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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Cyrus Eierud Zening Fu Helen Petropoulos Anastasia Bohsali Armin Iraji Melanie Ganz Cyril Pernet Vince Calhoun TReNDS Center Georgia State University Georgia Institute of Technology Emory University Atlanta GA United States Department of Computer Science University of Copenhagen Copenhagen Denmark Neurobiology Research Unit Rigshospitalet Copenhagen Denmark

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Positron emission tomography (PET) tracer binding may not be aligned with commonly used parcellations of neocortex [1]. Independent component analysis (ICA) can capture coactivated regions among participants that might serve as robust templates from a data-driven perspective. NeuroMark is a framework combining pre-defined templates with spatially constrained ICA, capturing a wide range of brain markers across imaging modalities [2],[3]. Here, we build NeuroMark PET beta-amyloid templates for the 18F-florbetapir (FBP) and the 18F-florbetaben (FBB) radioligands, aiming to provide reliable spatial priors for future PET studies using ICA. Measuring the spatial similarities using correlation, the templates for the NeuroMark FBP and FBB templates matched strongly (ρ > 0.4) for 18 components. In a final step, the NeuroMark FBP template is applied on both FBB and FBP radioligands, showing that the age correlate profile across the FBB and FBP radioligands are statistically similar (p < 0.0008). The overall results demonstrate that NeuroMark ICA analyses are fully automated and the proposed PET templates would have great potential for large-scale analysis studies.

关键词： Brain Correlation Automation Independent component analysis Reliability Positron emission tomography Epidemiology Engineering in medicine and biology

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WEIGHTED SUM OF SEGMENTED CORRELATION: AN EFFICIENT METHOD FOR SPECTRA MATCHING IN HYPERSPECTRAL IMAGES

arXiv

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arXiv 2024年

作者： Soor, Sampriti Kumari, Priyanka Sagar, B.S. Daya Shetty, Amba School of Computer Engineering Kalinga Institute of Industrial Technology Bhubaneswar India Department of Water Resources and Ocean Engineering NIT Karnataka Surathkal India Systems Science and Informatics Unit Indian Statistical Institute Bangalore India

Matching a target spectrum with known spectra in a spectral library is a common method for material identification in hyperspectral imaging research. Hyperspectral spectra exhibit precise absorption features across different wavelength segments, and the unique shapes and positions of these absorptions create distinct spectral signatures for each material, aiding in their identification. Therefore, only the specific positions can be considered for material identification. This study introduces the Weighted Sum of Segmented Correlation method, which calculates correlation indices between various segments of a library and a test spectrum, and derives a matching index, favoring positive correlations and penalizing negative correlations using assigned weights. The effectiveness of this approach is evaluated for mineral identification in hyperspectral images from both Earth and Martian surfaces. © 2024, CC BY-NC-ND.

关键词： Hyperspectral imaging

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Solving Generalized Grouping Problems in Cellular Manufacturing Systems Using a Network Flow Model

arXiv

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arXiv 2024年

作者： Uddin, Md Kutub Islam, Md Saiful Jahin, Md Abrar Seam, Md Saiful Islam Mridha, M.F. Department of Mechanical Engineering Khulna University of Engineering & Technology Khulna9203 Bangladesh Department of Industrial Engineering and Management Khulna University of Engineering & Technology Khulna9203 Bangladesh Physics and Biology Unit Okinawa Institute of Science and Technology Graduate University Okinawa904-0412 Japan Department of Computer Science American International University Bangladesh Dhaka1229 Bangladesh

This paper focuses on the generalized grouping problem in the context of cellular manufacturing systems (CMS), where parts may have more than one process route. A process route lists the machines corresponding to each operation of the part. Inspired by the extensive and widespread use of network flow algorithms, this research formulates the process route family formation for generalized grouping as a unit capacity minimum cost network flow model. The objective is to minimize dissimilarity (based on the machines required) among the process routes within a family. The proposed model optimally solves the process route family formation problem without pre-specifying the number of part families to be formed. The process route of family formation is the first stage in a hierarchical procedure. For the second stage (machine cell formation), two procedures, a quadratic assignment programming (QAP) formulation, and a heuristic procedure, are proposed. The QAP simultaneously assigns process route families and machines to a pre-specified number of cells in such a way that total machine utilization is maximized. The heuristic procedure for machine cell formation is hierarchical in nature. Computational results for some test problems show that the QAP and the heuristic procedure yield the same results. © 2024, CC BY.

关键词： Cellular manufacturing

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A STUDY ON INTERIOR Γ-HYPERFILTERS IN ORDERED Γ-SEMIHYPERGROUPS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2022年第1期84卷 71-80页

作者： Chen, C. Kosari, S. Omidi, S. Davvaz, B. Akhoundi, M. Institute of Software School of Electronics Engineering and Computer Sciences Peking University Beijing100871 China Institute of Computing Science and Technology Guangzhou University Guangzhou510006 China Ministry of Education Iran Department of Education in Tehran Tehran Iran Department of Mathematics Yazd University Yazd Iran Clinical Research Development Unit of Rouhani Hospital Babol University of Medical Sciences Babol Iran

In this paper, interior Γ-hyperfilters of ordered Γ-semihypergroups are de- fined and various types of them are studied. Results related to productional ordered Γ- semihypergroups were investigated. Moreover, we investigate some properties of the in- verse images of strong interior Γ-hyperfilters in ordered Γ-semihypergroups. Finally, we discuss the relationship between two fundamental notions of ordered Γ-semihypergroup, the several types of interior Γ-hyperfilters and the (completely) prime interior Γ-hyperideals. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： (completely) prime I-Γ-hyperfilter Ordered Γ-semihypergroup Strong I-Γ-hyperfilter Weak I-Γ-hyperfilter

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Prediction of Adsorption and Desorption Isotherms for Atmospheric Water Harvesting

Prediction of Adsorption and Desorption Isotherms for Atmosp...

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Learning and technology Conference (L&T)

作者： Narjisse Kabbaj Mohamed F. El-Amin Electrical and Computer Engineering Department Effat College of Engineering Energy and Technology Research Center Effat University Jeddah Saudi Arabia Natural Science Math and Tech Unit Effat College of Engineering Energy and Technology Research Center Effat University Jeddah Saudi Arabia

This study improves the mathematical modeling for the potential of atmospheric water harvesting (AWH) using desiccant materials. This research is crucial in highlighting the sustainable water management strategies of AWH systems in converting atmospheric moisture into a vital water source. The primary focus of our research methodology was the analytical derivation of sorption isotherms, essential for the hygrothermal simulation of desiccant materials. This was accomplished through the application of two established models, namely, the Guggenheim-Anderson-de Boer (GAB) and Van Genuchten (VG). Experimental data on various anhydrous salts from existing literature have been used. An in-depth comparative analysis of these models reveals that the VG model aligns more closely with the experimental data, thus asserting its superiority in enhancing the selection and efficiency of desiccant materials in AWH systems. By confirming the VG model’s superiority in accurately modeling sorption isotherms, our research not only improves the model of AWH systems but also, importantly, contributes to the development of advanced water harvesting technologies.

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Photon orbits and phase transitions in Kiselev-AdS black holes from gravity

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The European Physical Journal C 2024年第8期84卷 1-13页

作者： Sood, Ashima Kumar, Arun Singh, J. K. Ghosh, Sushant G. Centre for Theoretical Physics Jamia Millia Islamia New Delhi India Department of Mathematics Netaji Subhas University of Technology New Delhi India Institute for Theoretical Physics and Cosmology Zhejiang University of Technology Hangzhou China Astrophysics and Cosmology Research Unit School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Durban South Africa

The acceleration observed in cosmological expansion is often attributed to negative pressure, potentially arising from quintessence. We explore the relationship between the photon orbit radius and the phase transition of spherical AdS black holes in f(R, T) gravity influenced by quintessence dark energy, specifically Kiselev-AdS black holes in f(R, T) gravity. We are treating the negative cosmological constant $$\Lambda $$ as the system’s pressure to examine the impact of the state parameter $$\omega $$ and the f(R, T) gravity parameter $$\gamma $$ . Interestingly, Kiselev-AdS black holes within the f(R, T) gravity framework exhibit a van der Waals-like phase transition. In contrast, these black holes display a Hawking–Page-like phase transition in general relativity. We demonstrate that below the critical point, the black hole undergoes a first-order vdW-like phase transition, with $$r_{ps}$$ and $$u_{ps}$$ serving as order parameters exhibiting a critical exponent of 1/2, similar to ordinary thermal systems. It suggests that $$r_{ps}$$ and $$u_{ps}$$ can serve as order parameters in characterizing black hole phase transitions, hinting at a potentially universal gravitational relationship near critical points within black hole thermodynamic systems. Investigating the correlation between photon sphere radius and thermodynamic phase transitions provides a valuable means of distinguishing between different gravity theory models, ultimately shedding light on the nature of dark energy. Finally, as $$\gamma $$ tends towards zero, our results precisely align with those of Kiselev-AdS black holes.

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Brain-Controlled computer Tasks for Paralyzed Persons: Framework Overview

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Procedia computer science 2024年 237卷 28-35页

作者： Amna Imran Haider Chaudhary Maimoona Tariq Zahra Ali Abdul Ahad Hammad Naqvi Paulo Jorge Coelho Ivan Miguel Pires Knowledge Unit of Science and Technology University of Management and Technology Sialkot Pakistan School of Software Northwestern Polytechnical University Xian Shaanxi 710072 P. R. China Department of Computer Science Istanbul Technical University Turkey Polytechnic of Leiria Leiria Portugal Institute for Systems Engineering and Computers at Coimbra Coimbra Portugal Instituto de Telecomunicações Universidade da Beira Interior Covilhã Portugal

To bridge the digital barrier between those with disabilities and those without impairments, several applications can be operated by brain signals. It highlights the importance of employing brain-computer interfaces (BCI) and mentions a specific system called the "Brain-Controlled computer System" that can control a computer cursor and perform mouse actions using brain signals.. The system can control the cursor and provide mouse left/right click with brain signals using a low-cost Brainlink Lite device. Based on this system, we employed machine learning and deep learning methodologies to develop a system that classifies brain signals for cursor movement. The methodology involved gathering user input through surveys, interviews, and comparison studies, as well as utilizing pre-developed datasets collected using a mind sensor. We initially trained a model on a previous dataset, achieving approximately 70% accuracy. However, when applied to the new dataset, the accuracy dropped to 49%. To improve the results, we experimented with more complex models, including additional layers and a dropout layer to prevent overfitting. Despite these enhancements, the accuracy only reached a maximum of 52%. The research team collected a dataset tailored to their specific application. They made a groundbreaking discovery by applying a convolutional neural network (CNN), typically used for image analysis, to process continuous brainwave data. Despite this non-standard use, their hypothesis proved correct, with the CNN model achieving an impressive 80% accuracy in classifying brain signals for controlling a cursor.

关键词： Brain-Controlled Brainlink Lite EEG Machine Learning Deep learning

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Collective excitations of a Bose-condensed gas: Fate of second sound in the crossover regime between hydrodynamic and collisionless regimes

arXiv

引用

arXiv 2023年

作者： Hiyane, Hoshu Watabe, Shohei Nikuni, Tetsuro Quantum Systems Unit Okinawa Institute of Science and Technology Graduate University Okinawa Onna904-0495 Japan Department of Physics Tokyo University of Science Shinjuku Tokyo162-8601 Japan Faculty of Engineering Computer Science and Engineering Shibaura Institute of Technology Toyosu Tokyo135-8548 Japan

We develop the moment method for Bose–Einstein condensates at finite temperatures that enable us to study collective sound modes from the hydrodynamic to the collisionless regime. In particular, we investigate collective excitations in a weakly interacting dilute Bose gas by applying the moment method to the Zaremba–Nikuni–Griffin equation, which is the coupled equation of the Boltzmann equation with the generalized Gross–Pitaevskii equation. Utilizing the moment method, collective excitations in the crossover regime between the hydrodynamic and collisionless regimes are investigated in detail. In the crossover regime, the second sound mode loses the weight of the density response function because of the significant coupling with incoherent modes, whereas the first sound shows a distinct but broad peak structure. We compare the result obtained by the moment method with that of the Landau two-fluid equations and show that the collective mode predicted by the Landau two-fluid equations well coincides with the result from the moment method even far from the hydrodynamic regime, whereas clear distinction also emerges in the relatively higher momentum regime. Copyright © 2023, The Authors. All rights reserved.

关键词： Method of moments

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Suggesting Exit Path in a Multi-Path in Case of an Emergency

Suggesting Exit Path in a Multi-Path in Case of an Emergency

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： M S Vignesh Nikhil Kumar Adwitiya Mukhopadhyay Pooja Rani Manoj Kumar Pallavi Joshi Department of Computer Science Amrita School of Computing Amrita Vishwa Vidyapeetham Mysuru India School of Engineering and Technology BML Munjal University Gurugram India Founder VSPP Tech LLC Texas USA School of Computer Science FEIS University of Wollongong in Dubai Dubai UAE MEU Research Unit Middle East University Amman Jordan

This study proposes an innovative approach to address the challenges of navigating multi-exit scenarios during emergencies by utilizing the VGG19 model and incorporating voice guidance. A crucial component of this research is the extensive CubiCasa5K dataset, comprising 5,000-floor plans with detailed annotations, including exit paths and structural information from diverse indoor environments. These floor plans serve as a valuable resource for generating synthetic images of exit paths within various buildings. The synthetic images undergo pre-processing and are inputted into the VGG19 model for feature extraction and exit path classification. To enhance user experience, a text-to-speech synthesis system is integrated, generating a tailored voice message offering clear and concise instructions based on the VGG19’s classification of the exit path. The solution achieves an impressive accuracy of 94.96%, promising to significantly improve individual safety by providing accurate and timely guidance in complex emergency situations.

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Study of Supervised Learning Algorithms for the Prediction of Road Accident Severity in Senegal 7

Study of Supervised Learning Algorithms for the Prediction o...

引用

7th International Conference on Computational Intelligence and Applications, ICCIA 2022

作者： Dia, Yoro Faty, Lamine Sarr, Moussa Dethie Sall, Ousmane Bousso, Mamadou Landu, Tony Tona UFR-SET Iba der Thiam University of Thies Thies Senegal Assane Seck University of Ziguinchor Computer Science and Engineering Laboratory for Innovation Ziguinchor Senegal Digital Unit-Science Technology and Digital Pole Virtual University of Senegal Dakar Senegal UFR-SES Iba der Thiam University of Thies Thies Senegal

ISBN: (纸本)9781665495844

According to a literature search, current studies on road accidents in Senegal are mostly conducted using conventional descriptive statistics, which, however, does not correctly identify cause and effect relationships and is unable to establish models that could predict accidents. An alternative way to reduce traffic accidents is to develop a model for predicting accident fatality. This model relates the severity of accidents to the main actors involved, namely the driver, the vehicle and the various characteristics of the road environment. This paper presents a study of several models for predicting the severity of traffic accidents in Senegal based on supervised learning algorithms such as Random Forest, k-nearest neighbor, SVM, logistic regression and naive Bayesian classifier, in order to estimate the accident severity from historical data. To solve the problem of unbalanced classes, we use several measures of models' performance namely percentage performance (Accuracy), area under the ROC curve, accuracy, Recall and F1 criterion. The best results were obtained by the Random Forest and SVM algorithms respectively, based on the percentage performance and the F1 criterion. Regarding the value of the area under the ROC curve, the best results were obtained by Random Forests and K-nearest neighbor algorithms, respectively. The Random Forests algorithms, which give the best results in model practice, can be used in studies on the prediction of road accident severity. © 2022 IEEE.

关键词： Decision trees

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