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arXiv 2024年

作者： Mieno, Takuya Inenaga, Shunsuke Department of Computer and Network Engineering University of Electro-Communications Chofu Japan Department of Informatics Kyushu University Fukuoka Japan

A substring u of a string T is said to be a repeat if u occurs at least twice in T. An occurrence [i..j] of a repeat u in T is said to be a net occurrence if each of the substrings aub = T[i− 1..j + 1], au = T[i− 1..j + 1], and ub = T[i..j + 1] occurs exactly once in T. The occurrence [i− 1..j + 1] of aub is said to be an extended net occurrence of u. Let T be an input string of length n over an alphabet of size σ, and let ENO(T) denote the set of extended net occurrences of repeats in T. Guo et al. [SPIRE 2024] presented an online algorithm which can report ENO(T[1..i]) in T[1..i] in O(nσ2) time, for each prefix T[1..i] of T. Very recently, Inenaga [arXiv 2024] gave a faster online algorithm that can report ENO(T[1..i]) in optimal O(#ENO(T[1..i])) time for each prefix T[1..i] of T, where #S denotes the cardinality of a set S. Both of the aforementioned data structures can be maintained in O(nlog σ) time and occupy O(n) space, where the O(n)-space requirement comes from the suffix tree data structure. In particular, Inenaga’s recent algorithm is based on Weiner’s right-to-left online suffix tree construction. In this paper, we show that one can modify Ukkonen’s left-to-right online suffix tree construction algorithm in O(n) space, so that ENO(T[1..i]) can be reported in optimal O(#ENO(T[1..i])) time for each prefix T[1..i] of T. This is an improvement over Guo et al.’s method that is also based on Ukkonen’s algorithm. Further, this leads us to the two following space-efficient alternatives: A sliding-window algorithm of O(d) working space that can report ENO(T[i−d+1..i]) in optimal O(#ENO(T[i− d+ 1..i])) time for each sliding window T[i− d+ 1..i] of size d in T. A CDAWG-based online algorithm of O(e) working space that can report ENO(T[1..i]) in optimal O(#ENO(T[1..i])) time for each prefix T[1..i] of T, where e Copyright © 2024, The Authors. All rights reserved.

关键词： Data structures

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Minimal Resource Required E-Health System with End-to-End Authenticated Encryption Mechanism

Minimal Resource Required E-Health System with End-to-End Au...

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International Conference on Modern Circuits and Systems Technologies (MOCAST)

作者： Kyriaki Tsantikidou Nicolas Sklavos Computer Engineering and Informatics Department (CEID) SCYTALE Group University of Patras Hellas

Smart health applications provide new services to traditional healthcare structures. They mainly employ the Internet of Things (IoT) technology, which allows different components to communicate via data protocols. Such a protocol is the Message Queuing Telemetry Transport (MQTT). Nevertheless, MQTT does not have any built-in security scheme, thus leaving crucial health data vulnerable to attacks. The Transport Layer Security (TLS) protocol can be applied on top of MQTT. However, even with the time reduction of TLS 1.3, it adds communication overhead, causing issues to resource-constrained IoT devices. This paper designs a lightweight authenticated encryption system for end-to-end security in Smart Health. The proposed architecture achieves 92.7% area decrease compared to other MQTT-based implementations. The employed cryptographic primitive, Photon-Beetle AEAD, is implemented in a 4-bit structural architecture with resource sharing techniques. The main functions of the algorithm are fused, further achieving resource decrease and a low execution time. The mechanism is employed only on end devices with proper key management schemes. Intermediate components are not required to process the data before transmitting them, thus reducing the computation and communication overhead. Overall, this research is one of the few that focuses on a FPGA-based implementation rather than more high-processing devices for MQTT, better simulating the IoT limitations.

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Deterministic Networking (DetNet): Architecture, Protocols, and Advanced Applications

Deterministic Networking (DetNet): Architecture, Protocols, ...

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International Conference on Mechatronics (ICOM)

作者： Zeinab E. Ahmed Aisha A. Hashim Rashid A. Saeed Mamoon M. Saeed Department of Computer Engineering University of Gezira Sudan Department of Electrical and Computer Engineering International Islamic University Malaysia Malaysia School of Electronic Engineering Sudan University of Science and Technology Khartoum Sudan Department of Communications and Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Yemen

ISBN: (数字)9798350349788

ISBN: (纸本)9798350349795

This paper provides a thorough overview of Deterministic Networking (DetN et), focusing on establishing predictable data routes in Layer 2 and Layer 3 networks to address network issues like congestion, latency, and packet loss. It discusses DetNet's principles, architecture, and Operations, Administration, and Maintenance (OAM) protocols, crucial for fault detection and network monitoring. DetN et ensures bounded latency and minimal data loss, catering to industries' need for reliable flows over multi-hop paths. It integrates Time Sensitive Networking (TSN) and MPLS, using Resource Allocation (RA), Service Protection (SP), and Explicit Routing (ER) as core technologies, within a structured architecture of controller, application, and network planes. OAM is pivotal for efficient DetN et management, offering tools for fault detection, continuity checks, and maintenance activities to maintain Service Level Objectives (SLOs). The paper delves into advanced DetN et applications, highlighting enhanced protocols, health care frameworks, service function chain management, and industrial networking solutions, emphasizing their potential to improve reliability and network efficiency across diverse applications.

关键词： Industries Multiprotocol label switching Job shop scheduling Service function chaining Fault detection Packet loss Medical services

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Evaluation and improvement of Segment Anything Model for interactive histopathology image segmentation

arXiv

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arXiv 2023年

作者： Kim, SeungKyu Oh, Hyun-Jic Min, Seonghui Jeong, Won-Ki Korea University College of Informatics Department of Computer Science and Engineering Korea Republic of

With the emergence of the Segment Anything Model (SAM) as a foundational model for image segmentation, its application has been extensively studied across various domains, including the medical field. However, its potential in the context of histopathology data, specifically in region segmentation, has received relatively limited attention. In this paper, we evaluate SAM’s performance in zero-shot and fine-tuned scenarios on histopathology data, with a focus on interactive segmentation. Additionally, we compare SAM with other state-of-the-art interactive models to assess its practical potential and evaluate its generalization capability with domain adaptability. In the experimental results, SAM exhibits a weakness in segmentation performance compared to other models while demonstrating relative strengths in terms of inference time and generalization capability. To improve SAM’s limited local refinement ability and to enhance prompt stability while preserving its core strengths, we propose a modification of SAM’s decoder. The experimental results suggest that the proposed modification is effective to make SAM useful for interactive histology image segmentation. The code is available at https://***/hvcl/SAM_Interactive_Histopathology © 2023, CC BY-NC-SA.

关键词： Image segmentation

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Reference-Free Isotropic 3D EM Reconstruction using Diffusion Models

arXiv

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arXiv 2023年

作者： Lee, Kyungryun Jeong, Won-Ki Korea University College of Informatics Department of Computer Science and Engineering Korea Republic of

Electron microscopy (EM) images exhibit anisotropic axial resolution due to the characteristics inherent to the imaging modality, presenting challenges in analysis and downstream tasks. Recently proposed deep-learning-based isotropic reconstruction methods have addressed this issue;however, training the deep neural networks require either isotropic ground truth volumes, prior knowledge of the degradation process, or point spread function (PSF). Moreover, these methods struggle to generate realistic volumes when confronted with high scaling factors (e.g. ×8, ×10) In this paper, we propose a diffusion-model-based framework that overcomes the limitations of requiring reference data or prior knowledge about the degradation process. Our approach utilizes 2D diffusion models to consistently reconstruct 3D volumes and is well-suited for highly downsampled data. Extensive experiments conducted on two public datasets demonstrate the robustness and superiority of leveraging the generative prior compared to supervised learning methods. Additionally, we demonstrate our method’s feasibility for self-supervised reconstruction, which can restore a single anisotropic volume without any training data. The source code is available on GitHub: https://***/hvcl/diffusion-em-recon. © 2023, CC BY-NC-ND.

关键词： Deep neural networks

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Product Recognition for Inventory Management Using Spatial Partitioning in a Multi-Camera System

Product Recognition for Inventory Management Using Spatial P...

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2025 IEEE International Conference on Consumer electronics, ICCE 2025

作者： Munasinghe, Viduranga Lee, Tae-Ho Kim, Tae Sung Kim, Jin-Sung Lee, Hyuk-Jae Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Department of Electronic Engineering SunMoon University Asan31460 Korea Republic of

ISBN: (纸本)9798331521165

Recent advancements in deep learning have significantly improved object detection capabilities. However, accurately recognizing objects in environments with complex occlusions remains a challenge. For instance, detecting densely packed items on shelves in unmanned stores presents difficulties even for the most cutting-edge deep-learning object detectors. To address this issue, we propose a deep learning-based inventory management system tailored for multi-camera unmanned stores. The proposed method utilizes a Voronoi diagram-based ground plane localization technique along with regions of interest (ROI) obtained by using image difference. A weighted voting algorithm is employed to ensure an accurate inventory check. This approach outperforms conventional ROI detection methods by 10.45% in terms of recognition accuracy. © 2025 IEEE.

关键词： Deep learning

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Tender Notice Extraction from E-papers Using Neural Network

arXiv

引用

arXiv 2023年

作者： Bhattarai, Ashmin Sedhai, Anuj Neupane, Devraj Khadka, Manish Bastola, Rama Department of Electronic and Computer Engineering Institute of Engineering Tribhuvan University Thapathali Campus Kathmandu Nepal

Tender notices are usually sought by most of the companies at regular intervals as a means for obtaining the contracts of various projects. These notices consist of all the required information like description of the work, period of construction, estimated amount of project, etc. In the context of Nepal, tender notices are usually published in national as well as local newspapers. The interested bidders should search all the related tender notices in newspapers. However, it is very tedious for these companies to manually search tender notices in every newspaper and figure out which bid is best suited for them. This project is built with the purpose of solving this tedious task of manually searching the tender notices. Initially, the newspapers are downloaded in PDF format using the selenium library of python. After downloading the newspapers, the e-papers are scanned and tender notices are automatically extracted using a neural network. For extraction purposes, different architectures of CNN namely ResNet, GoogleNet and Xception are used and a model with highest performance has been implemented. Finally, these extracted notices are then published on the website and are accessible to the users. This project is helpful for construction companies as well as contractors assuring quality and efficiency. This project has great application in the field of competitive bidding as well as managing them in a systematic manner. © 2023, CC BY.

关键词： Extraction

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Design of circular pad coupler of inductive power transfer for electric vehicle (EV) 8

Design of circular pad coupler of inductive power transfer f...

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8th International Conference on computer and Communication engineering, ICCCE 2021

作者： Zaini, Syasya Azra Yusoff, Siti Hajar Hanifah, Mohd Shahrin Abu Sulaiman, Erwan Nanda, Nadia Nazieha Badruhisham, Saidatul Haneen Department of Electronic and Computer Engineering Kula Lumpur Malaysia Department of Electrical Engineering Johor Malaysia

ISBN: (纸本)9781728110646

The depletion in energy sources especially oil is among the crucial issues nowadays in Malaysia. Since the quantity of vehicles in Malaysia are increasing, the oil sources are not enough to accommodate all. Wireless charging of Electric Vehicle (EV) has been developed to solve this issue but it gives limited performance due to misalignment, air gap and power loss. Therefore, this project proposed three coil pair design of circular pad coupler for wireless charging of EV. These three pairs were tested for air gap and misalignment cases using simulation and experimental work to find the best coil pair which gives the highest efficiency of power transfer. To design the circular pad, three elements are required in this project which are circuit parameters, geometric properties and experimental work. At first, the circuit parameters are calculated using a specific equation to obtain the inductance value for primary and secondary coil at resonant frequency which is needed for the fabrication of coil process. The simulation for ideal case were done using NI Multisim software to prove the calculated circuit parameters. Then, the geometric properties were calculated and designed in JMAG Designer software. Before designing the circular coil, several geometric parameters like inner diameter, outer diameter and number of turns were set up and calculated. Here, the magnetic flux density and power transfer were observed and measured for each coil pair design. The limitation for this study is that the high cost of copper wire and limited equipment in the laboratory. © 2021 IEEE.

关键词： Electric vehicles

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Distributed operational management of microgrids: a second order dual update approach

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IFAC-PapersOnLine 2023年第2期56卷 1540-1545页

作者： Giulio Ferro Michela Robba Federico Delfino Rabab Haider Anuradha M. Annaswamy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA 02141 USA Department of of Electrical Electronic Telecommunications Engineering and Naval Architecture University of Genova

This paper develops a Distributed Energy Management System (EMS) to optimally allocate electric and thermal power production in a polygenerative microgrid. The EMS problem is formulated as a multiperiod convex optimization problem and solved using AL-SODU, a new distributed algorithm based on the augmented Lagrangian method with second order dual updates. The proposed AL-SODU algorithm significantly outperforms state of the art algorithms employing first order dual updates, with 15-times speedup in convergence speed. A case study of the EMS based on AL-SODU is conducted on the Smart Polygeneration Microgrid (SPM) located on the Savona Campus of University of Genova (Italy). The EMS determines the optimal schedules for electric and thermal power plants every 15-minutes. This real time scheduling of the microgrid is enabled by the Al-SODU algorithm, which solves the scheduling problem in 1.86s.

关键词： Microgrids distributed control second order methods

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Optimized Vision Transformer for Dementia Diagnosis Using Micro-Doppler Radar

Optimized Vision Transformer for Dementia Diagnosis Using Mi...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Ishibashi, Ryuto Nojiri, Naoto Kaneko, Hayata Kenshi, Saho Meng, Lin Graduate School of Science and Engineering Ritsumeikan University 1-1-1 Nojihigashi Shiga Kusatsu525-8577 Japan Ritsumeikan University Department of Electronic and Computer Engineering 1-1-1 Nojihigashi Shiga Kusatsu525-8577 Japan

ISBN: (纸本)9798350337020

In the aging society, the number of dementia patients continues to increase, and early detection of dementia is required. However, going to a hospital and being diagnosed by a doctor is burdensome for elderly people. This paper designs a Vision Transformer(ViT)-based gait diagnosis with micro-Doppler radar to diagnose dementia without burden for elderly people. The ViT is optimized by proposed Vertical Rectangle Patching and Adaptive Thresholding, which improve the Attention of Vi'I. The micro-Doppler radar collects the signal of elderly people, and the signal is transformed into two kinds of signal-analyzed images by two signal-analysis methods (Short-term Fourier Transform: STFT, and Continuous Wavelet Transform: CWT) for diagnosing by optimized ViI. Experiments compare eight kinds of CNN models, and current ViTs with the optimized ViT to evaluate the proposal's performance. The experimental results show that STFT is suitable for analyzing micro-Doppler radar signals, and ViT-56x4s+th, which uses Vertical Rectangle Patching and Adaptive Thresholding, achieves high scores such as an accuracy of 88.9%. Another proposed model ViT-224xl allows for faster learning convergence for time series data and improved accuracy without fine-tuning. In summary, the possibility of diagnosing dementia by optimized ViT has been provided. The experimentation of Adaptive thresholding also proves there are some unimportant patches and brings an idea for reducing the unimportant computations to achieve a compact ViT as future work. © 2023 IEEE.

关键词： Dementia Diagnosis MicroDoppler Radar Vision Transformer

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