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A Framework of Integrating Manufacturing Plants in Smart Grid Operation: Manufacturing Flexible Load Identification

Procedia Manufacturing 2019年 39卷 1232-1241页

作者： Md. Monirul Islam Zeyi Sun Wenqing Hu Cihan Dagli Department of Engineering Management and Systems Engineering Missouri University of Science and Technology Rolla MO 65409 Department of Mathematics and Statistics Missouri University of Science and Technology Rolla MO 65409

In the deregulated electricity markets run by Independent System Operator (ISO), a two-settlement (day-ahead and real-time) process is typically used to determine the electricity price to the end-use customers at different buses. In the day-ahead settlement, the demand is predicted at each bus based on the previous consumption behavior of the consumers and thus, Locational Marginal Price (LMP) can be determined and shared to the consumers. A significant gap is usually observed between the planned and real-time demands due to the uncertainties of the weather (temperature, wind-speed etc.), the intensity of business, and everyday activities. Therefore, a large price variation may occur in the real-time market and the dispatching plan needs to be adjusted to respond to the variation. To reduce the gap between the day-ahead and real-time dispatching plans, a modified framework, i.e., a three-settlement process considering the integration of the manufacturing plants into the existing two-settlement process is proposed in this study. The manufacturing end-use customers report the flexibility of their loads to the ISO so that the ISO can update the day-ahead price through an updated dispatching plan that utilizes the feedback of the load flexibility from the manufacturers. A mathematical model is developed to identify the flexible and non-flexible loads of the manufacturers. Particle Swarm Optimization (PSO) is used to solve this mathematical model and a case study is conducted to illustrate the effectiveness of the model.

关键词： Manufacturing load Independent System Operator Flexibility Three-settlement

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An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis

Natural Language Processing Journal

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Natural Language Processing Journal 2023年 4卷

作者： Akshat Shukla Chaarvi Bansal Sushrut Badhe Mukul Ranjan Rohitash Chandra Department of Civil Engineering Indian Institute of Technology Delhi Delhi India Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani Pilani Rajasthan India Midam Charitable Trust Puducherry India Department of Electronics and Electrical Engineering Indian Institute of Technology Guwahati Guwahati Assam India Transitional Artificial Intelligence Research Group School of Mathematics and Statistics University of New South Wales Sydney Australia

Google Translate has been prominent for language translation; however, limited work has been done in evaluating the quality of translation when compared to expert translators. Sanskrit, one of the oldest written languages in the world was added to the Google Translate engine in 2022. Sanskrit is known as the mother of North Indian languages such as Hindi, Punjabi, and Bengali. Sanskrit has been used for composing sacred Hindu texts such as the Bhagavad Gita and the Upanishads. In this study, we present a framework that evaluates Google Translate for Sanskrit using the Bhagavad Gita. We first published a translation of the Bhagavad Gita in Sanskrit using Google Translate and then compared it with selected prominent translations by experts. Our framework features a BERT-based language model that implements sentiment and semantic analysis. The results indicate that there is a low level of similarity between the Bhagavad Gita by Google Translate and expert translators in terms of sentiment and semantic analyses. We found major inconsistencies in the translation of philosophical terms and metaphors. We further implemented a qualitative evaluation and found that Google Translate was unsuitable for the translation of certain Sanskrit words and phrases due to the poetic nature, contextual significance, metaphor and imagery. The mistranslations are not surprising since the Bhagavad Gita is known as a difficult text not only to translate but also to interpret since it relies on contextual, philosophical and historical information. It is difficult to distinguish different names and philosophical concepts such as karma and dharma without knowing the context and having a background of Hindu philosophy. Our framework lays the foundation for the automatic evaluation of other languages that can be translated by Google Translate.

关键词： Natural language processing Language translator models Sanskrit translations Google Translate Semantic analysis Sentiment analysis Hindu texts

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REFINED (Representation of features as images with neighborhood dependencies): A novel feature representation for convolutional neural networks

arXiv

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arXiv 2019年

作者： Bazgir, Omid Zhang, Ruibo Dhruba, Saugato Rahman Rahman, Raziur Ghosh, Souparno Pal, Ranadip Department of Electrical and Computer Engineering Texas Tech University University Department of Mathematics and Statistics Texas Tech University Department of Statistics University of Nebraska-Lincoln

Deep learning with Convolutional Neural Networks has shown great promise in various areas of image-based classification and enhancement but is often unsuitable for predictive modeling involving non-image based features or features without spatial correlations. We present a novel approach for representation of high dimensional feature vector in a compact image form, termed REFINED (REpresentation of Features as Images with NEighborhood Dependencies), that is conducible for convolutional neural network based deep learning. We consider the correlations between features to generate a compact representation of the features in the form of a two-dimensional image using minimization of pairwise distances similar to multi-dimensional scaling. We hypothesize that this approach enables embedded feature selection and integrated with Convolutional Neural Network based Deep Learning can produce more accurate predictions as compared to Artificial Neural Networks, Random Forests and Support Vector Regression. We illustrate the superior predictive performance of the proposed representation, as compared to existing approaches, using synthetic datasets, cell line efficacy prediction based on drug chemical descriptors for NCI60 dataset and drug sensitivity prediction based on transcriptomic data and chemical descriptors using GDSC dataset. Results illustrated on both synthetic and biological datasets shows the higher prediction accuracy of the proposed framework as compared to existing methodologies while maintaining desirable properties in terms of bias and feature extraction. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

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Study of area change and rehabilitation of mangrove ecosystems in Karimunjawa National Park

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AIP Conference Proceedings 2023年第1期2683卷

作者： M. Arief Rahman Halim Tri Retnaningsih Soeprobowati Hadiyanto Hadiyanto Luri Nurlaila Syahid Master Program of Environmental Science School of Postgraduate Studies Universitas Diponegoro Semarang Indonesia Department of Biology Faculty of Science and Mathematics Universitas Diponegoro Semarang Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Diponegoro Semarang Indonesia Department of Geodesy and Geomatics Remote Sensing and Geographic Information Science Research Group Faculty of Earth Science and Technology Institut Teknologi Bandung Bandung Indonesia

The mangrove ecosystem is one of the unique and distinctive ecosystems because it is a compelling natural resource. However, in the current era, many people are greedy, resulting in the conversion of mangrove land, which causes a decrease in the area of the mangrove ecosystem. This study aims to determine changes in the extent of the mangrove ecosystem in Karimunjawa National Park and the appropriate rehabilitation efforts there. The method used in this research is a case study with descriptive analysis. Data collection techniques used literature studies from several related research sources whose research locations were in the Karimunjawa National Park. The collected data were then analyzed using the SWOT method. The main priority to be chosen as the primary strategic plan to repair damage and rehabilitate mangroves in Karimunjawa National Park is to establish synergistic cooperation between the implementation of government programs and the wishes of the local community through revitalizing coastal areas due to abrasion by replanting mangrove trees. This alternative strategy is a Strength-Threats (ST) strategy, where strength is maximized to overcome threats.

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Non-dimensional newton-puiseux expansions

arXiv

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arXiv 2021年

作者： Chapman, C.J. Wynn, Henry P. Atherton, M.A. Bates, R.A. Department of Mathematics University of Keele StaffordshireST5 5BG United Kingdom Department of Statistics London School of Economics LondonWC2A 2AE United Kingdom Department of Mechanical Engineering Brunel University London UxbridgeUB3 3PH United Kingdom Rolls-Royce plc Moor Lane DerbyDE24 8BJ United Kingdom

Recent results in the theory and application of Newton-Puiseux expansions, i.e. fractional power series solutions of equations, suggest further developments within a more abstract algebraic-geometric framework, involving in particular the theory of toric varieties and ideals. Here, we present a number of such developments, especially in relation to the equations of van der Pol, Riccati, and Schrödinger. Some pure mathematical concepts we are led to are Graver, Gröbner, lattice and circuit bases, combinatorial geometry and differential algebra, and algebraic-differential equations. Two techniques are coordinated: classical dimensional analysis (DA) in applied mathematics and science, and a polynomial and differential-polynomial formulation of asymptotic expansions, referred to here as Newton-Puiseux (NP) expansions. The latter leads to power series with rational exponents, which depend on the choice of the dominant part of the equations, often referred to as the method of"dominant balance". The paper shows, using a new approach to DA based on toric ideals, how dimensionally homogeneous equations may best be non-dimensionalised, and then, with examples involving differential equations, uses recent work on NP expansions to show how non-dimensional parameters affect the results. Our approach finds a natural home within computational algebraic geometry, i.e. at the interface of abstract and algorithmic *** Codes 76M55 13F65 © 2021, CC0.

关键词： Computational geometry

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Generalized gapped-kmer filters for robust frequency estimation

arXiv

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arXiv 2021年

作者： Mohammad-Noori, Morteza Ghareghani, Narges Ghandi, Mahmood School of Mathematics Statistics and Computer Science College of Science University of Tehran P.O. Box 14155-6455 Tehran Iran Department of Engineering Science College of Engineering University of Tehran P.O. Box 11165-4563 Tehran Iran P.O.Box: 19395-5746 Tehran Iran Broad Institute of MIT and Harvard 7 Cambridge Center 4034C CambridgeMA02142 United States

In this paper, we study the generalized gapped k-mer filters and derive a closed form solution for their coefficients. We consider nonnegative integers and k, with k ≤ , and an -tuple B = (b1, . . ., b) of integers bi ≥ 2, i = 1, . . ., . We introduce and study an incidence matrix A = A,k;B. We develop a Möbius-like function νB which helps us to obtain closed forms for a complete set of mutually orthogonal eigenvectors of AA as well as a complete set of mutually orthogonal eigenvectors of AA corresponding to nonzero eigenvalues. The reduced singular value decomposition of A and combinatorial interpretations for the nullity and rank of A, are among the consequences of this approach. We then combine the obtained formulas, some results from linear algebra, and combinatorial identities of elementary symmetric functions and νB, to provide the entries of the Moore-Penrose pseudo-inverse matrix A+ and the Gapped k-mer filter matrix A+A. © 2021, CC BY.

关键词： Eigenvalues and eigenfunctions

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A fast two-stage algorithm for non-negative matrix factorization in streaming data

arXiv

引用

arXiv 2021年

作者： Gu, Ran Du, Qiang Billinge, Simon J.L. School of Statistics and Data Science Nankai University Tianjin300071 China Department of Applied Physics and Applied Mathematics Fu Foundation School of Engineering and Applied Sciences Columbia University New YorkNY10027 United States Data Science Institute Columbia University New YorkNY10027 United States Condensed Matter Physics and Materials Science Department Brookhaven National Laboratory UptonNY11973 United States

In this article, we study algorithms for nonnegative matrix factorization (NMF) in various applications involving streaming data. Utilizing the continual nature of the data, we develop a fast two-stage algorithm for highly efficient and accurate NMF. In the first stage, an alternating non-negative least squares (ANLS) framework is used, in combination with active set method with warm-start strategy for the solution of subproblems. In the second stage, an interior point method is adopted to accelerate the local convergence. The convergence of the proposed algorithm is proved. The new algorithm is compared with some existing algorithms in benchmark tests using both real-world data and synthetic data. The results demonstrate the advantage of our algorithm in finding high-precision *** Codes 65K10, 90C26 Copyright © 2021, The Authors. All rights reserved.

关键词： Non-negative matrix factorization

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Effect of variations of concentration of texturized soy protein substitution on meat taste in plant-based frozen food products

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AIP Conference Proceedings 2025年第1期3186卷

作者： Kennis Rozana Nur’aini Kartikasari Ahvina Dwi Okta Firana Alimatul Aziizah Dediek Tri Kurniawan Nonny Aji Sunaryo Harsalim Aimunandar Jayaputra Department Biology Faculty of Mathematics and Natural Sciences Universitas Negeri Malang Jl. Semarang 5 Malang 65145 Indonesia Department Management Faculty of Economics Universitas Negeri Malang Jl. Semarang 5 Malang 65145 Indonesia Department Industrial Technology Faculty of Engineering Universitas Negeri Malang Jl. Semarang 5 Malang 65145 Indonesia Study Program Civil Engineering Politeknik Negeri Malang Jl. Soekarno Hatta 9 Malang 65145 Indonesia

Innovation in the food sector is the most promising innovation, especially since the need for food will be directly proportional to population growth which continues to increase throughout the year. Among the many types of food, frozen food products have a much greater demand than other types of food. Frozen food products are claimed to be more practical for various activities. The development of nonanimal-based frozen food needs to be developed to be an option for vegetarians and groups of people who want to maintain health. This study was conducted to determine the optimal concentration of texturized soy protein as a substitute for meat in non-animal frozen food products while considering the delicious taste that everyone likes. Variations in the concentration of texturized soy protein used were 3%, 5%, and 7%, respectively, of the total amount of all ingredients. Based on the results of research conducted, it is known that a 5% concentration of texturized soy protein produces frozen food products with a similar taste, color, texture, and aroma as animal-based frozen food products in general.

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On extracting new wave solutions to a modified nonlinear Schrödinger’s equation using two integration methods

引用

Results in Physics 2022年 38卷

作者： K. Nonlaopon B. Günay Mohamed S. Mohamed S.K. Elagan S.A. Nagati Shahram Rezapour Department of Mathematics Faculty of Science Khon Kaen University Khon Kaen 40002 Thailand Faculty of Engineering and Natural Sciences Bahçeşehir University 34349 Istanbul Turkey Department of Mathematics and Statistics College of Sciences Taif University P.O. Box 11099 Taif 21944 Saudi Arabia Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan

In the present article, we have utilized two efficient techniques to obtain new optical solitons for the nonlinear Schrödinger’s equation. The advantages of the employed methods are that they are straightforward to use and able extraction of different types of solutions in single frameworks. The solutions presented in this paper evoke new applications and concepts for the considered special form of Schrödinger’s equation. Numerical simulations of some of the acquired solutions are also presented in the paper. After applying some necessary changes in these techniques, they can be implemented in solving other applied complex models arising in mathematics, physics, and applied mathematics.

关键词： Closed-form solution Symbolic calculations Nonlinear Schrödinger’s equation

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Biases in inverse Ising estimates of near-critical behavior

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Physical Review E 2023年第1期108卷 014109-014109页

作者： Maximilian B. Kloucek Thomas Machon Shogo Kajimura C. Patrick Royall Naoki Masuda Francesco Turci School of Physics HH Wills Physics Laboratory University of Bristol Tyndall Avenue Bristol BS8 1TL United Kingdom Bristol Centre for Functional Nanomaterials HH Wills Physics Laboratory University of Bristol Tyndall Avenue Bristol BS8 1TL United Kingdom Faculty of Information and Human Sciences Kyoto Institute of Technology Kyoto 606-8585 Japan Gulliver UMR CNRS 7083 ESPCI Paris Université PSL 75005 Paris France Department of Mathematics State University of New York at Buffalo Buffalo New York 14260-2900 USA Computational and Data-Enabled Science and Engineering Program State University of New York at Buffalo Buffalo New York 14260-5030 USA

Inverse Ising inference allows pairwise interactions of complex binary systems to be reconstructed from empirical correlations. Typical estimators used for this inference, such as pseudo-likelihood maximization (PLM), are biased. Using the Sherrington-Kirkpatrick model as a benchmark, we show that these biases are large in critical regimes close to phase boundaries, and they may alter the qualitative interpretation of the inferred model. In particular, we show that the small-sample bias causes models inferred through PLM to appear closer to criticality than one would expect from the data. Data-driven methods to correct this bias are explored and applied to a functional magnetic resonance imaging data set from neuroscience. Our results indicate that additional care should be taken when attributing criticality to real-world data sets.

关键词： Critical phenomena Cortical networks Spin glasses Functional magnetic resonance imaging Ising model

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