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Mitigating errors in mobile-based dietary assessments: Effects of a data modification process on the validity of an image-assisted food and nutrition app

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Nutrition 2023年 116卷 112212-112212页

作者： Ho, Dang Khanh Ngan Chiu, Wan-Chun Kao, Jing-Wen Tseng, Hsiang-Tung Yao, Chih-Yuan Su, Hsiu-Yueh Wei, Pin-Hui Le, Nguyen Quoc Khanh Nguyen, Hung Trong Chang, Jung-Su School of Nutrition and Health Sciences College of Nutrition Taipei Medical University Taipei Taiwan Department of Nutrition Wan Fang Hospital Taipei Medical University Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Dietetics Taipei Medical University Hospital Taipei Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Research Center for Artificial Intelligence in Medicine Taipei Medical University Taipei Taiwan Translational Imaging Research Center Taipei Medical University Hospital Taipei Taiwan Department of Adult Nutrition Counselling National Institute of Nutrition Hanoi Viet Nam Department of Clinical Nutrition and Dietetics National Hospital of Endocrinology Hanoi Viet Nam Graduate Institute of Metabolism and Obesity Sciences College of Nutrition Taipei Medical University Taipei Taiwan Nutrition Research Center Taipei Medical University Hospital Taipei Taiwan Chinese Taipei Society for the Study of Obesity (CTSSO) Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

Objective: Mobile nutrition applications (apps) provide a simple way for individuals to record their diet, but the validity and inherent errors need to be carefully evaluated. The aim of this study was to assess the validity and clarify the sources of measurement errors of image-assisted mobile nutrition apps. Methods: This was a cross-sectional study with 98 students recruited from School of Nutrition and Health sciences, Taipei Medical University. A 3-d nutrient intake record by Formosa Food and Nutrient Recording App (FoodApp) was compared with a 24-h dietary recall (24-HDR). A two-stage data modification process, manual data cleaning, and reanalyzing of prepackaged foods were employed to address inherent errors. Nutrient intake levels obtained by the two methods were compared with the recommended daily intake (DRI), Taiwan. Paired t test, Spearman's correlation coefficients, and Bland–Altman plots were used to assess agreement between the FoodApp and 24-HDR. Results: Manual data cleaning identified 166 food coding errors (12%;stage 1), and 426 food codes with missing micronutrients (32%) were reanalyzed (stage 2). Positive linear trends were observed for total energy and micronutrient intake (all P_trend < 0.05) after the two stages of data modification, but not for dietary fat, carbohydrates, or vitamin D. There were no statistical differences in mean energy and macronutrient intake between the FoodApp and 24-HDR, and this agreement was confirmed by Bland–Altman plots. Spearman's correlation analyses showed strong to moderate correlations (r = 0.834 ∼ 0.386) between the two methods. Participants’ nutrient intake tended to be lower than the DRI, but no differences in proportions of adequacy/inadequacy for DRI values were observed between the two methods. Conclusions: Mitigating errors significantly improved the accuracy of the Formosa FoodApp, indicating its validity and reliability as a self-reporting mobile-based dietary assessment tool. Dietitians a

关键词： Food records Mobile application Mobile health Smartphone application

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Fast and Effective Clustering Method for Ancestry Estimation

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Procedia computer science 2019年 157卷 306-312页

作者： Arif Budiarto Bharuno Mahesworo James Baurley Teddy Suparyanto Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 BioRealm LLC USA Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Ancestry estimation which provides family history information is one of the most popular services in direct-to-consumer genomic testing. It is also an important task which aimed to reduce the confounding by ancestry on the relationship of genotypes and disease risk in assocation studies. Several methods have been developed to generate the best ancestry estimated scores even though some of them are still facing inefficient computation time. In this paper, a combination method between KMeans clustering and PCA is proposed estimate ancestry estimation from SNP genotyping data. This method was compared with baseline model, called fastSTRUCTURE, in term of the quality of clustering and computation time. Public data from 1000 Genome project is used to train and evaluate the proposed model and the baseline model. The proposed model can successfully generate clusters with better accuracy than fastSTRUCTURE (91.02% over 90.39%). More importantly, it can boost the computation time until 100 times faster than fastSTRUCTURE (from 490 seconds to 4.86 seconds).

关键词： Ancestry Estimation Population Stratification Clustering Bioinformatics Genomics

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An integrated system of mobile application and IoT solution for pond monitoring

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IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Ferdinan Darmalim Alam Ahmad Hidayat Tjeng Wawan Cenggoro Kartika Purwandari Sutristo Darmalim Bens Pardamean NusaNet Jakarta Indonesia 12710 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The current progress of information and communication technology has been critical to the development of the Internet of Things (IoT) in a aquaculture system. IoT solution in this system utilizes interconnectivity between devices to obtain fish pond monitoring data from sensing devices and then transmit the data to a remote server to be analyzed for decision-making in pond management. In this paper, we propose a smart pond IoT solution that provides a continuous and real-time pond monitoring. The system principally embeds five sensors that measure critical environmental parameters to determine water quality: temperature, pH, dissolved oxygen (DO), total dissolved solids (TDS), and salinity. The IoT solution also integrates the development of a mobile application on the android platform that allows remote monitoring capabilities for users to maintain efficient pond management. The application is designed with a friendly-user interface that helps the farmer to monitor sensor measurements, manage fish production cycle, record fish feeding schedule, and also monitor the health status of fish from multiple ponds.

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What kind of language is hard to language-model?

arXiv

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arXiv 2019年

作者： Mielke, Sebastian J. Cotterell, Ryan Gorman, Kyle Roark, Brian Eisner, Jason Department of Computer Science Johns Hopkins University Program in Linguistics Graduate Center City University of New York Google

How language-agnostic are current state-ofthe- art NLP tools? Are there some types of language that are easier to model with current methods? In prior work (Cotterell et al., 2018) we attempted to address this question for language modeling, and observed that recurrent neural network language models do not perform equally well over all the highresource European languages found in the Europarl corpus. We speculated that inflectional morphology may be the primary culprit for the discrepancy. In this paper, we extend these earlier experiments to cover 69 languages from 13 language families using a multilingual Bible corpus. Methodologically, we introduce a new paired-sample multiplicative mixed-effects model to obtain language difficulty coefficients from at-least-pairwise parallel corpora. In other words, the model is aware of inter-sentence variation and can handle missing data. Exploiting this model, we show that "translationese"is not any easier to model than natively written language in a fair comparison. Trying to answer the question of what features difficult languages have in common, we try and fail to reproduce our earlier (Cotterell et al., 2018) observation about morphological complexity and instead reveal far simpler statistics of the data that seem to drive complexity in a much larger sample. Copyright © 2019, The Authors. All rights reserved.

关键词： Recurrent neural networks

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A Model of Visual Intelligent System for Genus Identification of Fish in the Siluriformes Order

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IOP Conference Series: Earth and Environmental science 2021年第1期794卷

作者： Taufik Budhi Pramono R Ardharyan Islamy Saprudin Joni Johanda Putra Teddy Suparyanto Kartika Purwandari Tjeng Wawan Cenggoro Bens Pardamean Aquaculture Study Program Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 Aquatic Resources Management Brawijaya University Malang East Java Indonesia Graduate Program Aquatic Resources Faculty of Fisheries and Marine Science Jenderal Soedirman University Purwokerto Central Java Indonesia 53123 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Ambiguity in the fish naming is present in several fish species database, especially for fish in Siluformes order. To fix the ambiguity, a visual intelligent system is needed to automate the fish naming correction in the database. In this study, we developed a deep-learning-based model as the core of the intelligent system. The proposed model achieved 89% accuracy for the classification of three genera in Siluformes order: Mystus, Hemibagrus, and Glyptothorax.

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Personal health records - Potential one-stop approach in polypharmacy

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computer Methods and programs in Biomedicine Update 2022年 2卷

作者： Chen, Ya-Lin Satria, Fauzi Budi Jamshed, Shazia Babar, Zaheer-Ud-Din Mukherjee, Nilesh Yang, Hsuan-Chia Li, Yu-Chuan Iqbal, Usman Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan PhD Program in Global Health & Health Security College of Public Health Taipei Medical University Taipei Taiwan Department of Pharmacy Practice Faculty of Pharmacy UniSZA Kuala Terengganu Malaysia Qualitative Research-Methodological Application in Health Sciences Research Group Kulliyyah of Pharmacy International Islamic University Malaysia Kuantan Malaysia Centre for Pharmaceutical Policy and Practice Research Department of Pharmacy University of Huddersfield Huddersfield United Kingdom Master of Science in Systems Biology Manipal School of Life Sciences Manipal Academy of Higher Education Manipal India International Center for Health Information Technology (ICHIT) Taipei Medical University Taipei Taiwan

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Efficient Focusing with Large Numerical Aperture Using a Hybrid Metalens

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Physical Review Applied 2020年第4期13卷 044016-044016页

作者： Ming Kang Younes Ra'di Diego Farfan Andrea Alù Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Photonics Initiative Advanced Science Research Center City University of New York New York 10031 USA Physics Program Graduate Center City University of New York New York 10016 USA Department of Electrical Engineering City College of The City University of New York New York 10031 USA

Focusing light using electrically thin layers is of paramount importance in several applications, from integrated optics to microwave engineering and sensing. Recently, gradient metasurfaces, which are electrically thin arrays of densely located polarizable particles, have been employed to perform different wave-front transformations, including focusing. In comparison to a bulk lens, these designs provide ultrathin geometries, but they suffer from fundamental limitations on their overall efficiency and achievable numerical aperture. Metagratings offer a solution for efficient beam steering at large angles, but it is challenging to utilize them in the small-angle limit. Here, we introduce a hybrid metalens design, which provides dramatic enhancement in lensing performance compared with that of state-of-the-art metasurfaces, combining metagratings and conventional gradient approaches. Our experimental prototype enables microwave focusing with large efficiency (η=0.479) and near-unity numerical aperture (NA=0.98), yielding a sharp focal point at the diffraction limit in the far field (FWHM=0.332λ). We propose a hybrid metalens design with exceptional performance in terms of efficiency and numerical aperture, opening up opportunities for high-throughput optical lithography, high-density data recording, focal plane arrays, radar, and communication systems.

关键词： Classical optics Integrated optics Metamaterials Optical & microwave phenomena Devices Surfaces

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Parameter Identifiability and Input-Output Equations

arXiv

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arXiv 2020年

作者： Ovchinnikov, Alexey Pogudin, Gleb Thompson, Peter Department of Mathematics CUNY Queens College and Ph.D. Programs in Mathematics and Computer Science CUNY Graduate Center NY United States LIX CNRS École Polytechnique Institute Polytechnique de Paris France Department of Computer Science National Research University Higher School of Economics Moscow Russia Courant Institute of Mathematical Sciences New York University New York United States Ph.D. Program in Mathematics CUNY Graduate Center New York United States

Structural parameter identifiability is a property of a differential model with parameters that allows for the parameters to be determined from the model equations in the absence of noise. One of the standard approaches to assessing this problem is via input-output equations and, in particular, characteristic sets of differential ideals. The precise relation between identifiability and input-output identifiability is subtle. The goal of this note is to clarify this relation. The main results are: • identifiability implies input-output identifiability;• these notions coincide if the model does not have rational first integrals;• the field of input-output identifiable functions is generated by the coefficients of a "minimal" characteristic set of the corresponding differential ideal. We expect that some of these facts may be known to the experts in the area, but we are not aware of any articles in which these facts are stated precisely and rigorously proved. Copyright © 2020, The Authors. All rights reserved.

关键词： Rational functions

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Anomaly Detection in Climate Data Using Stacked and Densely Connected Long Short-Term Memory Model

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Journal of computers (Taiwan) 2020年第4期31卷 42-53页

作者： Saleh Abbas, Bahtiar Wahyono, Teguh Heryadi, Yaya Soeparno, Haryono Doctor of Computer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Salatiga Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Department of Industrial Engineering Bina Nusantara University Jakarta Indonesia

Climate anomalies are considered as an important factor closely related to many disasters causing many human losses, such as airline crash, wildfires, drought and flooding in many areas. Many researchers have projected that the rising global temperature will increase the draught, especially in the mid-latitude areas. Taking those problems into account, studies on anomaly detection in climate are crucial. While climate prediction aims to analyze and model regular pattern of climate, climate anomaly studies aim to model climate deviation from its previous general patterns. Long Short Term Memory (LSTM) is a method employed in this research because it has been proven to work effectively in several anomaly detection studies, especially for data with similar characteristics. This paper presents empirical results of using Basic LSTM, Densely Connected (DC) LSTM, and Stacked-DC LSTM models to detect temperature anomaly as a manifestation of climate change in Semarang City. The results show that Stacked DC LSTM produced higher accuracy in detecting anomaly than the other two methods. © 2020 computer Society of the Republic of China. All rights reserved.

关键词： Long short-term memory

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Inverse-designed silicon photonic circuit for nonreciprocal transmission

Inverse-designed silicon photonic circuit for nonreciprocal ...

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Frontiers in Optics, FIO 2019 - Part of Frontiers in Optics + Laser science APS/DLS

作者： Yang, Ki Youl Skarda, Jinhie Cotrufo, Michele Ahn, Geun Ho Alù, Andrea Vučković, Jelena E. L. Ginzton Laboratory Stanford University StanfordCA94305 United States Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Department of Electrical Engineering City University of New York New YorkNY10031 United States

Broadband nonreciprocal transmission is demonstrated in an inverse-designed silicon photonic circuit. Cascaded nonlinear resonators break the single-resonator fundamental bound on forward transmission at wide nonrecip... 详细信息

ISBN: (纸本)9781943580675

关键词： Silicon photonics

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