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REMOVAL OF ASPIRIN IN PHARMACEUTICAL WASTEWATER BY ELECTROCOAGULATION METHODS

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Xinan Jiaotong Daxue Xuebao/Journal of Southwest Jiaotong University 2022年第4期57卷 93-104页

作者： Suhartana, S. Purwanto, P. Darmawan, Adi Widhiarih, Tatik Doctoral Program in Environmental Science School of Postgraduate Studies Universitas Diponegoro Semarang Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Diponegoro Semarang Indonesia Department of Chemistry Faculty of Science and Mathematics Universitas Diponegoro Semarang Indonesia Department of Statistics Faculty of Science and Mathematics Universitas Diponegoro Semarang Indonesia

According to several researchers reporting, it was reported that organic pollutants dissolved in water were increasing. One of these increasing pollutants is aspirin. Our study aimed to remove aspirin in pharmaceutical wastewater by electrocoagulation, using an aluminum plate (15 cm x 4 cm x 0.5 cm) as an anode and a carbon plate (15 cm x 4 cm x 0.5 cm) as a cathode. Aspirin-containing organic pollutant samples (artificial) were prepared by dissolving aspirin purchased from a pharmacy in distilled water of varying concentrations. Before and after the sample is purified by the electrocoagulation process, its character is measured. pH, color, chemical oxygen demand (COD), turbidity, density, and conductivity were measured. The differences in the character of organic pollutants (aspirin) before and after electrocoagulation were explained from various points of view, such as electrode distance, initial pH, current density, and contact time. The kinetic processes that occur are also observed and reported. Indicators of soluble aspirin pollutants, such as pH, color, turbidity, density, and conductivity, decreased significantly. Furthermore, the dissolved aspirin pollutant was associated with research variables such as electrode distance, initial pH, current density, and contact time. Electrocoagulation can be considered an alternative method to treat wastewater containing aspirin pollutants. © 2022 Science Press. All rights reserved.

关键词： Organic pollutants

A markov-switching model approach to heart sound segmentation and classification

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arXiv 2018年

作者： Noman, Fuad Salleh, Sh-Hussain Ting, Chee-Ming Balqis Samdin, S. Ombao, Hernando Hussain, Hadri Center for Biomedical Engineering Faculty of Biosciences and Medical Engineering Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Center for Biomedical Engineering Faculty of Biosciences and Medical Engineering Universiti Teknologi Malaysia Skudai Johor81310 Malaysia Statistics Program King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

Objective: This paper considers challenges in developing algorithms for accurate segmentation and classification of heart sound (HS) signals. Methods: We propose an approach based on Markov switching autoregressive model (MSAR) to segmenting the HS into four fundamental components each with distinct second-order structure. The identified boundaries are then utilized for automated classification of pathological HS using the continuous density hidden Markov model (CD-HMM). The MSAR formulated in a state-space form is able to capture simultaneously both the continuous hidden dynamics in HS, and the regime switching in the dynamics using a discrete Markov chain. This overcomes the limitation of HMM which uses a single-layer of discrete states. We introduce three schemes for model estimation: (1.) switching Kalman filter (SKF);(2.) refined SKF;(3.) fusion of SKF and the duration-dependent Viterbi algorithm (SKF-Viterbi). Results: The proposed methods are evaluated on Physionet/CinC Challenge 2016 database. The SKF-Viterbi significantly outperforms SKF by improvement of segmentation accuracy from 71% to 84.2%. The use of CD-HMM as a classifier and Mel-frequency cepstral coefficients (MFCCs) as features can characterize not only the normal and abnormal morphologies of HS signals but also morphologies considered as unclassifiable (denoted as X-Factor). It gives classification rates with best gross F1 score of 90.19 (without X-Factor) and 82.7 (with X-Factor) for abnormal beats. Conclusion: The proposed MSAR approach for automatic localization and detection of pathological HS shows a noticeable performance on large HS dataset. Significance: It has potential applications in heart monitoring systems to assist cardiologists for pre-screening of heart pathologies. Copyright © 2018, The Authors. All rights reserved.

关键词： Switching

Retracted: Implementation Method CUSUM to Determine the Accident Prone Areas in Web Based

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Retracted: Implementation Method CUSUM to Determine the Acci...

2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, Computer Science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Dinata, Rozzi Kesuma Abdullah, Dahlan Hartono, H. Erliana, Cut Ita Riasti, Berliana Kusuma Iskandar, Akbar Sari, Ifit Novita Nurmawati, N. Nanuru, Ricardo Freedom Putri, Lusi Dwi Manurung, Rosida Tiurma Sriadhi, S. Saleh, A.A. Astari, T. Khaddafi, Muammar Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Informatics Universitas Sebelas Maret Surakarta Indonesia Department of Informatics STMIK AKBA Makassar Indonesia Departement Of: Social Science Education Program Post Graduate Program Universitas Kanjuruhan Malang Malang Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Universitas Kristen Indonesia Maluku Ambon Indonesia Department of Civil Engineering Universitas Lancang Kuning Pekanbaru Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Statistics Financial and Social Sciences Research Group Indonesia Department of Elementary School Teacher Education STKIP Citra Bangsa Aceh Utara Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

At the Unit Laka Lantas Polres Lhokseumawe determining accident-prone areas on roads in Lhokseumawe still using manual systems. Determination of accident-prone areas are less effective because the police Unit Laka Lantas Polres Lhokseumawe just using the data of the last year and had to repeatedly calculate manually accident-prone areas based on the number of human casualties. In this study the system implementation CUSUM method (Cummulative Summary) to determine the accident-prone areas designed using the web-based programming language PHP. In this system there are three processes to determine areas prone to accidents, the accident rate calculations based on the weighted severity, blacksite calculations using the Z-Score method for determining areas prone to accident blackspots and calculations using the CUSUM method to determine the critical points of an accident. The data used are secondary data obtained from the Police Unit Laka Lantas Polres Lhokseumawe years 2009-2013. © Published under licence by IOP Publishing Ltd.

关键词： Accidents

On Self-Organizing Feature Map (SOFM) Formation by Direct Optimization Through a Genetic Algorithm

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On Self-Organizing Feature Map (SOFM) Formation by Direct Op...

International Conference on Hybrid Intelligent Systems (HIS)

作者： José Everardo B. Maia Guilherme A. Barreto André L.V. Coelho Department of Teleinformatics Engineering Federal University of Ceará Fortaleza Ceara Brazil Department of Statistics and Computing State Univ. of Ceara Fortaleza Ceara Brazil Department of Statistics and Computing State University of Ceará Fortaleza Ceara Brazil Department of Teleinformatics Engineering Federal Univ. of Ceara Fortaleza Ceara Brazil Graduate Program in Applied Informatics University of Fortaleza Fortaleza Ceara Brazil

This paper examines the formation of self-organizing feature maps (SOFM) by the direct optimization of a cost function through a genetic algorithm (GA). The resulting SOFM is expected to produce simultaneously a topologically correct mapping between input and output spaces and a low quantization error. The proposed approach adopts a cost (fitness) function which is a weighted combination of indices that measure these two aspects of the map quality, specifically, the quantization error and the Pearson correlation coefficient between the corresponding distances in input and output spaces. The resulting maps are compared with those generated by the Kohonen's self-organizing map (SOM) algorithm in terms of the quantization error (QE), the weighted topological error (WTE) and the Pearson correlation coefficient (PCC) indices. The experiments show the proposed approach produces better values of the quality indices as well as is more robust to outliers.

关键词： Gallium Neurons Arrays Genetic algorithms Indexes Optimization Genetics

A non-Gaussian spatio-temporal model for daily wind speeds based on a multivariate skew-t distribution

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arXiv 2017年

作者： Tagle, Felipe Castruccio, Stefano Crippa, Paola Genton, Marc G. Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre DameIN46556 United States Department of Civil and Environmental Engineering and Earth Sciences University of Notre Dame Notre DameIN46556 United States Statistics Program King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

Facing increasing domestic energy consumption from population growth and industrialization, Saudi Arabia is aiming to reduce its reliance on fossil fuels and to broaden its energy mix by expanding investment in renewable energy sources, including wind energy. A preliminary task in the development of wind energy infrastructure is the assessment of wind energy potential, a key aspect of which is the characterization of its spatio-temporal behavior. In this study we examine the impact of internal climate variability on seasonal wind power density uctuations over Saudi Arabia using 30 simulations from the Large Ensemble Project (LENS) developed at the National Center for Atmospheric Research. Furthermore, a spatio-temporal model for daily wind speed is proposed with neighbor-based cross-temporal dependence, and a multivariate skewt distribution to capture the spatial patterns of higher order moments. The model can be used to generate synthetic time series over the entire spatial domain that adequately reproduce the internal variability of the LENS dataset. Copyright © 2017, The Authors. All rights reserved.

关键词： Wind power

FinGAT: Financial graph attention networks for recommending top-K profitable stocks

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arXiv 2021年

作者： Hsu, Yi-Ling Tsai, Yu-Che Li, Cheng-Te Master Program in Statistics National Taiwan University Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Institute of Data Science National Cheng Kung University Tainan Taiwan

Financial technology (FinTech) has drawn much attention among investors and companies. While conventional stock analysis in FinTech targets at predicting stock prices, less effort is made for profitable stock recommendation. Besides, in existing approaches on modeling time series of stock prices, the relationships among stocks and sectors (i.e., categories of stocks) are either neglected or pre-defined. Ignoring stock relationships will miss the information shared between stocks while using pre-defined relationships cannot depict the latent interactions or influence of stock prices between stocks. In this work, we aim at recommending the top-K profitable stocks in terms of return ratio using time series of stock prices and sector information. We propose a novel deep learning-based model, Financial Graph Attention Networks (FinGAT), to tackle the task under the setting that no pre-defined relationships between stocks are given. The idea of FinGAT is three-fold. First, we devise a hierarchical learning component to learn short-term and long-term sequential patterns from stock time series. Second, a fully-connected graph between stocks and a fully-connected graph between sectors are constructed, along with graph attention networks, to learn the latent interactions among stocks and sectors. Third, a multi-task objective is devised to jointly recommend the profitable stocks and predict the stock movement. Experiments conducted on Taiwan Stock, S&P 500, and NASDAQ datasets exhibit remarkable recommendation performance of our FinGAT, comparing to state-of-the-art methods. Copyright © 2021, The Authors. All rights reserved.

关键词： Profitability

Machine learning based non-Newtonian fluid model with molecular fidelity

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arXiv 2020年

作者： Lei, Huan Wu, Lei Weinan, E. Department of Computational Mathematics Science & Engineering Department of Statistics & Probability Michigan State University MI48824 United States Department of Mathematics and Program in Applied and Computational Mathematics Princeton University NJ08544 United States

We introduce a machine-learning-based framework for constructing continuum non-Newtonian fluid dynamics model directly from a micro-scale description. Polymer solution is used as an example to demonstrate the essential ideas. To faithfully retain molecular fidelity, we establish a micro-macro correspondence via a set of encoders for the micro-scale polymer configurations and their macro-scale counterparts, a set of nonlinear conformation tensors. The dynamics of these conformation tensors can be derived from the micro-scale model and the relevant terms can be parametrized using machine learning. The final model, named the deep non-Newtonian model (DeePN2), takes the form of conventional non-Newtonian fluid dynamics models, with a new form of the objective tensor derivative. Numerical results demonstrate the accuracy of DeePN2. Copyright © 2020, The Authors. All rights reserved.

关键词： Viscous flow

Local changes in marching cubes to generate less degenerated triangles 10

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Local changes in marching cubes to generate less degenerated...

10th International Conference on Computer Graphics Theory and Applications, GRAPP 2015

作者： Leal, Thiago F. Peixoto, Aruquia B. M. Silva, Cassia I. G. Dreux, Marcelo De A. De Moura, Carlos A. Department of Mathematics Rio de Janeiro Federal Institute IFRJ Paracambi Rio de Janeiro Brazil Mechanical Engineering Doctorate Program Rio de Janeiro State University UERJ Rio de Janeiro Brazil Department of Basic Disciplines CEFET/RJ Nova Iguaçu Rio de Janeiro Brazil Computer Science Doctorate Program Fluminense Federal University UFF Niteroi Rio de Janeiro Brazil Mechanical Engineering Department Rio de Janeiro Pontifical Catholic University PUC-Rio Rio de Janeiro Brazil Mathematics and Statistics Institute Rio de Janeiro State University UERJ Rio de Janeiro Brazil

ISBN: (纸本)9789897580871

The Marching Cubes algorithm is widely used to generate surfaces from implicit functions. It builds a mesh of triangles but many degenerated ones happen to appear among them, which can make the mesh thus built unfit for many applications, like the Finite Element Method. To overcome this undesired behavior our work proposes changes on the triangle generation that are automatically generated by Marching Cubes inside each voxel. We first generate the polygon border inside each voxel that intersects the surface. Each polygon is tested so as to guarantee the need to insert a new vertex inside itself, the triangles being then generated according to each polygon properties in order to guarantee the best ratio between their sides and angles. The resulting triangles inside each voxel exhibit the best possible ratio between their dimensions, thus leading to a better mesh. Copyright © 2015 SCITEPRESS - Science and Technology Publications. All rights reserved.

关键词： Finite element method

Rainfall Frequency Analysis Using Event-Maximum Rainfalls – an Event-Based Mixture Distribution Modeling Approach

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SSRN

SSRN 2023年

作者： Cheng, Ke-Sheng Chen, Bo-Yu Lin, Teng-Wei Nakamura, Kimihito Ruangrasamee, Piyatida Chikamori, Hidetaka Department of Bioenvironmental Systems Engineering National Taiwan University Taipei Taiwan Master Program in Statistics National Taiwan University Taipei Taiwan Graduate School of Agriculture Kyoto University Kyoto Japan Department of Water Resources Engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Environmental Management Engineering Okayama University Okayama Japan

Rainfall frequency analysis, an essential work for water resources management, is often conducted by using the annual maximum rainfall series. For rainfall stations with short record lengths and outliers presence, the use of annual maximum series for rainfall frequency analysis may yield design rainfall estimates of higher uncertainties. Moreover, for regions with cyclostationary climate patterns, the annual maximum rainfalls may be caused by different prevalent storm types, which differ in terms of their occurrence frequency and storm rainfall characteristics. In this study, we propose an event-maximum-rainfall-based mixture distribution modeling approach for rainfall frequency analysis. By considering the event-maximum rainfalls of individual storm events, the sample size for parameter estimation increases, and the uncertainty of design rainfall estimates reduces. Mixture distribution modeling enables a thorough investigation of the contributing probabilities of different storm types to the annual maximum rainfall. Through rigorous stochastic simulation, we demonstrated the superiority of the proposed approach over the conventional annual-maximum-rainfall approach. The proposed approach was applied to four representative rainfall stations in Taiwan, and the results revealed that the proposed approach is more robust than the conventional annual-maximum-rainfall approach. The results provide insights into the contributions of individual storm types to the annual maximum rainfall. © 2023, The Authors. All rights reserved.

关键词： Poisson distribution