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Fruit Quality Assessment with Densely Connected Convolutional Neural Network

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arXiv 2022年

作者： Morshed, Md. Samin Ahmed, Sabbir Ahmed, Tasnim Islam, Muhammad Usama Rahman, A.B.M. Ashikur Department of Computer Science and Engineering Islamic University of Technology Gazipur1704 Bangladesh School of Computing and Informatics University of Louisiana at Lafayette LafayetteLA United States Department of ICS King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

Accurate recognition of food items along with quality assessment is of paramount importance in the agricultural industry. Such automated systems can speed up the wheel of the food processing sector and save tons of manual labor. In this connection, the recent advancement of Deep learning-based architectures has introduced a wide variety of solutions offering remarkable performance in several classification tasks. In this work, we have exploited the concept of Densely Connected Convolutional Neural Networks (DenseNets) for fruit quality assessment. The feature propagation towards the deeper layers has enabled the network to tackle the vanishing gradient problems and ensured the reuse of features to learn meaningful insights. Evaluating on a dataset of 19,526 images containing six fruits having three quality grades for each, the proposed pipeline achieved a remarkable accuracy of 99.67%. The robustness of the model was further tested for fruit classification and quality assessment tasks where the model produced a similar performance, which makes it suitable for real-life applications. © 2022, CC BY.

关键词： Fruits

Photonic Frequency Space Simulation of Tight-Binding Lattices Using Integrated LNOI Ring Resonators

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Photonic Frequency Space Simulation of Tight-Binding Lattice...

Pacific Rim Conference on Lasers and Electro-Optics (CLEO/Pacific Rim)

作者： Armandas Balčytis Hiep Dinh Tomoki Ozawa Yasutomo Ota Toshihiko Baba Satoshi Iwamoto Arnan Mitchell Thach G. Nguyen Integrated Photonics and Applications Centre RMIT University Melbourne VIC Australia Advanced Institute for Materials Research Tohoku University Sendai Japan Department of Applied Physics and Physico-Informatics Keio University Yokohama Japan Department of Electrical and Computer Engineering Yokohama National University Hodogaya-ku Yokohama Japan Research Center for Advanced Science and Technology The University of Tokyo Meguro-ku Tokyo Japan

We use electro-optically modulated ring cavities, integrated on thin-film lithium niobate, to model frequency dimension tight-binding lattices with versatile connectivity. Inter-mode coupling range, strength, and hopp... 详细信息

ISBN: (数字)9798350372076

ISBN: (纸本)9798350372083

关键词： Frequency modulation Lithium niobate Resonant frequency Lattices Electro-optic modulators Ring lasers Laser modes

Delay Tolerant and Multipath Reliability for Energy Efficient Heterogeneous VANETs Network

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Delay Tolerant and Multipath Reliability for Energy Efficien...

Advanced engineering and Technologies (ICONNIC), International Conference on

作者： Zudha Pratama Ichwan Setiarso Sarmad Nozad Mahmood Mohammed Almohamadi Sameer Alani Fatima Hashim Abbas Razan Abdulhammed Ahmed H. Alkhayyat Rabei Raad Ali Informatics Engineering University of Dian Nuswantoro Kediri Indonesia Visual communication design University of Dian Nuswantoro Kediri Indonesia Computer Technology Engineering Al-Kitab University Kirkuk Iraq College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna Iraq Research Center University of Mashreq Baghdad Iraq Medical Laboratories Techniques Al-Mustaqbal University College Babil Iraq Department of Computer Engineering Technology Northern Technical University Mosul Iraq College of technical engineering The Islamic University Najaf Iraq

Vehicular Adhoc Networks (VANETs) provide communication among vehicles to build smart cities using Intelligent Transportation System (ITS). In this paper, we proposed Delay Tolerant and Multipath Reliability (DTMR) in VANETs. The simulation of the DTMR method is performed using OMNet++ network simulator with Simulation of Urban Mobility (SUMO). The parameters which are considered for the performance analysis are end-to-end delay, data failure rate, data success rate and throughput. The results show that the DTMR method produces 85ms lower end-to-end delay, 13% lower data failure rate, 93 % higher data success rate and 614 Kbps higher throughput. The proposed DTMR method has better overall performance than the ISFF and VDPR methods.

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Bridge the Present and Future: A Cross-Layer Matching Game in Dynamic Cloud-Aided Mobile Edge Networks

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arXiv 2023年

作者： Qi, Houyi Liwang, Minghui Wang, Xianbin Li, Li Gong, Wei Jin, Jian Jiao, Zhenzhen The School of Informatics Xiamen University Fujian China The Department of Electrical and Computer Engineering Western University ON Canada The Department of Control Science and Engineering Tongji University Shanghai China The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The Research Institute of Industrial Internet of Things CAICT China The iF-Labs Beijing Teleinfo Technology Co. Ltd. CAICT China

Cloud-aided mobile edge networks (CAMENs) allow edge servers (ESs) to purchase resources from remote cloud servers (CSs), while overcoming resource shortage when handling computation-intensive tasks of mobile users (MUs). Conventional trading mechanisms (e.g., onsite trading) confront many challenges, including decision-making overhead (e.g., latency) and potential trading failures. This paper investigates a series of cross-layer matching mechanisms to achieve stable and cost-effective resource provisioning across different layers (i.e., MUs, ESs, CSs), seamlessly integrated into a novel hybrid paradigm that incorporates futures and spot trading. In futures trading, we explore an overbooking-driven aforehand cross-layer matching (OA-CLM) mechanism, facilitating two future contract types: contract between MUs and ESs, and contract between ESs and CSs, while assessing potential risks under historical statistical analysis. In spot trading, we design two backup plans respond to current network/market conditions: determination on contractual MUs that should switch to local processing from edge/cloud services;and an onsite cross-layer matching (OS-CLM) mechanism that engages participants in real-time practical transactions. We next show that our matching mechanisms theoretically satisfy stability, individual rationality, competitive equilibrium, and weak Pareto optimality. Comprehensive simulations in real-world and numerical network settings confirm the corresponding efficacy, while revealing remarkable improvements in time/energy efficiency and social welfare. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

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Asian Journal of Control 2022年第1期24卷 388-400页

作者： Moaveni, Bijan Rashidi Fathabadi, Fatemeh Molavi, Ali Center of excellence for Modelling and Control of Complex Systems Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Western Michigan University MI United States Institute of Robotics and Industrial Informatics Polytechnical University of Catalonia Barcelona Spain

This study proposes an anti-slip control system for electric trains based on the fuzzy logic theory, which prevents the wheels from slipping during the acceleration and simultaneously tracks the desired speed profile. To improve the control performance, the train longitudinal velocity and the slip ratio are estimated. By using a field-oriented control (FOC), the angular speed of the traction motor is controlled. The fuzzy control system determines the desired angular speed of the traction motor as the reference input of FOC to obtain the desired slip ratio and track the desired speed profile. Simulation results show the effectiveness of the control system in various wheel–rail surface conditions based on the real parameters of ER24PC locomotive. © 2020 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd

关键词： Traction motors

Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer

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Predicting Microsatellite Instability from Histology Images ...

IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Yun-Chi Chen Tung Chao Wimaya Nitya Phandita Tzu-Yu Sun Huai-Zhi Wang Yi-Hsien Hsieh Le-Yin Hsu Che Lin Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University (NTU) Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan Data Science Degree Program NTU Taipei Taiwan Department of Electrical Engineering NTU Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan Smart Medicine and Health Informatics Program NTU Taipei Taiwan

ISBN: (数字)9798331518622

ISBN: (纸本)9798331518639

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients.

关键词： Attention mechanisms Histopathology Computational modeling Precision medicine Small satellites Immunotherapy Colorectal cancer Predictive models Transformers Genetics

Wideband THz Multi-User Downlink Communications with Leaky Wave Antennas

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arXiv 2023年

作者： Gabay, Yaela Shlezinger, Nir Routtenberg, Tirza Ghasempour, Yasaman Alexandropoulos, George C. Eldar, Yonina C. the School of ECE Ben-Gurion University of the Negev Israel the Department of ECE Princeton University NJ United States the Department of Informatics and Telecommunications National and Kapodistrian University of Athens Athens15784 Greece Department of Electrical and Computer Engineering University of Illinois Chicago ChicagoIL60601 United States the Faculty of Math and CS Weizmann Institute of Science Rehovot Israel

Future wireless systems are envisioned to utilize the large spectra available at THz bands for wireless communications. Extremely massive multiple-input multiple-output (MIMO) antennas can be costly and power inefficient for wideband THz communications. An alternative antenna technology, which can achieve low cost and power efficient THz signaling, is based on leaky wave antennas (LWAs). In this paper, we explore the usage of the LWAs for wideband downlink multiuser THz communications. We propose a model for LWA-aided communication systems that faithfully captures the antenna operations. We that LWAs yield frequency-dependent beams, where the equivalent wideband channel induces dependence between angle, frequency, and spectral lobe width. We identify the LWA’s inherent frequency-selective beamsteering capabilities as motivating multi-band THz communications that deviate from conventional orthogonal frequency-division, and employ nonidentical subbands. Then, we propose an alternating optimization algorithm for jointly optimizing the LWA configuration along with the spectral division and power allocation to maximize the achievable sum-rate. Our numerical results show that a single LWA can generate diverse beampatterns, exhibiting performance comparable to costly fully digital MIMO. Interestingly, we demonstrate that allowing transmission with non-identical subbands leverages the characteristics of LWA-based channels compared to uniform division, yielding improved beamsteering that translate to higher rates Copyright © 2023, The Authors. All rights reserved.

关键词： Antenna lobes

A trustable and interoperable decentralized solution for citizen-centric and cross-border eGovernance: A conceptual approach

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arXiv 2021年

作者： Domalis, George Karacapilidis, Nikos Tsakalidis, Dimitris Giannaros, Anastasios Novelcore Greece IMIS Lab. MEAD University of Patras Greece Computer Engineering and Informatics Department University of Patras Greece

Aiming to support a cross-sector and cross-border eGovernance paradigm for sharing common public services, this paper introduces an AI-enhanced solution that enables beneficiaries to participate in a decentralized network for effective big data exchange and service delivery that promotes the once-only priority and is by design digital, efficient, cost-effective, interoperable and secure. The solution comprises (i) a reliable and efficient decentralized mechanism for data sharing, capable of addressing the complexity of the processes and their high demand of resources;(ii) an ecosystem for delivering mobile services tailored to the needs of stakeholders;(iii) a single sign-on Wallet mechanism to manage transactions with multiple services;and (iv) an intercommunication layer, responsible for the secure exchange of information among existing eGovernment systems with newly developed ones. An indicative application scenario showcases the potential of our approach. © 2021, CC BY.

关键词： Electronic data interchange

Validation Methods to Promote Real-world Applicability of Machine Learning in Medicine 3

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Validation Methods to Promote Real-world Applicability of Ma...

3rd International Conference on Digital Medicine and Image Processing, DMIP 2020

作者： Bin Rafiq, Riyad Modave, Francois Guha, Shion Albert, Mark V. Department of Computer Science and Engineering University of North Texas DentonTX United States Department of Health Outcomes and Biomedical Informatics University of Florida United States Department of Computer Science Marquette University MilwaukeeWI United States

ISBN: (纸本)9781450389044

The impact of Artificial Intelligence (AI) on health care has been dramatic;however, there is a considerable degree of skepticism among clinicians about the real-world applicability of advanced predictive models;for this reason, it is particularly important to emphasize the need for proper model validation in machine learning. Often model skepticism is well-placed as modelers may overclaim the real-world replicability for their models, understate the known limitations, or simply not be aware of the hidden limits of the modeling approach. Educational approaches limited to rigorous and thorough justification of all model design decisions may not be practical given model complexity. This also becomes more challenging as state-of-the-art models with the highest benchmark accuracy are becoming less interpretable, e.g. ensemble methods or deep learning. However, in the same way that test-driven development has been a successful paradigm to navigate the complex coding landscape through a focus on testable results, we have observed a similar improvement in modeling strategy when the focus of a predictive model is driven by validation targets rather than more abstract, theoretical concerns. In this study, we provide an overview of the common limitations of model validation methods in medicine. We then present solutions to address such limitations, with a focus on strengthening the validity of predictive models. © 2020 ACM.

关键词： Deep learning