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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Atsushi Isozaki Kazuki Fukae Kenichi Arai Toru Kobayashi Masahide Nakamura Computer and Information Science Program Graduate School of Engineering Nagasaki University Nagasaki Japan Division of Electrical Engineering and Computer Science Graduate School of Engineering Nagasaki University Nagasaki Japan Center of Mathematical and Data Sciences Kobe University Hyogo Japan

ISBN: (纸本)9781665492331

This study is related to a system that enables elderly people to communicate interactively with young people who use existing message exchange services by simply speaking to an avatar on a tablet PC, without having to perform complicated operations of the tablet PC. On the other hand, the young people side can bring in elderly people who could not previously participate in existing message exchange services groups. The effectiveness of the system was verified through demonstration experiments with two households consisting of elderly people in their 80s.

关键词： Economics Avatars Older adults Usability Smart phones Consumer electronics Commercialization

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Optimization Process of Glycerol Esterification Using Real Time Adaptive Control

Optimization Process of Glycerol Esterification Using Real T...

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International Conference on Advanced computer Science and Information Systems

作者： Iwan Aang Soenandi Ani Suryani Taufik Djatna Irzaman Post Graduate Program of Agro-industrial Technology Bogor Agricultural University Dramaga Indonesia Lecturer Faculty of Engineering and Computer Science Krida Wacana Christian University Post Graduate Program of Agro-industrial Technology Bogor Agricultural University. Dramaga Indonesia Post Graduate Program of Agro-industrial Technology and Graduate Program of Computer Science Bogor Agricultural University. Dramaga Indonesia Department of Physics Faculty Mathematics and Natural Sciences Bogor Agricultural University. Dramaga Indonesia

ISBN: (纸本)9781509003648

The synthesis reaction used in esterification needs high energy consumption and a precise processing time to get the best yield of target. In this study, a model was formulated to optimize glycerol esterification process by minimizing the time needed for the process and maximizing the yield of Mono-glycerides. This optimization has gained importance for boosting the esterification industry and improving the production efficiency. Optimization through adaptive monitoring and control has provided significant advances in the process efficiency, a lower energy consumption and a better product quality. This paper presents the optimization with a computational algorithm in real time and adaptive control (RTAC), as compared to the conventional (traditional) methods to monitor and control of glycerol esterification processes. The identification of esterification status based on temperature and time are evaluated to strengthen the optimization. An adaptive method as feature selection to select wavelength IR sensors at specified intervals was carried out with Relief algorithm and Adaptive Pillar K-means clustering method to set the parameter control was proposed in this paper. Many combinations were evaluated from real time condition process, to achieve the best optimization results. The experimental results demonstrate that real time adaptive control can be achieved by using three clusters, which are heating up, stabilizing and finishing. In RTAC, each cluster has its own parameter to set the control point by the servo motor that was attached to magnetic stirrer-heater. By using optimization parameter for each cluster, esterification process time can be shortened by 15-20 minutes with a higher yield (7% or more), lower range stirrer rotation (300rpm-450 rpm) and a lower final temperature of 200℃ - 210℃.

关键词： Optimization Real Time Adaptive Control Glycerol Esterification

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Classification of Highly Similar Fish Species Using Machine Learning

Classification of Highly Similar Fish Species Using Machine ...

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International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Leandro Magno C. Silva Franklin Cesar Flores Rosilene Luciana Delariva Gustavo Z. Felipe Yandre M. G. Da Costa Graduate Program in Computer Science State University of Maringá Federal Institute of Paraná Maringá Brazil Department of Informatics State University of Maringá Maringá Brazil Center for Biological and Health Sciences State University of Western Paraná Cascavel Brazil Graduate Program in Computer Science State University of Maringá Maringá Brazil

ISBN: (数字)9798350391886

ISBN: (纸本)9798350391893

Fish species inventory and monitoring is a timely concern due to the increasing environmental imbalance. In this sense, the development of machine learning strategies aiming to support automatic fish species identification is an important contribution, both in environmental and scientific terms. This study explores handcrafted features aiming to perform fish species identification in a quite challenging scenario, in which the inter-classes differences are minimal, as the species belong to the same family considering the hierarchy of biological classification (i.e. Characidae). For this purpose, it is proposed a set of features designed properly, aiming to capture visual properties closely related to each species that are difficult to be noted by experts in this domain of investigation. An additional contribution of this work is a dataset of 4870 images taken from 416 individuals from nine fish species. The Region of Interest (RoI) corresponding to the fish body is segmented, and horizontal and vertical histograms are collected from each sample, aiming to capture information related to the body shape, and other characteristics particular to each species. Experiments are performed using the Support Vector Machine (SVM), K-Nearest Neighbours (K-NN), Random Forest and Naive-Bayes classifiers and, in the best scenario, it is obtained an accuracy rate of 99%. This result corroborates the hypothesis that the use of handcrafted features specifically developed for this type of application can be quite effective in addressing this classification problem.

关键词： Support vector machines Image segmentation Visualization Histograms Image recognition Shape Fish

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Terahertz Cavity Phonon Polaritons in Lead Telluride in the Deep-Strong Coupling Regime

arXiv

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arXiv 2025年

作者： Baydin, Andrey Manjappa, Manukumara Mishra, Sobhan Subhra Xu, Hongjing Doumani, Jacques Tay, Fuyang Kim, Dasom Rappl, Paulo H.O. Abramof, Eduardo Singh, Ranjan Hernandez, Felix G.G. Kono, Junichiro Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Smalley–Curl Institute Rice University HoustonTX77005 United States Rice Advanced Materials Institute Rice University HoustonTX77005 United States Instrumentation and Applied Physics Department Indian Institute of Science Bangalore560012 India Center for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University 639798 Singapore Department of Physics and Astronomy Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley–Curl Institute Rice University HoustonTX77005 United States Group of Research and Development in Materials and Plasma National Institute for Space Research São José dos Campos São Paulo12201-970 Brazil Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 637371 Singapore Instituto de Física Universidade de São Paulo São Paulo05508-090 Brazil Department of Material Science and NanoEngineering Rice University HoustonTX77005 United States

Lead telluride is an important thermoelectric material due to its large Seebeck coefficient combined with its unusually low thermal conductivity that is related to the strong anharmonicity of phonons in this material. Here, we have studied the resonant and nonperturbative coupling of transverse optical phonons in lead telluride with cavity photons inside small-mode-volume metallic metasurface cavities that have photonic modes with terahertz frequencies. We observed a giant vacuum Rabi splitting on the order of the bare phonon and cavity frequencies. Through terahertz time-domain spectroscopy experiments, we systematically studied the vacuum Rabi splitting as a function of sample thickness, temperature, and cavity length. Under the strongest light–matter coupling conditions, the strength of coupling exceeded the bare phonon and cavity frequencies, putting the system into the deep-strong coupling regime. These results demonstrate that this uniquely tunable platform is promising for realizing and understanding predicted cavity-vacuum-induced ferroelectric instabilities and exploring applications of light–matter coupling in the ultrastrong and deep-strong coupling regimes in quantum technology. Copyright © 2025, The Authors. All rights reserved.

关键词： Phonons

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Decision fusion of circulating markers for breast cancer detection in premenopausal women

Decision fusion of circulating markers for breast cancer det...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Jesneck, Jonathan L. Mukherjee, Sayan Nolte, Loren W. Lokshin, Anna E. Marks, Jeffrey R. Lo, Joseph Department of Biomedical Engineering Department of Statistical Science Computational Biology and Bioinformatics Program Duke Advanced Imaging Labs. Institute for Genome Sciences and Policy Department of Computer Science Duke University Department of Electrical and Computer Engineering Division of Hematology/Oncology University of Pittsburgh School of Medicine University of Pittsburgh Cancer Institute Pittsburgh PA 15213 United States Department of Experimental Surgery Duke University Medical Center Medical Physics Graduate Program Duke University Durham NC 27708 United States

ISBN: (纸本)1424415098

Current mammographic screeningfor breast cancer is less effective for younger women. To complement mammography for premenopausal women, we investigated the feasibility screening test using 98 blood serum proteins. Because the data set was very noisy and contained only weak features, we used a classifier designed for noisy data: decision fusion. Decision fusion outperformed both a support vector machine (SVM) and linear regression with forward stepwise feature selection on all three two-class classification tasks: normal tissue vs. cancer, normal tissue vs. benign lesions, and benign lesions vs. cancer. Decision fusion detected cancer moderately well (AUC=0.84 on normal vs. cancer), demonstrating promise as a screening tool. Decision fusion also detected benign lesions similarly well (AUC=0.83 on normal vs. benign lesions) and was the only classifier to achieve any success in separating benign from malignant lesions (AUC=0.64 on benign vs. cancer). The classification results suggest that the assayed proteins are more indicative of a secondary effect, such as immune response, rather than specific for breast cancer. In conclusion, the decision fusion classifier demonstrated some promise in detecting breast lesions and outperformed other classifiers, especially for the very noisy classification problem of distinguishing benign from malignant lesions. ©2007 IEEE.

关键词： Tissue

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High-Resolution Imaging of Human Cancer Proteins Using Microprocessor Materials

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ChemBioChem 2022年第17期23卷 e202200310-e202200310页

作者： Solares, Maria J. Jonaid, G.M. Luqiu, William Y. Berry, Samantha Khadela, Janki Liang, Yanping Evans, Madison C. Pridham, Kevin J. Dearnaley, William J. Sheng, Zhi Kelly, Deborah F. Molecular Cellular and Integrative Biosciences Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park 16802 PA United States Bioinformatics and Genomics Graduate Program Huck Institutes of the Life Sciences Pennsylvania State University University Park 16802 PA United States Department of Biomedical Engineering Pennsylvania State University University Park 16802 PA United States Center for Structural Oncology Pennsylvania State University University Park 16802 PA United States Department of Electrical and Computer Engineering Duke University Durham 27708 NC United States Fralin Biomedical Research Institute at VTC Virginia Tech Roanoke 24016 VA United States

Mutations in tumor suppressor genes, such as Tumor Protein 53 (TP53), are heavily implicated in aggressive cancers giving rise to gain- and loss-of-function phenotypes. While individual domains of the p53 protein have been studied extensively, structural information for full-length p53 remains incomplete. Functionalized microprocessor chips (microchips) with properties amenable to electron microscopy permitted us to visualize complete p53 assemblies for the first time. The new structures revealed p53 in an inactive dimeric state independent of DNA binding. Residues located at the protein-protein interface corresponded with modification sites in cancer-related hot spots. Changes in these regions may amplify the toxic effects of clinical mutations. Taken together, these results contribute advances in technology and imaging approaches to decode native protein models in different states of activation. © 2022 Wiley-VCH GmbH.

关键词： cancer electron microscopy microchips p53, molecular modeling

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Validation of a gamified framework for teaching and learning for algorithms subject from a control group

Validation of a gamified framework for teaching and learning...

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Frontiers in Education (FIE) Conference

作者： José Augusto de Sena Quaresma Sandro Ronaldo Bezerra Oliveira Marianne Kogut Eliasquevici Graduate Program in Creativity and Innovation in Higher Education Methodologies (PPGCIMES) Federal University of Pará (UFPA) Belém Brazil Graduate Program in Computer Sciense (PPGCC) Institute of Exact and Natural Sciences (ICEN) Federal University of Pará (UFPA) Belém Brazil

ISBN: (数字)9781728189611

ISBN: (纸本)9781728189628

This Research to Practice Full Paper presents the gamification as a teaching and learning practice that can be applied as a positive result allowing students to develop the necessary skills for the content of the Algorithms subject. In this context, we have as a guiding question for this work: How to validate a gamified framework for the Algorithms subject or equivalent for undergraduate courses in Information Technology? Thus, the main goal of this work is to validate the gamified approach proposed for the Algorithms subject in undergraduate courses in Information Technology. The gamified framework for the Algorithms subject or equivalent is an alternative to the teaching and learning process, which provides greater performance, as well as a motivation for students to be interacting in their learning process. Through the validation process, we can see that compared to the previously acquired grades, students achieved a higher performance. In addition, through the analysis within the same class between forms in the professor's practice, that is, the comparison of how the subject is taught with the gamified approach, we perceive a greater engagement of the students for the delivery of activities and participation in the class.

关键词： Education Games programming profession Information technology Tools Visualization Training

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Genetic programming Theory and Practice XX 1

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丛书名： Genetic and Evolutionary Computation

1000年

作者： Stephan Winkler Leonardo Trujillo Charles Ofria Ting Hu

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DRYING OF REFRACTORY CASTABLES - HOW COMPLEX THE MODELLING NEEDS TO BE? A NUMERICAL AND EXPERIMENTAL STUDY 17

DRYING OF REFRACTORY CASTABLES - HOW COMPLEX THE MODELLING N...

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17th Unified International Technical Conference on Refractories, UNITECR 2022

作者： Moreira, M.H. Pont, S. Dal Ausas, R.F. Cunha, T.M. Luz, A.P. Pandolfelli, V.C. Federal University of Sao Carlos Graduate Program in Materials Science and Engineering SP Sao Carlos Brazil CNRS Grenoble INP 3SR Université Grenoble Alpes Grenoble38000 France Institute of Mathematical and Computer Sciences University of São Paulo SP São Carlos13566-590 Brazil

Calcium aluminate cement (CAC)bonded castables have numerous benefits when compared to monolithic refractories. Their main drawback is their long initial heating, when the physical and chemically-bonded water are released. If the mass flux of water to the ambient is lower than the vapor generation, the gas pressure can increase well above the material's strength resulting in cracks and spalling of the ceramic lining. In order to avoid this, optimized heat up curves are needed, and one promising methodology by using numerical models. Most of these calculations are based on tools used for simulating Portland cement concrete structures on fire and they vary both in complexity and their basic assumptions. Thus, the main question that remains is how complex such models need to be in order to capture the fundamental aspects of this phenomenon. The present work aimed to solve this issue by implementing multiple numerical tools reported in the literature with distinct complexity levels and fundamental assumptions and by also conducting neutron tomography tests on a CAC-bonded castable. It was possible to see that the pressure values predicted by such methodologies are equivalent and the water content predicted is qualitatively similar within the models and with the experimental values, indicating that the simplest approach might be used for predicting the castables' drying. © 2022 Unified International Technical Conference on Refractories, UNITECR 2022 - Proceedings. All rights reserved.

关键词： Portland cement

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Interpreting cabinet approval ratings by neural networks

Interpreting cabinet approval ratings by neural networks

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IASTED International Conference on Artificial Intelligence and Applications, AIA 2007

作者： Kamimura, Ryotaro Yoshida, Fumihiko Kitajima, Ryozo Information Science Laboratory Information Technology Center Tokai University 1117 Kitakaname Hiratsuka Kanagawa 259-1292 Japan Department of Media Studies Tokai University 1117 Kitakaname Hiratsuka Kanagawa 259-1292 Japan Graduate Program in Computer Sciences Tokai University 1117 Kitakaname Hiratsuka Kanagawa 259-1292 Japan

ISBN: (纸本)9780889866317

In this paper, we try to estimate Japan's cabinet approval ratings by using neural networks. In addition, we try to extract the important features in input patterns. This is the first attempt to use neural networks and to interpret the mechanism of inference for approval estimation in a comprehensive way. Experimental results show that neural networks have much better performance than that obtained by the standard regression analysis in terms of training and testing errors. The information loss analysis reveals that the first variable, that is, the previous ratings should play the most important role in inference. Though the experimental result here shown is a preliminary one, it certainly suggests a possibility of the automatic inference of cabinet approval ratings.

关键词： Feature extraction

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