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New Paradigms in Manifold Learning for Knowledge Discovery and Inverse Design of Photonic Nanostructures 19

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New Paradigms in Manifold Learning for Knowledge Discovery a...

Quantum Sensing and Nano Electronics and Photonics XIX 2023

作者： Zandehshahvar, Mohammadreza Javani, Mohammad Hadigheh Kiarashi, Yashar Zhu, Muliang Brown, Tyler Bao, Daqian Marzban, Mahmoodreza Pourabolghasem, Reza Adibi, Ali School of Electrical and Computer Engineering Georgia Institute of Technology 778 Atlantic Dr NW GA30332 United States Clark Atlanta University 223 James P Brawley Dr SW AtlantaGA30314 United States Department of Biomedical Informatics Emory School of Medicine 100 Woodruff Circle AtlantaGA30322 United States

ISBN: (纸本)9781510659650

This talk is focused on using the intelligent aspects of machine learning (ML) for both the understanding of the subtle properties of nanophotonic devices and their inverse design to achieve a desired response. It will be shown that by reducing the dimensionality of the problem using manifold learning techniques and simplifying the resulting networks using pruning, the computation complexity of the underlying artificial intelligence (AI) algorithms will be considerably reduced. Furthermore, by optimally defining the loss function (or the metric) for AI algorithms, priceless information about the properties of photonic nanostructures can be uncovered while facilitating the better visualization of the input-output relationship in these nanostructures. In addition, the resulting manifold-learning algorithms can be optimally trained to facilitate the inverse design of such nanostructures while minimizing the structural complexity. This talk will provide the foundation for both knowledge discovery and design in photonic nanostructures using manifold learning and metric learning and their application to the highly desired metaphotonic structures as an example platform. © 2023 SPIE.

关键词： Nanostructures

Time-dependent alternative route planning 20

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Time-dependent alternative route planning

20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems, ATMOS 2020

作者： Kontogiannis, Spyros Paraskevopoulos, Andreas Zaroliagis, Christos D. Department of Computer Science and Engineering University of Ioannina Greece Computer Technology Institute and Press "Diophantus" Patras Greece Department of Computer Engineering and Informatics University of Patras Greece Department of Computer Engineering and Informatics University of Patras Greece Computer Technology Institute and Press "Diophantus" Patras Greece

ISBN: (纸本)9783959771702

We present a new method for computing a set of alternative origin-to-destination routes in road networks with an underlying time-dependent metric. The resulting set is aggregated in the form of a time-dependent alternative graph and is characterized by minimum route overlap, small stretch factor, small size and low complexity. To our knowledge, this is the first work that deals with the time-dependent setting in the framework of alternative routes. Based on preprocessed minimum travel-time information between a small set of nodes and all other nodes in the graph, our algorithm carries out a collection phase for candidate alternative routes, followed by a pruning phase that cautiously discards uninteresting or low-quality routes from the candidate set. Our experimental evaluation on real time-dependent road networks demonstrates that the new algorithm performs much better (by one or two orders of magnitude) than existing baseline approaches. In particular, the entire alternative graph can be computed in less than 0.384sec for the road network of Germany, and in less than 1.24sec for that of Europe. Our approach provides also "quick-and-dirty" results of decent quality, in about 1/300 of the above mentioned query times for continental-size instances. © Spyros Kontogiannis, Andreas Paraskevopoulos, and Christos D. Zaroliagis

关键词： Travel time

A Simulation-Optimization Model for Automated Parcel Lockers Network Design in Urban Scenarios in Pamplona (Spain), Zakopane, and Krakow (Poland) 22

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A Simulation-Optimization Model for Automated Parcel Lockers...

Proceedings of the Winter Simulation Conference

作者： Bartosz Sawik Adrian Serrano-Hernandez Aitor Ballano Javier Faulin Department of Business Informatics and Engineering Management AGH University of Science and Technology Krakow POLAND Institute of Smart Cities Department of Statistics Computer Science and Mathematics Public University of Navarre Pamplona SPAIN

The constant rise of e-commerce coupled with extremely fast deliveries is a significant contributor to saturate city centers' mobility. To address this issue, the development of a convenient Automated Parcel Lockers (APLs) network improves last-mile distribution by reducing the number of transportation vehicles, the distances driven, and the delivery stops. This article aims to define and compare APL networks in the cities of Pamplona (Spain), Zakopane and Krakow (Poland). Thereby, a bi-criteria weighted-sum simulation optimization model is developed for a representative year for the aforementioned cities. The simulation forecasts the e-commerce demands whereas the optimal APL network is obtained with a bi-criteria maximum APL revenues and minimum network costs. Meaningful results are obtained from the multi-criteria hybrid model outcomes as well as from the cities comparison. These outcomes suggest efficient APLs networks considering cultural and demographic factors for a massive use of APLs in high-demand periods.

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Minimum Mean Squared Error Holographic Beamforming for Sum-Rate Maximization

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arXiv 2025年

作者： Sheemar, Chandan Kumar Khan, Wali Ullah Alexandropoulos, George C. Ahmed, Manzoor Chatzinotas, Symeon SnT department The University of Luxembourg Luxembourg Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens16122 Greece School of Computer and Information Science Institute for AI Industrial Technology Research Hubei Engineering University Xiaogan City432000 China

This paper studies the problem of hybrid holographic beamforming for sum-rate maximization in a communication system assisted by a reconfigurable holographic surface. Existing methodologies predominantly rely on gradient-based or approximation techniques necessitating iterative optimization for each update of the holographic response, which imposes substantial computational overhead. To address these limitations, we establish a mathematical relationship between the mean squared error (MSE) criterion and the holographic response of the RHS to enable alternating optimization based on the minimum MSE (MMSE). Our analysis demonstrates that this relationship exhibits a quadratic dependency on each element of the holographic beamformer. Exploiting this property, we derive closed-form optimal expressions for updating the holographic beamforming weights. Our complexity analysis indicates that the proposed approach exhibits only linear complexity in terms of the RHS size, thus, ensuring scalability for large-scale deployments. The presented simulation results validate the effectiveness of our MMSE-based holographic approach, providing useful insights. © 2025, CC BY.

关键词： Iterative methods

Classifying Simulated Gait Impairments using Privacy-preserving Explainable Artificial Intelligence and Mobile Phone Videos

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arXiv 2024年

作者： Reddy, Lauhitya Anand, Ketan Kaushik, Shoibolina Rodrigo, Corey McKay, J. Lucas Kesar, Trisha M. Kwon, Hyeokhyen Department of Biomedical Engineering Emory University Georgia Institute of Technology AtlantaGA United States Department of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA United States Department of Computer Science Emory University AtlantaGA United States Department of Rehabilitation Medicine Emory University AtlantaGA United States Department of Neurology Emory University AtlantaGA United States Department of Biomedical Informatics Emory University AtlantaGA United States

Accurate diagnosis of gait impairments is often hindered by subjective or costly assessment methods, with current solutions requiring either expensive multi-camera equipment or relying on subjective clinical observation. There is a critical need for accessible, objective tools that can aid in gait assessment while preserving patient privacy. In this work, we present a mobile phone-based, privacy-preserving artificial intelligence (AI) system for classifying gait impairments and introduce a novel dataset of 743 videos capturing seven distinct gait patterns. The dataset consists of frontal and sagittal views of trained subjects simulating normal gait and six types of pathological gait (circumduction, Trendelenburg, antalgic, crouch, Parkinsonian, and vaulting), recorded using standard mobile phone cameras. Our system achieved 86.5% accuracy using combined frontal and sagittal views, with sagittal views generally outperforming frontal views except for specific gait patterns like Circumduction. Model feature importance analysis revealed that frequency-domain features and entropy measures were critical for classifcation performance, specifically lower limb keypoints proved most important for classification, aligning with clinical understanding of gait assessment. These findings demonstrate that mobile phone-based systems can effectively classify diverse gait patterns while preserving privacy through on-device processing. The high accuracy achieved using simulated gait data suggests their potential for rapid prototyping of gait analysis systems, though clinical validation with patient data remains necessary. This work represents a significant step toward accessible, objective gait assessment tools for clinical, community, and tele-rehabilitation settings. © 2024, CC BY-NC-SA.

关键词： Differential privacy

Maximum Correntropy Criterion Kalman Filter for Indoor Quadrotor Navigation under Intermittent Measurements

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arXiv 2023年

作者： Hadjiloizou, Loizos Makridis, Evagoras Charalambous, Themistoklis Deliparaschos, Kyriakos M. Department of Intelligent Systems KTH Royal Institute of Technology Stockholm Sweden Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Electrical and Computer Engineering and Informatics Department Cyprus University of Technology Limassol Cyprus

We present a multisensor fusion framework for the onboard real-time navigation of a quadrotor in an indoor environment. The framework integrates sensor readings from an Inertial Measurement Unit (IMU), a camera-based object detection algorithm, and an Ultra-WideBand (UWB) localisation system. Often the sensor readings are not always readily available, leading to inaccurate pose estimation and hence poor navigation performance. To effectively handle and fuse sensor readings, and accurately estimate the pose of the quadrotor for tracking a predefined trajectory, we design a Maximum Correntropy Criterion Kalman Filter (MCC-KF) that can manage intermittent observations. The MCC-KF is designed to improve the performance of the estimation process when is done with a Kalman Filter (KF), since KFs are likely to degrade dramatically in practical scenarios in which noise is non-Gaussian (especially when the noise is heavy-tailed). To evaluate the performance of the MCC-KF, we compare it with a previously designed Kalman filter by the authors. Through this comparison, we aim to demonstrate the effectiveness of the MCC-KF in handling indoor navigation missions. The simulation results show that our presented framework offers low positioning errors, while effectively handling intermittent sensor measurements. Copyright © 2023, The Authors. All rights reserved.

关键词： Kalman filters

Blockchain-Enhanced Energy-Efficient Architectures for Sustainable Internet of Things Ecosystems 1st

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Blockchain-Enhanced Energy-Efficient Architectures for Susta...

1st International Conference on Advanced Network Technologies and Computational Intelligence, ICANTCI 2024

作者： Goyal, S.B. Rajawat, Anand Singh Verma, Chaman Illés, Zoltán Singh, Jaiteg Faculty of Information Technology City University Petaling Jaya46100 Malaysia School of Computer Sciences and Engineering Sandeep University Nashik India Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest Hungary Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India

ISBN: (纸本)9783031860683

Novel technique are required to ensure the long-term viability and maximize the efficiency of energy consumption in the constantly changing Internet of Things (IoT) landscape. In order to accomplish these objectives, this study examines the potential use of blockchain technology into IoT architectural concepts. Our approach utilizes blockchain technology to effectively manage and enhance energy consumption in IoT devices and networks. This is achieved by capitalizing on the decentralized, secure, and transparent characteristics of blockchain. Our objective is to do this by developing a decentralized ledger system that documents all energy transactions and interactions inside an Internet of Things (IoT) environment. This strategy utilizes blockchain technology to provide accountability and real-time monitoring of energy consumption, hence facilitating improved energy allocation and consumption. We delve into the concept and execution of smart contracts that ensure transactions and automate energy-conservation procedures, thereby diminishing the necessity for centralized authority and alleviating energy wastage. In addition, we examine the possibility of blockchain technology to enable direct energy transfer between Internet of Things (IoT) devices. This feature facilitates the development of a self-sustaining Internet of Things ecosystem by enabling devices with surplus energy to vend it to those requiring it. We also tackle the difficulties associated with the integration of blockchain with IoT, such as the energy consumption resulting from blockchain activities and the ability to effectively handle large volumes of data. Furthermore, we offer resolutions to these problems. The proposed framework improves the energy efficiency of IoT ecosystems and promotes their sustainability by advocating for the use of renewable energy sources and decreasing carbon footprints. Through the utilization of simulations and real-world illustrations, we showcase the efficacy of our bl

关键词： Clean energy

A modified SELEX approach to identify DNA aptamers with binding specificity to the major histocompatibility complex presenting ovalbumin model antigen

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RSC Advances 2023年第46期13卷 32681-32693页

作者： Lin, Yang Chen, Cho-Yi Ku, Yu-Chia Wang, Li-Chin Hung, Chia-Chien Lin, Zhi-Qian Chen, Bing-Hong Hung, Jui-Tse Sun, Yi-Chen Hung, Kai-Feng Department of Medical Research Taipei Veterans General Hospital 201 Section 2 Shi-Pai Road Taipei112 Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei Taiwan School of Computer Science Georgia Institute of Technology Atlanta GA United States Kang Chiao International School Taipei Taiwan School of Medicine Tzu-Chi University Hualien Taiwan Department of Ophthalmology Taipei Tzu Chi Hospital The Buddhist Tzu Chi Medical Foundation New Taipei City Taiwan Department of Dentistry School of Dentistry National Yang Ming Chiao Tung University Taipei Taiwan

Aptamers have sparked significant interest in cell recognition because of their superior binding specificity and biocompatibility. Cell recognition can be mediated by targeting the major histocompatibility complex (MHC) that presents short peptides derived from intracellular antigens. Although numerous antibodies have demonstrated a specific affinity for the peptide-MHC complex, the number of aptamers that exhibit comparable characteristics is limited. Aptamers are usually selected from large libraries via the Systemic Evolution of Ligands by Exponential Enrichment (SELEX), an iterative process of selection and PCR amplification to enrich a pool of aptamers with high affinity. However, the success rate of aptamer identification is low, possibly due to the presence of complementary sequences or sequences rich in guanine and cytosine that are less accessible for primers. Here, we modified SELEX by employing systemic consecutive selections with minimal PCR amplification. We also modified the analysis by selecting aptamers that were identified in multiple selection rounds rather than those that are highly enriched. Using this approach, we were able to identify two aptamers with binding specificity to cells expressing the ovalbumin alloantigen as a proof of concept. These two aptamers were also discovered among the top 150 abundant candidates, despite not being highly enriched, by performing conventional SELEX. Additionally, we found that highly enriched aptamers tend to contain fractions of the primer sequence and have minimal target affinity. Candidate aptamers are easily missed in the conventional SELEX process. Therefore, our modification for SELEX may facilitate the identification of aptamers for more application in diverse biomedical fields. Significance: we modify the conventional method to improve the efficiency in the identification of the aptamer, a single strand of nucleic acid with binding specificity to the target molecule, showing as a proof of concept that

关键词： Peptides

RoboDesign1M: A Large-scale Dataset for Robot Design Understanding

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arXiv 2025年

作者： Le, Tri Nguyen, Toan Tran, Quang Nguyen, Quang Huang, Baoru Nguyen, Hoan Vu, Minh Nhat Ta, Tung D. Nguyen, Anh FPT Software AI Center Viet Nam Department of Computer Science University of Liverpool United Kingdom University of Information Technology HCMC Viet Nam Automation & Control Institute TU Wien Austria Department of Creative Informatics The University of Tokyo Japan

Robot design is a complex and time-consuming process that requires specialized expertise. Gaining a deeper understanding of robot design data can enable various applications, including automated design generation, retrieving example designs from text, and developing AI-powered design assistants. While recent advancements in foundation models present promising approaches to addressing these challenges, progress in this field is hindered by the lack of large-scale design datasets. In this paper, we introduce RoboDesign1M, a large-scale dataset comprising 1 million samples. Our dataset features multimodal data collected from scientific literature, covering various robotics domains. We propose a semi-automated data collection pipeline, enabling efficient and diverse data acquisition. To assess the effectiveness of RoboDesign1M, we conduct extensive experiments across multiple tasks, including design image generation, visual question answering about designs, and design image retrieval. The results demonstrate that our dataset serves as a challenging new benchmark for design understanding tasks and has the potential to advance research in this field. RoboDesign1M will be released to support further developments in AI-driven robotic design automation. © 2025, CC BY-NC-ND.

关键词： Machine design