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DrugBlock: An Advanced System to Secure Drug Supply Chain Using Internet of Things and Blockchain-Enabled Consumer Electronics

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IEEE Transactions on Consumer Electronics 2024年

作者： Namasudra, Suyel Das, Sangjukta Crespo, Ruben Gonzalez Taniar, David Moparthi, Nageswara Rao National Institute of Technology Agartala Department of Computer Science and Engineering Tripura India Bennett University School of Computer Science Engineering and Technology Uttar Pradesh India Universidad Internacional de la Rioja Logroño Spain Monash University Faculty of Information Technology Australia Amaravati Campus Amrita School of Computing Amrita Vishwa Vidyapeetham Andhra Pradesh India

The growing consumer interest in product quality and originality has made the drug supply chain management system complex and critical. Moreover, fraudulent activities, such as drug contamination, have become global issues in the drug supply chain. Traditional centralized systems struggle to maintain transparency and traceability throughout the supply chain, often resulting in inefficiencies and vulnerabilities. Here, consumer electronics devices can be integrated with the ecosystem to extend the reach of the drug supply chain. In this paper, a solution for traditional drug supply chain systems is presented by using blockchain technology and Internet of Things (IoT) with a focus on consumer electronics. Here, blockchain supports to store drug records immutably, while keeping information transparent to all entities involved in the network. This proposed scheme is deployed over the Ethereum blockchain network and uses IoT technology to provide the key features of blockchain, such as drug traceability, security, and transparency. Here, smart contracts automate the entire process in the proposed supply chain network, and all the drug batch's transfer details are stored on the blockchain network. The security analysis and performance analysis of the proposed scheme are performed to evaluate the efficiency of the proposed scheme over some existing schemes. © 1975-2011 IEEE.

关键词： Smart contract

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FUNCTIONAL-LEVEL UNCERTAINTY QUANTIFICATION FOR CALIBRATED FINE-TUNING ON LLMS

arXiv

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arXiv 2024年

作者： Niu, Ruijia Wu, Dongxia Yu, Rose Ma, Yi-An Department of Computer Science and Engineering University of California San Diego La Jolla CA United States Halıcıoğlu Data Science Institute University of California San Diego La Jolla CA United States

Accurate uncertainty quantification of large language models (LLMs) provides credibility measure over their outputs. However, fine-tuned LLMs often struggle with overconfidence in uncertain predictions due to the limitations in the models’ ability to generalize with limited data. Existing parameter efficient fine-tuning (PEFT) uncertainty quantification methods for LLMs focus on post fine-tuning stage and fall short of calibrating epistemic uncertainty. To address these limitations, we propose Functional-Level Uncertainty Quantification for Calibrated Fine-Tuning (UQ4CT), which captures and calibrates epistemic uncertainty over the space of functions that map input prompts to outputs. We implement UQ4CT during the fine-tuning stage via a mixture-of-experts framework that hierarchically decomposes the functional space. We demonstrate that UQ4CT reduces Expected Calibration Error (ECE) by more than 25% while maintaining high accuracy across 5 benchmarks. Even under distribution shift, UQ4CT maintains superior ECE performance with high accuracy, showcasing improved generalizability. © 2024, CC BY.

关键词： Modeling languages

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Small Polaron-Induced Ultrafast Ferroelectric Restoration in BiFeO3

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Physical Review X 2025年第2期15卷 021046-021046页

作者： Wenfan Chen Tian Wang Chun-Chieh Yu Yuancheng Jing Xiaosong Li Wei Xiong Materials Science and Engineering Program University of California San Diego La Jolla California 92093 USA Department of Chemistry University of Washington Seattle Washington 98195 USA Department of Chemistry University of California San Diego La Jolla California 92093 USA Department of Electrical and Computer Science Engineering University of California San Diego La Jolla California 92093 USA

In this report, we apply a suite of ultrafast spectroscopic techniques and advanced calculations to reveal the interplay between electronic and lattice degrees of freedom in ferroelectric BiFeO3. Using transient sum frequency generation spectroscopy, which is sensitive to electronic polarizations, we observe a transient electronic dipole reduction upon optical excitation which recovers at 0.5 and 10 ps timescale. The time-dependent density functional theory calculation reveals that both ligand-metal charge transfer and local excitation transition occurred upon photo excitation. To reveal the nature of electronic dipole restoration, we employ transient extreme ultraviolet (EUV) spectroscopy—an element-specific ultrafast technique that follows charge dynamics of Bi, Fe, and O altogether. The transient EUV dynamics observed both ultrafast free charge carrier relaxation to excitons, as well as polaron formation. However, a timescale comparison suggests that only the polaron formation is responsible for the 0.5 ps electronic dipole restoration, whereas the faster electronic relaxation does not contribute to the ferroelectric property changes. Multireference configuration interaction calculation further corroborates this result by showing both Fe and Bi atoms shift from the ground state equilibrium—leading to the polaron formation. Our result disentangles the multidegrees of freedom in ultrafast ferroelectric modulation and identifies the pivotal motion—a local polaron formation—for the fast ferroelectric recovery. It provides crucial insights on the specific lattice distortion that could modulate properties or phase transitions of condensed matter materials.

关键词： Light polarization

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Discriminative Feature Learning Through Angular Margin-Based Softmax Losses for Breast Cancer Classification

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Biophysical Reviews and Letters 2024年第4期19卷 291-311页

作者： Pendar Alirezazadeh Fadi Dornaika Abdelmalik Moujahid Department of Informatics University of the Basque Country UPV/EHU Donostia-San Sebastian Spain IKERBASQUE Basque Foundation for Science Bilbao Spain Department of Computer Science and Technology High School of Engineering and Technology Universidad Internacional de la Rioja Logroño Spain

When many histopathological breast images with different magnification levels need to be analyzed, diagnosing benign or malignant cancer from the images can be time-consuming. Automatic classification of histopathological images of breast cancer can support the diagnostic workflow in pathology, reducing analysis time. Recently, convolutional neural networks (CNNs) have been used for more accurate classification of breast cancer histopathological images. CNNs typically highlight semantic information to extract discriminative features. However, the traditional softmax loss used by CNNs usually lacks sufficient discriminative power. To address this problem, several angular margin-based softmax loss functions have been proposed, including large Margin Softmax Loss (A-Softmax), large Margin Cosine Loss (CosFace), Additive Angular Margin Loss (ArcFace), and Linear ArcFace (Li-ArcFace). All of these improved losses are based on the same concept: maximizing inter-class variance while minimizing intra-class distance. This paper focuses on these four losses and their effectiveness in extracting discriminative features and creating decision margins between classes. Extensive experimental evaluations were conducted on a public and well-known histopathological breast cancer image dataset (BreakHis). Further experiments with the BACH dataset for breast cancer classification and the SARS-CoV-2 CT-scan dataset for COVID-19 detection affirm the generalization capability of angular margin-based softmax losses in medical image classification.

关键词： Breast cancer histopathological image angular margin-based softmax loss compactness and separability BreakHis SARS-CoV-2 CT-scan

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Flight Testing Instrumentation Development and Integration for a Subscale Integrated High Lift Propulsor Testbed

Flight Testing Instrumentation Development and Integration f...

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AIAA science and Technology Forum and Exposition, AIAA SciTech Forum 2025

作者： Dantsker, D. Mancuso, Renato Ward, Byron Miller, Christian Shea, Donovan Collins, Kyle Department of Intelligent Systems Engineering Indiana University BloomingtonIN47408 United States Department of Computer Science Boston University BostonMA02215 United States Wayfarer Aircraft Research and Development La MesaCA91941 United States Eagle Flight Research Center Embry Riddle Aeronautical University Dayonta BeachFL32114 United States Embry Riddle Aeronautical University Dayonta BeachFL32114 United States

ISBN: (数字)9781624107238

ISBN: (纸本)9781624107238

Recent advancements in electric and hybrid-electric aircraft have sparked interest in Advanced Aerial Mobility (AAM), enabling innovative air transport solutions. Distributed Electric Propulsion (DEP), with its favorable aero-propulsive interactions, is a key focus for advanced aircraft designs, and thus an area of significant interest for academia and industry. Wayfarer Aircraft has developed and patented a novel new form of of blown wing lift augmentation called the Integrated High Lift Propulsor (IHLP), which uses DEP integrated with a Krueger slat or flap. This paper presents the instrumented, reconfigurable subscale IHLP distributed electric propulsion testbed that will be used to parameterize the performance and handling qualities (P&HQ) of IHLP. The subscale aircraft, which was developed from a 35%-scale Cessna 182 R/C scale model aircraft, was instrumented with a custom-integrated flight control and data acquisition system developed to enable this flight research — specifically a Holybro Pixhawk 6X autopilot running custom flight control software coupled with a custom version of the Al Volo FDAQ data acquisition system. The paper presents IHLP including its advantages and performance improvements in high-lift and cruise conditions compared to conventional distributed electric propulsion (DEP) systems. The detailed development of the IHLP subscale testbed are presented, including modifications, instrumentation design, and the integration of the data acquisition and flight control systems. Preliminary results from ground testing are presented to demonstrate the capabilities of the instrumented IHLP testbed. © 2025, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Testbeds

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Timed I/O Automata: It Is Never Too late to Complete Your Timed Specification Theory

arXiv

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arXiv 2023年

作者： Goorden, Martijn A. larsen, Kim G. Legay, Axel Lorber, Florian Nyman, Ulrik Wąsowski, Andrzej Department of Computer Science Aalborg University Selma Lagerlöfs Vej 300 Öst Aalborg9220 Denmark Department of Computer Science Engineering UC Louvain Place Sainte Barbe 2 Louvain-la-Neuve1348 Belgium Department of Computer Science IT University Rued Langgaards Vej 7 Copenhagen S2300 Denmark

A specification theory combines notions of specifications and implementations with a satisfaction relation, a refinement relation and a set of operators supporting stepwise design. We develop a complete specification framework for real-time systems using Timed I/O Automata as the specification formalism, with the semantics expressed in terms of Timed I/O Transition Systems. We provide constructs for refinement, consistency checking, logical and structural composition, and quotient of specifications—all indispensable ingredients of a compositional design methodology. The theory is backed by rigorous proofs and is being implemented in the open-source tool ECDAR. © 2023, CC BY.

关键词： Specifications

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A Novel Smartphone Recommendation System Using Ensemble Machine Learning

A Novel Smartphone Recommendation System Using Ensemble Mach...

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2023 IEEE Asia-Pacific Conference on computer science and Data engineering, CSDE 2023

作者： Almadhor, Ahmad Abbas, Sidra Sampedro, Gabriel Avelino Abisado, Mideth Gadekallu, Thippa Reddy College of Computer and Information Sciences Jouf University Sakaka72388 Saudi Arabia Comsats University Islamabad Department of Computer Science Islamabad Pakistan University of the Philippines Open University Faculty of Information and Communication Studies Los Baños4031 Philippines De la Salle University Center for Computational Imaging and Visual Innovations 2401 Taft Ave. Manila1004 Philippines College of Computing and Information Technologies National University Manila Philippines Zhongda Group Jiaxing City Zhejiang Province Haiyan County314312 China Lebanese American University Department of Electrical and Computer Engineering Byblos Lebanon School of Information Technology and Engineering Vellore Institute of Technology Tamil Nadu India College of Information Science and Engineering Jiaxing University Jiaxing314001 China Lovely Professional University Division of Research and Development Phagwara India

ISBN: (纸本)9798350341072

Due to the proliferation of internet evaluations brought on by the rising demand for smartphones, consumers find it challenging to make accurate selections when purchasing. In this paper, we offer ensemble voting methods based on TF-IDF (Term Frequency-Inverse Document Frequency) features for clas-sifying mobile phone ratings. We use a recently assembled dataset comprising over 13,000 smartphone reviews from the Flipkart website. The suggested approach includes feature extraction using the TF-IDF, data cleaning, balancing, and voting-based model prediction. To identify the recently created Flipkart dataset, the suggested method created an ensemble voting mechanism based on machine learning techniques. According to the experimental findings, the suggested method performs more accurately and efficiently than conventional machine learning techniques. At 98.0 %, the model achieved the greatest accuracy. The suggested method can be expanded to additional e-commerce platforms with sizable datasets of online evaluations and assist customers in making updated purchase preferences. © 2023 IEEE.

关键词： Machine learning

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RecGS: Removing Water Caustic with Recurrent Gaussian Splatting

arXiv

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arXiv 2024年

作者： Zhang, Tianyi Zhi, Weiming Huang, Kaining Mangelson, Joshua Barbalata, Corina Johnson-Roberson, Matthew Robotics Institute School of Computer Science Carnegie Mellon University PittsburghPA15213 United States Department of Mechanical & Industrial Engineering Louisiana State University Baton RougeLA70803 United States Department of Electrical and Computer Engineering Brigham Young University ProvoUT84602 United States

Water caustics are commonly observed in seafloor imaging data from shallow-water areas. Traditional methods that remove caustic patterns from images often rely on 2D filtering or pre-training on an annotated dataset, hindering the performance when generalizing to real-world seafloor data with 3D structures. In this paper, we present a novel method Recurrent Gaussian Splatting (RecGS), which takes advantage of today’s photorealistic 3D reconstruction technology, 3D Gaussian Splatting (3DGS), to separate caustics from seafloor imagery. With a sequence of images taken by an underwater robot, we build 3DGS recurrently and decompose the caustic with low-pass filtering in each iteration. In the experiments, we analyze and compare with different methods, including joint optimization, 2D filtering, and deep learning approaches. The results show that our proposed RecGS paradigm can effectively separate the caustic from the seafloor, improving the visual appearance, and can be potentially applied on more problems with inconsistent illumination. Our videos and code are released at https://***/proj/*** © 2024, CC BY.

关键词： Iterative methods

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Comparison of classical machine learning and ensemble techniques in the context of dengue severity prediction

Comparison of classical machine learning and ensemble techni...

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Colombian Caribbean Conference (C3), IEEE

作者： Wilson Arrubla-Hoyos Zurisaddai Seveiche-Maury Khalid Saeed Jorge Eliecer Gómez Gómez Emiro De-la-Hoz-Franco Faculty of Engineering University of Sucre Sincelejo Colombia Faculty of Computer Science Bialystok University of Technology Bialystok Poland Faculty of Engineering University of Cordoba Monteria Colombia Department Computer Science and Electronics Corporación Universidad de la Costa Barranquilla Colombia

Dengue disease, spread by mosquitoes, affects a large part of the world's population. Early diagnosis is essential to avoid its severe impacts. This paper seeks to compare classical machine learning techniques with ensemble approaches in the early classification of dengue: Dengue without alarm signs (DNWS), Dengue with alarm signs (DWWS) and Severe Dengue (SD). A dataset available at https://***/ from the Colombian government with 53,814 records and 38 attributes is used. The data are processed in Google Colab using Pandas, Matplotlib and Numpy, while Scikit-learn is used for modeling. The results are supported by a detailed confusion matrix, revealing the actual performance of each model and highlighting the superiority of the ensemble approaches over classical techniques in early dengue classification. The Stacking method achieves an accuracy (Acc) of 88%, outperforming all other techniques employed. Among the classical techniques, Decision Tree (DT) achieved the best result with an Acc of 84%. In conclusion, when contrasting the performance of classical techniques and ensemble approaches in early dengue classification, it is highlighted that the latter demonstrate robustness in terms of quality metrics, such as accuracy, recall and F1-Score. This observation suggests that ensemble approaches have the potential to overcome the limitations associated with classical techniques, resulting in more robust and accurate achievements.

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AFDM-Enabled Integrated Sensing and Communication: Theoretical Framework and Pilot Design

arXiv

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arXiv 2025年

作者： Zhang, Fan Wang, Zhaocheng Mao, Tianqi Jiao, Tianyu Zhuo, Yinxiao Wen, Miaowen Xiang, Wei Chen, Sheng Karagiannidis, George K. Department of Electronic Engineering Tsinghua University Beijing100084 China State Key Laboratory of CNS/ATM Beijing Institute of Technology Beijing100081 China Zhuhai519088 China School of Electronic and Information Engineering South China University of Technology Guangzhou China School of Computing Engineering and Mathematical Sciences La Trobe University MelbourneVIC3086 Australia School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Greece

The integrated sensing and communication (ISAC) has been envisioned as one representative usage scenario of sixth-generation (6G) network. However, the unprecedented characteristics of 6G, especially the doubly dispersive channel, make classical ISAC waveforms rather challenging to guarantee a desirable performance level. The recently proposed affine frequency division multiplexing (AFDM) can attain full diversity even under doubly dispersive effects, thus becoming a competitive candidate for next-generation ISAC waveforms. Relevant investigations are still at an early stage, which involve only straightforward design lacking explicit theoretical analysis. This paper provides an in-depth investigation on AFDM waveform design for ISAC applications. Specifically, the closed-form Crámer-Rao bounds of target detection for AFDM are derived, followed by a demonstration on its merits over existing counterparts. Furthermore, we formulate the ambiguity function of the pilot-assisted AFDM waveform for the first time, revealing conditions for stable sensing performance. To further enhance both the communication and sensing performance of the AFDM waveform, we propose a novel pilot design by exploiting the characteristics of AFDM signals. The proposed design is analytically validated to be capable of optimizing the ambiguity function property and channel estimation accuracy simultaneously as well as overcoming the sensing and channel estimation range limitation originated from the pilot spacing. Numerical results have verified the superiority of the proposed pilot design in terms of dual-functional performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Cramer-Rao bounds

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