VERN achieves a more focused visual effect, surpassing suboptimal methods with up to 7.80% improvement in average drop (AD) metrics and up to 6.05% improvement in average increase (AI) metrics in recognition tasks.VERN also exhibits an 82.00% level of localization for the maximum point of the heat value.Furthermore, VERN can be applied to explain traditional DNN and exhibits good scalability, improving the performance of other methods in explaining RevNN.Furthermore, through adversarial attack analysis experiments, it is observed that adversarial attacks alter the decision basis of the model.This is reflected in the misalignment of the model’s attention regions, thereby aiding in the exploration of the operation mechanism of adversarial attacks.…”
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Adaptive Spatial Lattice Manufacturing (ASLM): A novel approach to efficient lattice structure production by Justin Dirrenberger, Pierre Lapouge, Rachel Azulay, Peter Evers, Tom Vroemen

“…Unlike traditional additive manufacturing techniques, ASLM corresponds to a direct assembly of solid rods, by welding, offering remarkable benefits in energy efficiency, dimensional accuracy, and scalability. This paper introduces the ASLM process, detailing its computational design principles, build mechanics, and material compatibility using AISI 316L stainless steel. …”
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Single-step retrosynthesis prediction via multitask graph representation learning by Peng-Cheng Zhao, Xue-Xin Wei, Qiong Wang, Qi-Hao Wang, Jia-Ning Li, Jie Shang, Cheng Lu, Jian-Yu Shi

“…Then, its robustness and scalability and the contributions of its crucial components are validated. …”
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Enhancing Real-Time Processing in Industry 4.0 Through the Paradigm of Edge Computing by Nerea Gómez Larrakoetxea, Borja Sánz Uquijo, Iker Pastor López, Jon García Barruetabeña, Pablo García Bringas

“…By subdividing datasets into smaller, specialized edge models, this study offers a viable approach to mitigating the latency challenges inherent in cloud computing, thereby enhancing real-time data processing capabilities, scalability, and adaptability for modern industrial applications.…”
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Enhancing unity-based AR with optimal lossless compression for digital twin assets. by Mohammed Hlayel, Hairulnizam Mahdin, Mohammad Hayajneh, Saleh H AlDaajeh, Siti Salwani Yaacob, Mazidah Mat Rejab

“…This study will deliver practical guidance on optimal compression method selection to improve user experience and scalability for AR digital twin implementations.…”
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Optimizing precision farming: enhancing machine learning efficiency with robust regression techniques in high-dimensional data by Nour Hamad Abu Afouna, Majid Khan Majahar Ali

“…To overcome these obstacles, reducing retraining time and resolving the complexity issue is essential for improving the machine learning algorithm’s performance, scalability, and efficiency, especially when dealing with large or high-dimensional datasets. …”
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Quantum-Inspired Multi-Scale Object Detection in UAV Imagery: Advancing Ultra-Small Object Accuracy and Efficiency for Real-Time Applications by Muhammad Muzammul, Muhammad Assam, Ayman Qahmash

“…It also establishes a foundation for future advancements, including scalability to diverse datasets, integration with edge computing platforms, and the exploration of quantum computing techniques. …”
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Hydrogel-based nanoparticles: revolutionizing brain tumor treatment and paving the way for future innovations by Alireza Shadab, Simin Farokhi, Arshia Fakouri, Neda Mohagheghzadeh, Ali Noroozi, Zahra Sadat Razavi, Arian Karimi Rouzbahani, Hamidreza Zalpoor, Mohamad Mahjoor

“…The study also addresses the need for enhanced synthesis techniques, stability, scalability, and cost-cutting measures to overcome obstacles and advance the clinical use of hydrogel-based nanoparticles in treating brain tumors. …”
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Economic control of next generation aerospace fleets by Felipe Montana, Will Jacobs, Evangelia Pontika, Panagiotis Laskaridis, Matthew Griffiths, Peter Beecroft, Derek Wall, Visakan Kadirkamanathan, Andrew R Mills

“…Challenges introduced by considering multiple assets include the construction of economic multi-objective optimization criteria, handling rare events such as failures, application of fleet-level constraints, and scalability. The proposed solution presents a framework for economic fleet optimization. …”
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Comparative analysis of cryopreserved adipose stem cells expanded in hollow fiber bioreactor versus conventional tissue culture flasks by Guoqiang Ren, Morten Brøndum Sørensen, Simone Riis Porsborg, Trine Fink, Vladimir Zachar, Qiuyue Peng

“…However, the choice between tissue culture polystyrene (TCP) and hollow fiber system (HFB) system for adipose-derived stem cell (ASC) production remains a critical decision, with implications for scalability, reproducibility, and the clinical efficacy. …”
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The control strategy for distributed energy storage devices using fully diffusion strategy by Zejian Liu, Ping Yang, Xu Lin, Ziwei Fan, Cencen Hong

“…Compared with centralized control, the proposed method contributes to a higher scalability and reliability. Diffusion strategy allows adjacent nodes to diffuse and cooperate information in real-time, and it includes a stochastic gradient term. …”
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An Adaptive Intrusion Detection System for Evolving IoT Threats: An Autoencoder-FNN Fusion by J. Jasmine Shirley, M. Priya

“…The AE-FNN model’s high accuracy, robustness, and scalability position it as a valuable tool in securing interconnected IoT ecosystems, making it an important advancement in network security.…”
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Integrating Knowledge Graphs with Symbolic AI: The Path to Interpretable Hybrid AI Systems in Medicine by Maria-Esther Vidal, Yashrajsinh Chudasama, Hao Huang, Disha Purohit, Maria Torrente

“…This position paper examines the challenges and research opportunities in integrating KGs with neuro-symbolic AI, highlighting their potential to enhance explainability, scalability, and context-aware reasoning in hybrid AI systems. …”
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Anomaly detection solutions: The dynamic loss approach in VAE for manufacturing and IoT environment by Praveen Vijai, Bagavathi Sivakumar P

“…While traditional anomaly detection approaches face limitations such as scalability issues, high false alarm rates, and reliance on skilled expertise, this study proposes a novel approach using a BiLSTM-Variational Autoencoder (BiLSTM-VAE) model with a dynamic loss function. …”
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Replication-Based Query Management for Resource Allocation Using Hadoop and MapReduce over Big Data by Ankit Kumar, Neeraj Varshney, Surbhi Bhatiya, Kamred Udham Singh

“…The technique allows for capabilities to inform a massive database of information, from storage and indexing techniques to the distribution of queries, scalability, and performance in heterogeneous environments. …”
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Constructing immersive toy trial experience in mobile augmented reality by Lingxin Yu, Jiacheng Zhang, Xinyue Wang, Siru Chen, Xuehao Qin, Zhifei Ding, Jiahao Han

“…In terms of methodology, we have specifically designed an expandable collection of toy images, allowing the recognition of recently introduced toys by adding them to the database, enhancing the scalability of our application. In comparison to previous research, our work transcends the constraints of traditional toy shopping, providing a more intuitive, interactive, and personalized experience through AR technology.…”
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Feature Selection with Graph Mining Technology by Thosini Bamunu Mudiyanselage, Yanqing Zhang

“…A critical data preprocessing problem is feature selection, whereby its non-scalability negatively influences both the efficiency and performance of big data applications. …”
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Ferroelectric memory: state-of-the-art manufacturing and research by D. A. Abdullaev, R. A. Milovanov, R. L. Volkov, N. I. Borgardt, A. N. Lantsev, K. A. Vorotilov, A. S. Sigov

“…Semiconductor industry calls for emerging memory, demonstrating high speed (like SRAM or DRAM), nonvolatility (like Flash NAND), high endurance and density, good scalability, reduced energy consumption and reasonable cost. …”
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A proximal policy optimization based deep reinforcement learning framework for tracking control of a flexible robotic manipulator by Joshi Kumar V, Vinodh Kumar Elumalai

“…Moreover, the major limitation of the existing policy gradient based DRL techniques is that they are computationally expensive and suffer from scalability issues for complex higher order systems. …”
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A Modified Implementation of Tristate Inverter Based Static Master-Slave Flip-Flop with Improved Power-Delay-Area Product by Kunwar Singh, Satish Chandra Tiwari, Maneesha Gupta

“…Simulations were also performed at 130 nm, 90 nm, and 65 nm to reveal the scalability of both the designs at modern process nodes.…”
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