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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Chatterjee, Iman Goršič, Maja Kaya, Robert A. H. Erion, Collyn J. Clapp, Joshua D. Novak, Vesna D. University of Cincinnati Deptartment of Electrical and Computer Engineering Cincinnati United States University of Wisconsin Milwaukee College of Engineering & Applied Science Milwaukee United States University of Wyoming Department of Psychology Laramie United States University of Cincinnati Department of Electrical and Computer Engineering Cincinnati United States

ISBN: (纸本)9798350371499

Dyadic physiological responses are correlated with the quality of interpersonal processes - for example, the degree of "connectedness"in education and mental health counseling. Pattern recognition algorithms could be applied to such dyadic responses to identify the states of specific dyads, but such pattern recognition has primarily focused on classification. This paper instead uses regression algorithms to estimate three conversation aspects (valence, arousal, balance) from heart rate, skin conductance, respiration, and skin temperature. Data were collected from 35 dyads who engaged in 20 minutes of conversation, divided into 10 two-minute intervals. Each interval was rated with regard to conversation valence, arousal, and balance by an observer. When regression algorithms (support vector machines and Gaussian process regression) were trained on other data from the same dyad, they were able to estimate valence, arousal and balance with lower errors than a simple baseline estimator. However, when algorithms were trained on data from other dyads, errors were not lower than those of the baseline estimator. Overall, results indicate that, as long as training data from the same dyad are available, autonomic nervous system responses can be combined with regression algorithms to estimate multiple dyadic conversation aspects with some accuracy. This has applications in education and mental health counseling, though fundamental issues remain to be addressed before the technology is used in practice. © 2024 IEEE.

关键词： mHealth

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Applying Retrieval-Augmented Generation on Open LLMs for a Medical Chatbot Supporting Hypertensive Patients 3

Applying Retrieval-Augmented Generation on Open LLMs for a M...

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3rd AIxIA Workshop on Artificial Intelligence For Healthcare, HC@AIxIA 2024

作者： Aguzzi, Gianluca Magnini, Matteo Salcuni, Giuseppe Pio Ferretti, Stefano Montagna, Sara Department of Computer Science and Engineering University of Bologna Via dell'Università 50 Cesena Italy Department of Pure and Applied Sciences University of Urbino Piazza della Repubblica 13 Urbino Italy

Disease management, especially for chronic conditions or the elderly, involves continuous monitoring, lifestyle adjustments, and frequent healthcare interactions, necessitating effective home-care ICT solutions. To address these needs, chatbot technology has emerged as a promising tool for supporting patients in managing their health autonomously. In this context, chatbots must provide timely and accurate information and continuous empathetic support to maintain patient engagement. Additionally, data privacy concerns necessitate avoiding third-party Natural Language Processing and Generation services. To meet these needs, in this paper we propose the development of a chatbot to support patients in managing chronic conditions, focusing on hypertension. Particularly, we utilise open-source large language models to avoid proprietary systems due to privacy requirements. Given that their performance, based on state-of-the-art metrics, do not compete third-party services, we incorporate retrieval augmented generation (RAG) techniques, building a knowledge base with input from medical professionals to enhance model performance. We evaluated seven open-source models, including two specifically trained in the medical domain. Our results indicate that RAG significantly improves performance, surpassing that of specialised medical-domain models without RAG. This approach offers a promising solution for managing chronic conditions independently and securely. © 2024 CEUR-WS. All rights reserved.

关键词： Natural language processing systems

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Sand Cat Swarm Optimization with Deep Transfer Learning for Skin Cancer Classification

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computer Systems science & engineering 2023年第11期47卷 2079-2095页

作者： C.S.S.Anupama Saud Yonbawi G.Jose Moses E.Laxmi Lydia Seifedine Kadry Jungeun Kim Department of Electronics and Instrumentation Engineering V.R.Siddhartha Engineering CollegeVijayawada520007India Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Computer Science and Engineering University Institute of Engineering and Technology(UIET)Guru Nanak UniversityHyderabadIndia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Skin cancer is one of the most dangerous *** of the high melanoma death rate,skin cancer is divided into non-melanoma and *** dermatologist finds it difficult to identify skin cancer from dermoscopy images of skin ***,pathology and biopsy examinations are required for cancer *** studies have formulated computer-based systems for detecting skin cancer from skin lesion *** recent advancements in hardware and software technologies,deep learning(DL)has developed as a potential technique for feature ***,this study develops a new sand cat swarm optimization with a deep transfer learning method for skin cancer detection and classification(SCSODTL-SCC)*** major intention of the SCSODTL-SCC model lies in the recognition and classification of different types of skin cancer on dermoscopic ***,Dull razor approach-related hair removal and median filtering-based noise elimination are ***,the U2Net segmentation approach is employed for detecting infected lesion regions in dermoscopic ***,the NASNetLarge-based feature extractor with a hybrid deep belief network(DBN)model is used for ***,the classification performance can be improved by the SCSO algorithm for the hyperparameter tuning process,showing the novelty of the *** simulation values of the SCSODTL-SCC model are scrutinized on the benchmark skin lesion *** comparative results assured that the SCSODTL-SCC model had shown maximum skin cancer classification performance in different measures.

关键词： Deep learning skin cancer dermoscopic images sand cat swarm optimization machine learning

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Using Monte Carlo simulated PPGs signals to train a Deep Learning model to predict Hemoglobin levels

Using Monte Carlo simulated PPGs signals to train a Deep Lea...

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2023 Emerging Topics in Artificial Intelligence, ETAI 2023

作者： Alvarez, Michael Arzuaga, Emmanuel Sierra, Heidy Laboratory for Applied Remote Sensing Imaging and Photonics United States Department of Computer science & Engineering United States Department of Electrical and Computer Engineering United States University of Puerto Rico Mayaguez Puerto Rico

ISBN: (纸本)9781510665248

Measuring Hemoglobin (Hb) levels is required for the assessment of different health conditions, such as anemia, a condition where there are insufficient healthy red blood cells to carry enough oxygen to the body’s tissues. Measuring Hb levels requires the extraction of a blood sample, which is then sent to a laboratory for analysis. This is an invasive procedure that may add challenges to the continuous monitoring of Hb levels. Noninvasive techniques, including imaging and photoplethysmography (PPG) signals combined with machine learning techniques, are being investigated for continuous measurements of Hb. However, the availability of real data to train the algorithms is limited to establishing a generalization and implementation of such techniques in healthcare settings. In this work, we present a computational model based on Monte Carlo simulations that can generate multispectral PPG signals that cover a broad range of Hb levels. These signals are then used to train a Deep Learning (DL) model to estimate hemoglobin levels. Through this approach, valuable insights about the relationships between PPG signals, oxygen saturation, and Hb levels are learned by the DL model. The signals were generated by propagating a source in a volume that contains the skin tissue properties and the target physiological parameters. The source consisted of plane waves using the 660nm and 890 nm wavelengths. A range of 6 g/dL to 18dL Hb values was used to generate 468 PPGs to train a Convolutional Neural Network (CNN). The initial results show high accuracy in detecting low levels of Hb. To the best of our knowledge, the complexity of biological interactions involved in measuring hemoglobin levels has yet to be fully modeled. The presented model offers an alternative approach to studying the effects of changes in Hb levels on the PPGs signal morphology and its interaction with other physiological parameters that are present in the optical path of the measured signals. © 2023 SPIE.

关键词： Hemoglobin

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Strong magnon-magnon coupling and low dissipation rate in an all-magnetic-insulator heterostructure

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Physical Review applied 2024年第3期22卷 034017页

作者： Jiacheng Liu Yuzan Xiong Jingming Liang Xuezhao Wu Chen Liu Shun Kong Cheung Zheyu Ren Ruizi Liu Andrew Christy Zehan Chen Yifan Liu Ferris Prima Nugraha Xi-Xiang Zhang Dennis Chi Wah Leung Wei Zhang Qiming Shao Department of Electronic and Computer Engineering The IAS Center for Quantum Technologies The Department of Physics and Astronomy The Department of Applied Physics The Physical Science and Engineering Division (PSE) Department of Physics The

Magnetic insulators, such as yttrium iron garnets (YIGs), are important for spin-wave or magnonic devices as their low damping enables low-power dissipation. Magnetic insulator heterostructures can offer larger design space for realizing exotic magnonic quantum states, provided that individual layers have low damping and their exchange coupling is strong and engineerable. Here, we show that, in a high-quality all-insulator thulium iron garnet (TmIG)/YIG bilayer system, TmIG exhibits an ultralow dissipation rate thanks to its low-damping, low-saturation magnetization and strong orbital momentum. The low dissipation rates in both YIG and TmIG, along with their significant coupling strength due to interfacial exchange coupling, enable strong and coherent magnon-magnon coupling. The coupling strength can be tuned by varying the magnetic insulator layer thickness and magnon modes, which is consistent with analytical calculations and micromagnetic simulations. Our results demonstrate TmIG/YIG as a novel platform for investigating hybrid magnonic phenomena and open opportunities for magnon devices comprising all-insulator heterostructures.

关键词： Magnetic coupling Magnetic interactions Magnetization dynamics Magnons Spin waves Magnetic insulators Synthetic antiferromagnetic multilayers Transition metal oxides

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Satellite Image–Based Ecosystem Monitoring with Sustainable Agriculture Analysis Using Machine Learning Model

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Remote Sensing in Earth Systems sciences 2024年第4期7卷 764-773页

作者： Mulakaledu, Ajjanna Swathi, Baswaraju Jadhav, Makarand Mohan Shukri, Shakeerah Mohd Bakka, Vinod Jangir, Pradeep Department of English Koneru Lakshmaiah Education Foundation AP Vaddeswaram India Department of Computer Science and Engineering (Data Science) New Horizon College of Engineering Bengaluru India Department of Electronics and Telecommunication NBN Sinhgad Technical Institutes Campus Pune 411041 India Management and Science University Selangor Shah Alam Malaysia Koneru Lakshmaiah Education Foundation AP Vaddeswaram India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602 105 India Applied Science Research Center Applied Science Private University Amman Jordan

Understanding the variations in soil fertility and crop growth across time and geography is crucial for understanding the agricultural environment. Satellite and unmanned aerial remote sensing are the two main types of remote sensing methods used in agroecosystem monitoring. Through the collection of remote sensing photos, it is able to monitor as well as control agro-ecosystem environment in real-time. Spatial choice constraints are lessened by high-decision satellites, and satellite imagery processing is improved by use of artificial intelligence (AI) and machine learning methods, which enables computerised crop identification, disease diagnosis, and yield calculation. This research proposes novel technique in satellite image–based sustainable agriculture analysis with ecosystem monitoring using machine learning techniques. Here, the input is collected as satellite image and processed for noise removal and normalisation. Then, this image feature has been selected for analysis of crop growth using Gaussian belief kernel component analysis and classified using recursive Bayes probabilistic vector neural networks. Experimental analysis has been carried out in terms of training accuracy, precision, sensitivity, F-1 score, and AUC for various satellite image dataset. Proposed technique attained precision of 94%, sensitivity of 96%, AUC of 93%, training accuracy of 97%, and F1-score of 95%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Crop Growth Analysis Ecosystem Monitoring Machine Learning Techniques Satellite Image Sustainable Agriculture Analysis

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Toward Digital-Twin-Assisted Data Acquisition in Underwater Acoustic Sensor Networks

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Procedia computer science 2025年 257卷 241-248页

作者： Ivan Spajić Lars Michael Kristensen Volker Stolz Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences

Data transfer from underwater acoustic sensor networks (UASNs) to cloud services is challenging due to the severe bandwidth constraints of acoustic communication and energy consumption constraints of battery-powered sensor devices. To mitigate this problem, various forms of time series compression algorithms, both lossless and lossy, have been proposed in the literature. These proposals, however, focus on large time series whose in-memory buffering is not feasible in a UASN context. Furthermore, especially in oceanographic data acquisition, buffering large time series sacrifices the Age of Information. To address this gap, we evaluate a modern lossy compression algorithm, Mix-Piece, on small-sized time series. Motivated by our findings, we have developed the Custom-Piece algorithm, an adaptation of Mix-Piece that yields higher data compression at the expense of increased execution times. Our experimental evaluation of the Mix-Piece/Custom-Piece algorithms on real-world oceanographic data shows that compression ratios are highly dependent on the configuration of the algorithms due to the emerging characteristics of the underlying data sets. To facilitate practical use of the Mix-Piece/Custom-Piece algorithms, we outline how a digital twin may dynamically run simulations on available past data to support end-users in developing sensor configurations according to data acquisition requirements.

关键词： emerging networking wireless sensor networks applications optimization for effective communications lossy compression

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Noncrossing Longest Paths and Cycles 32

Noncrossing Longest Paths and Cycles

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32nd International Symposium on Graph Drawing and Network Visualization, GD 2024

作者： Aloupis, Greg Biniaz, Ahmad Bose, Prosenjit De Carufel, Jean-Lou Eppstein, David Maheshwari, Anil Odak, Saeed Smid, Michiel Tóth, Csaba D. Valtr, Pavel Khoury College of Computer Sciences Northeastern University BostonMA United States School of Computer Science University of Windsor Canada School of Computer Science Carleton University Ottawa Canada School of Electrical Engineering and Computer Science University of Ottawa Canada Computer Science Department University of California IrvineCA United States Department of Mathematics California State University Northridge Los AngelesCA United States Department of Computer Science Tufts University Medford United States Department of Applied Mathematics Charles University Prague Czech Republic

ISBN: (纸本)9783959773430

Edge crossings in geometric graphs are sometimes undesirable as they could lead to unwanted situations such as collisions in motion planning and inconsistency in VLSI layout. Short geometric structures such as shortest perfect matchings, shortest spanning trees, shortest spanning paths, and shortest spanning cycles on a given point set are inherently noncrossing. However, the longest such structures need not be noncrossing. In fact, it is intuitive to expect many edge crossings in various geometric graphs that are longest. Recently, Álvarez-Rebollar, Cravioto-Lagos, Marín, Solé-Pi, and Urrutia (Graphs and Combinatorics, 2024) constructed a set of points for which the longest perfect matching is noncrossing. They raised several challenging questions in this direction. In particular, they asked whether the longest spanning path, on any finite set of points in the plane, must have a pair of crossing edges. They also conjectured that the longest spanning cycle must have a pair of crossing edges. In this paper, we give a negative answer to the question and also refute the conjecture. We present a framework for constructing arbitrarily large point sets for which the longest perfect matchings, the longest spanning paths, and the longest spanning cycles are noncrossing. © Greg Aloupis, Ahmad Biniaz, Prosenjit Bose, Jean-Lou De Carufel, David Eppstein, Anil Maheshwari, Saeed Odak, Michiel Smid, Csaba D. Tóth, and Pavel Valtr.

关键词： Trees (mathematics)

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Virtuous, multi-level integration of research and education within the project "european Digital Dynamic Mapping" (EDDY) Excellent applied research as an enabler for excellent education in the context of Project-Based Learning in Higher Education Institutions

Virtuous, multi-level integration of research and education ...

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2023 Designing Futures: Zukunfte gestalten, INFORMATIK 2023 - 2023 Designing Futures: Shaping the Future, INFORMATIK 2023

作者： Rettig, Rasmus Weltz, Maximilian Hamburg University of Applied Sciences Faculty of Engineering and Computer Science Department of Information and Electrical Engineering Berliner Tor 7 Hamburg20099 Germany

ISBN: (纸本)9783885797319

Project-and Problem-Based Learning has been subject to research and implementation in engineering and computer science curricula for about the last 20 years. However, the projects and problems focused on in education have hardly been questioned for their relevance and effect. Considering current global and financial challenges, the authors propose to revise project-and problem-based approaches in education in the context of relevance and excellence in applied research. Besides coping with current cost-cutting, existing control mechanisms could ensure both relevance and excellence. Example projects based on more than 10 years of hands-on experience in Project-Based Learning in the context of externally funded research, for various classroom situations are included. © 2023 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： Autonomous vehicles

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An Efficient Steganographic Approach for Securing Text Transmission Using S-Box in Cloud 2

An Efficient Steganographic Approach for Securing Text Trans...

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2nd International Conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Ashraf, Humaira Malik, Javeria Ihsan, Uswa Al-Quayed, Fatima Humayun, Mamoona Jhanjhi, N.Z. International Islamic University Department of Computer Science and Software Engineering Islamabad Pakistan Department of Computer Science College of Computer and Information Sciences Jouf University Sakakah Saudi Arabia Department of Information Systems College of Computer and Information Sciences Jouf University Sakakah Saudi Arabia Taylor's University Malaysia Applied Science Research Center Applied Science Private University Amman11937 Jordan

ISBN: (纸本)9798350335644

In era of modern world and technology where everything is digitalized. Cloud computing emerged as one of the fastest growing parts of digital industry. With the Succor of cloud computing models, business accomplishes their objectives with least exertion when contrasted with traditional processing environment. In spite of these compensations, yet security of the information in cloud database is the significant fear in endorsement of cloud. Although several techniques have been proposed such as cryptographic and steganographic approaches, but all of these have some loopholes. Therefore, in this paper new data protection technique based on steganographic encryption is proposed which has less computational time and secure against known plain text and Man-In-Middle Attack. © 2023 IEEE.

关键词： Cryptography

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