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Preprint COMMUNICATION | doi:10.20944/preprints202405.1985.v1

Creation of the Remote Spin Entanglement with a Nanomechanical Cantilever

Vladimir I. Tsifrinovich

Subject: Physical Sciences, Applied Physics Keywords: entanglement; electron spin; nanomechanical cantilever; magnetic nanoparticle; Jaynes-Cummings model

Online: 30 May 2024 (09:18:08 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202404.1156.v1

Technology Acceptance Level of Dark Web Users

H.Eray Çelik, Serbest Ziyanak

Subject: Social Sciences, Behavior Sciences Keywords: Dark Web; Deep Web; Structural Equation Modeling; Technology Acceptance Model

Online: 17 April 2024 (13:24:32 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202403.1751.v1

Performance Evaluation of a National 7-Day Ensemble Streamflow Forecast Service for Australia

Mohammed Abdul Bari, Mohammad Mahadi Hasan, Gnanathikkam Emmanual Amirthanathan, Hapu Arachchige Prasantha Hapuarachchi, Aynul Kabir, Alex Daniel Cornish, Sunter Sunter, Paul Martinus Feikema

Subject: Environmental And Earth Sciences, Water Science And Technology Keywords: Ensemble streamflow forecast; 7-days; GR4H Model; performance evaluation; Australia

Online: 28 March 2024 (10:01:39 CET)

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The Australian Bureau of Meteorology offers a national operational 7-day ensemble streamflow forecast service covering regions of high environmental, economic and social significance. This semi-automated service generates streamflow forecasts every morning and is seamlessly integrated into the Bureau's Hydrologic Forecasting System (HyFS). Ensemble rainfall forecasts, European Centre for Medium-Range Weather Forecasts (ECMWF) and Poor Man's Ensemble (PME), available in the Numerical Weather Prediction (NWP) suite, are used to generate these streamflow forecasts. The NWP rainfall undergoes pre-processing using the Catchment Hydrologic Pre-Processer (CHyPP) before being fed into the GR4H rainfall-runoff model, which is embedded in the Short-term Water Information Forecasting Tools (SWIFT) hydrological modelling package. The simulated streamflow is then post-processed using the Error Representation and Reduction In Stages (ERRIS). We evaluated the performance of the operational rainfall and streamflow forecasts for 96 catchments using four years of operational data between January 2020 and December 2023. Performance evaluation metrics included CRPS, relative CRPS, CRPSS, and PIT-Alpha for ensemble forecasts and NSE, PCC, MAE, KGE, PBias and RMSE and three categorical metrics CSI, FAR and POD for deterministic forecasts. The skill scores CRPS, relative CRPS, CRPSS and PIT-Alpha, gradually decreased for both rainfall and streamflow as the forecast horizon increased from Day 1 to Day 7. A similar pattern emerged for NSE, KGE, PCC, MAE and RMSE as well as the categorical metrics. Forecast performance also progressively decreased with the higher streamflow regime. Most catchments showed positive performance skills, meaning the ensemble forecast outperformed climatology. Both streamflow and rainfall forecast skills varied spatially across the country – and were generally better in the high runoff generating catchments, and poorer in the drier catchments situated in the western part of the Great Dividing Range, South Australia and mid-west of Western Australia. We did not find any association between model forecast skill and the catchment area. Our findings demonstrate that the 7-day ensemble streamflow forecasting service is robust and draws great confidence from agencies that use these forecasts to support decisions around water resources management.

Preprint ARTICLE | doi:10.20944/preprints202401.2143.v1

Climate Change Impact on Management Practices of Maize Yield: Case of Mount Makulu, Zambia

Charles Bwalya Chisanga, Alice Chilambwe, Harison . K Kipkulei, Kabwe H. Mubanga

Subject: Environmental And Earth Sciences, Other Keywords: DSSAT model; GCMs; maize; nitrogen fertilizer; seasonal analysis; statistical downscaling

Online: 31 January 2024 (02:59:01 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.1953.v1

Regression Metamodel-Based Digital Twin for an Industrial Dynamic Crossflow Filtration Process

Matthias Heusel, Gunnar Grim, Joel Rauhut, Matthias Franzreb

Subject: Engineering, Bioengineering Keywords: digital twin; hybrid model; metamodel; dynamic crossflow filtration; industry-scale

Online: 29 January 2024 (04:13:46 CET)

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Preprint REVIEW | doi:10.20944/preprints202401.1857.v1

A Review on BERT: Language Understanding for Different Types of NLP Task

Md Saiful Islam, Long Zhang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Natural Language Processing (NLP); BERT; Language Model; Transfer Learning; Transformers

Online: 26 January 2024 (03:39:32 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.1038.v1

Computation of Real-Fluid Thermophysical Properties Using a Neural Network Approach Implemented in OpenFOAM

Nasrin Sahranavardfard, Damien Aubagnac-Karkar, Gabriele Costante, Faniry Nadia Zazaravaka Rahantamialisoa, Chaouki Habchi, Michele Battistoni

Subject: Engineering, Mechanical Engineering Keywords: OpenFOAM; Real-Fluid Model; Machine Learning; Neural Network; NNICE; CFD

Online: 14 January 2024 (16:14:16 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.1906.v1

Evaluation of Handheld Mobile Laser Scanner Systems for the Definition of Fuel Types in Structurally Complex Mediterranean Forest Stands

Raúl Hoffrén, María Teresa Lamelas, Juan de la Riva

Subject: Environmental And Earth Sciences, Remote Sensing Keywords: Wildfires; Fuel heterogeneity; HMLS; Prometheus fuel model; Fire modelling; Voxels

Online: 26 December 2023 (11:27:47 CET)

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The exposure of Mediterranean forests to large wildfires requires mechanisms to prevent and mitigate their negative effects on the territory and ecosystems. Fuel models synthesize the complexity and heterogeneity of forest fuels and allow understanding and modelling of fire behavior. However, it is sometimes challenging to define the fuel type in a structurally heterogeneous forest stand due to the mixture of characteristics from different types and limitations of qualitative field observation and passive and active airborne remote sensing. This can impact the performance of classification models that rely on in situ identification of fuel type as ground-truth, which can lead to a mistaken prediction of fuel types over larger areas in fire prediction models. In this study, a handheld mobile laser scanner (HMLS) system were used to assess its capability to define Prometheus fuel types in 43 forest plots in Aragón (NE Spain). The HMLS system captured the vertical and horizontal distribution of fuel at extremely high resolution to derive high-density three-dimensional point clouds (average: 63,148 points/m2) which were discretized into voxels of 0.05 m3. The total number of voxels in each 5 cm height stratum was calculated to quantify the fuel volume in each stratum, providing the vertical distribution of fuels (m3/m2) for each plot at centimetric scale. Additionally, fuel volume was computed for each Prometheus height stratum (0.60, 2, and 4 m) for each plot. The Prometheus fuel types were satisfactory identified for each plot, which was compared with the fuel type estimated in the field. This led to the modification of the ground-truth in 10 out of the 43 plots, with estimation errors between types 2–3, 5–6, and 6–7. These results demonstrate the ability of HMLS systems to capture fuel heterogeneity at centimetric scales for the definition of fuel types in Mediterranean forests, making them powerful tools for fuel mapping and fire modelling, and ultimately for improving wildfire prevention and forest management.

Preprint ARTICLE | doi:10.20944/preprints202312.1940.v1

Research on the Wood Density Measurement in Standing Trees though the Micro Drilling Resistance Method

Jianfeng Yao, Yabin Zhao, Jun Lu, Hengyuan Liu, Zhenyang Wu, Xinyu Song, Zhuofan Li

Subject: Biology And Life Sciences, Forestry Keywords: wood density; micro-drilling resistance method; standing trees; mathematical model

Online: 26 December 2023 (06:10:18 CET)

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To achieve a micro-destructive and rapid measurement of the wood density of standing trees, this study investigated the feasibility of using the micro-drilling resistance method, formulated a mathematical model, explored the potential for a unified model across multiple tree species, and analyzed the influence of moisture content on measurement accuracy. First, 231 tree cores and drill resistance data were sampled from Pinus massoniana, Cunninghamia lanceolate, and Cryptomeria fortunei. The basic density and moisture content of each core were measured, and the average value of each resistance data record was calculated. Second, the average drill resistance, the natural logarithm of average drill resistance, and absolute moisture content were used as independent variables, while the wood basic density was used as the dependent variable. Third, the total model of the three tree species and sub-model for each tree species were established through a stepwise regression method. Finally, the accuracy of each model was compared and analyzed with that of using the average basic density of each tree species as an estimated density. The results revealed that the estimation accuracy of the sub-model for each tree species was 1.670 percentage points higher than the average value of each tree species used as the density estimation value for these tree species. Additionally, except for Cryptomeria fortunei, the natural logarithm of drill resistance significantly influenced the wood density model at a significance level of 0.05. Moreover, moisture content significantly affected the total model and sub-models of Pinus massoniana at a significance level of 0.05. The estimation accuracy of the total mathematical model was 2.125 percentage points lower than that achieved using the average basic density of each tree species to predict their density. The results indicated the feasibility of using the micro-drilling resistance method to measure the wood density of standing trees. Moreover, the relationship between wood density and drill resistance did not follow a linear pattern, and moisture content slightly influenced the drill needle resistance. Furthermore, the establishment of a mathematical model for each tree species was deemed essential. This study provides valuable guidance for measuring the wood density of standing trees through the micro-drilling resistance method.

Preprint ARTICLE | doi:10.20944/preprints202312.1715.v1

Statistical Inference for Interval-Valued Spatial Error Models

Li Guan, Hai Zhou, Wei Zhang

Subject: Computer Science And Mathematics, Probability And Statistics Keywords: Interval-valued random variable, Spatial error model, Parameter estimator

Online: 22 December 2023 (08:18:03 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.0193.v1

Game-based Assessment of Students’ Digital Literacy Using Evidence-Centered Game Design

Jiayuan Li, Jie Bai, Sha Zhu, Harrison Hao Yang

Subject: Social Sciences, Education Keywords: digital literacy; digital game-based assessment; ECGD; AHP; assessment model

Online: 4 December 2023 (15:12:33 CET)

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Preprint ARTICLE | doi:10.20944/preprints202311.1477.v1

BNS: A Detection System to Find Nodes in Bitcoin Network

Ruiguang Li, Liehuang Zhu, Chao Li, Fudong Wu, Dawei Xu

Subject: Computer Science And Mathematics, Computer Networks And Communications Keywords: bitcoin; reachable nodes; unreachable nodes; node activity; dicision tree model

Online: 23 November 2023 (05:34:22 CET)

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Preprint ARTICLE | doi:10.20944/preprints202311.1392.v1

Deep-Learning-Based Hydrostatic Curve Modeling for Stability Calculation of Chine-Type Small Ships

Dongkeun Lee, Chaeog Lim, Sang-jin Oh, Minjoon Kim, Jun Soo Park, Sung-chul Shin

Subject: Engineering, Marine Engineering Keywords: hull form; deep learning model; hydrostatic curve modelling; small ships

Online: 22 November 2023 (06:31:44 CET)

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Preprint ARTICLE | doi:10.20944/preprints202311.0648.v1

Electroencephalogram-Based Human Performance Analysis for Improved Small Modular Reactor Operation

John Gaber, Jing Ren, Hossam A.Gabbar

Subject: Engineering, Safety, Risk, Reliability And Quality Keywords: Human Performance; Mental Model; EEG; SMR; Plant Operation; Human Factors

Online: 9 November 2023 (14:28:34 CET)

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Preprint ARTICLE | doi:10.20944/preprints202310.1002.v1

Optimizing Offshore Wind Power Generation in Extreme Climatic Scenarios

Fernando M. Camilo, Paulo J. Santos, Pedro J. Lobato, Sandrina B. Moreira

Subject: Engineering, Electrical And Electronic Engineering Keywords: Wind-offshore; Renewable Energy; Dynamic Model; Economic Evaluation; optimization methodologies

Online: 17 October 2023 (04:54:19 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202310.0704.v1

Evaluation of Subseasonal Precipitation Simulations for the Sao Francisco River Basin, Brazil

Nicole C. R. Ferreira, Sin Chan Chou, Claudine Dereczynski

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: Climate extremes; transition season; rainy season; model errors; extended range

Online: 11 October 2023 (08:56:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.0446.v1

Impact Pressure Influence of Flood on Bridge Deck under Sediment Deposition Conditions: An Experimental Study

Zhipan Niu, Yi Long, Chuke Meng, Hang Yang, Yihan Luo, Weiyang Zhao

Subject: Engineering, Civil Engineering Keywords: flood; sediment deposition; bridge deck; impact pressure; fluctuation; model experiment

Online: 7 September 2023 (04:54:34 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202309.0390.v1

Carbon Black Filling Amount on the Hyper-elastic Mechanical Behavior of Rubber

Zepeng Wang, Xiulong Yao, Fangru Hu, Chuanxiang Ma, Xinyan Li, Zhanli Miao, Junping Song, Lianxiang Ma, Wei Li

Subject: Chemistry And Materials Science, Materials Science And Technology Keywords: natural rubber; Yeoh constitutive model; hyper-elastic; carbon black filling

Online: 6 September 2023 (08:49:55 CEST)

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Preprint REVIEW | doi:10.20944/preprints202308.1952.v1

Bioactive Endodontic Hydrogels: From Parameters to Personalized Medicine

Marianne Lévêque, Mourad Bekhouche, Jean-Christophe Farges, Audrey Aussel, Kadiatou Sy, Raphael Richert, Maxime Ducret

Subject: Medicine And Pharmacology, Dentistry And Oral Surgery Keywords: Regenerative endodontic procedures; hydrogels; tissue engineering; apical release; preclinical model

Online: 29 August 2023 (08:45:41 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.1271.v1

Exploring Ethical Boundaries: Can ChatGPT Be Prompted to Give Advice on How to Cheat in University Assignments?

Dirk H.R. Spennemann

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: academic misconduct; artificial intelligence; ChatGPT; ethics; language model; machine learning

Online: 17 August 2023 (10:32:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.0070.v1

Efficient Hyperbolic Perceptron for Image Classification

Ahmad Omar Ahsan, Susanna Tang, Wei Peng

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Deep Neural Networks; Hyperbolic Geometry; Image Classification; Lorentz Model; Graphs

Online: 2 August 2023 (02:08:21 CEST)

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Deep neural networks with powerful auto-optimization tools have been widely applied in various research fields, e.g., NLP and computer vision. However, existing neural network architectures typically are constructed using different inductive biases, e.g., preconceptions, expecting to decrease parameter search space during training, reduce computational cost or introduce expert knowledge in the neural network design. As an alternative, Multilayer Perceptron (MLP) provides much better freedom for exploration, has a lower inductive bias than convolutional neural networks (CNNs), and offers good flexibility in learning complex patterns. Even though, such neural architectures are commonly built in a flat Euclidean space, which is not necessarily the optimal space for any data, and is especially not good for modeling hierarchical correlations. Hyperbolic neural networks (HNNs) have gained attention for their ability to capture hierarchical structures present in complex data types like graphs. Recently, there has been an increasing interest to extend HNNs to computer vision tasks, motivated by the observations that images possess rich hierarchical relations. However, this is generally applied by employing a Euclidean backbone for learning higher-level semantic representations and only incorporating a hyperbolic classifier for classification, which, we argue, does not make full use of the advantage of hyperbolic space. Considering the recovery of the attention-free Multilayer Perceptron(MLP), in this paper, we extend it to non-Euclidean space and propose a novel architecture, named Hyperbolic Res-MLP (HR-MLP), that leverages fully hyperbolic layers to learn feature embeddings and perform image classification in an end-to-end fashion. With the help of the proposed Lorentz cross-patch and cross-channel layers, we can directly perform operations in the hyperbolic domain with fewer parameters, making it faster to train and providing comparatively better performance than its Euclidean counterpart. Experiments on CIFAR10, CIFAR100, and MiniImageNet demonstrate a comparable and superior performance when compared to Euclidean baselines. Our code is available at (https://github.com/Ahmad-Omar-Ahsan/HR-MLP)

Preprint ARTICLE | doi:10.20944/preprints202307.0474.v1

Mathematical Programming for the Dynamics of Opinion Diffusion

Andrea Ellero, Giovanni Fasano, Daniela Favaretto

Subject: Physical Sciences, Other Keywords: Sociophysics; Stochastic Models; Galam’s Diffusion Model; Mathematical Programming; Parameter Optimisation

Online: 7 July 2023 (10:38:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.1767.v1

Usefulness of Tumor Marker Score for Prediction of Prognosis in Hepatocellular Carcinoma Patients Treated with Atezolizumab plus Bevacizumab: A Multicenter Retrospective Study

Kazunari Tanaka, Kunihiko Tsuji, Atsushi Hiraoka, Toshifumi Tada, Masashi Hirooka, Kazuya Kariyama, Joji Tani, Masanori Atsukawa, Koichi Takaguchi, Ei Itobayashi, Shinya Fukunishi, Toru Ishikawa, Kazuto Tajiri, Hironori Ochi, Hidenori Toyoda, Chikara Ogawa, Takashi Nishimura, Takeshi Hatanaka, Satoru Kakizaki, Noritomo Shimada, Kazuhito Kawata, Atsushi Naganuma, Hisashi Kosaka, Tomomitsu Matono, Hidekatsu Kuroda, Yutaka Yata, Hideko Ohama, Fujimasa Tada, Kazuhiro Nouso, Asahiro Morishita, Akemi Tsutsui, Takuya Nagano, Norio Itokawa, Tomomi Okubo, Taeang Arai, Keisuke Yokohama, Hiroki Nishikawa, Michitaka Imai, Yohei Koizumi, Shinichiro Nakamura, Hiroko Iijima, Masaki Kaibori, Yoichi Hiasa, Takashi Kumada

Subject: Medicine And Pharmacology, Oncology And Oncogenics Keywords: hepatocellular carcinoma; tumor marker; atezolizumab plus bevacizumab; prognosis; predictive model

Online: 26 June 2023 (09:42:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202306.0604.v1

The Role of Photosynthesis Processes in Dynamics of Plant Community

Aleksandr Abakumov, Svetlana Pak

Subject: Computer Science And Mathematics, Applied Mathematics Keywords: Mathematical model; differential equations; phytoplankton; photosynthesis; chlorophyll; optimal control problem

Online: 8 June 2023 (08:00:38 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.1416.v1

The Impact of Higher-Order Interactions on the Synchronization of Hindmarsh-Rose Neuron Maps under Different Coupling Functions

Mahtab Mehrabbeik, Atefeh Ahmadi, Fatemeh Bakouie, Amir Homayoun Jafari, Sajad Jafari, Dibakar Ghosh

Subject: Physical Sciences, Theoretical Physics Keywords: Higher-order network; Simplicial complex; Synchronization; Neuron; Map-based model

Online: 19 May 2023 (09:39:42 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0892.v1

The Role of Industrial Structure Upgrading in Moderating the Impact of Environmental Regulation on Air Pollution in China

Yu Liu, Chun-Ni Xie, Zi-Shuang Wang, Noure-El Houda REBAI, Xiao-Min Lai

Subject: Environmental And Earth Sciences, Pollution Keywords: air pollution; environmental regulation; industrial structure; PVAR model; Moderating effect

Online: 12 May 2023 (05:19:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0818.v1

Conglomerate Business Model:The Case of IJM Corporation Berhad

Seng Loong Kok, Supaprawat Siripipatthanakul

Subject: Business, Economics And Management, Business And Management Keywords: Management; Financial Performance; Corporate Diversification; Capital Structure; Conglomerate; Business Model

Online: 11 May 2023 (08:17:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0541.v1

Efficiency of Numerical Control Programs using Predefined Cycles for Automatic Symmetric Tool Path Calculation

Arina Modrea, Stefan Mocanu, Sorin Vlase, Virgil Florescu, Laurenţiu Rece

Subject: Engineering, Industrial And Manufacturing Engineering Keywords: computing methods; numerical control; mathematical model; predefined cycles; tool path

Online: 8 May 2023 (13:15:55 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202305.0107.v1

Drag Coefficient Parameterization Under Hurricane Wind Conditions

Alexandra Mikhailovna Kuznetsova, Georgy Alekseyevich Baydakov, Alexander Sergeyevich Dosaev, Yuliya Igorevna Troitskaya

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: drag coefficient; parameterizations; wave model; spray; ocean-atmosphere boundary layer

Online: 3 May 2023 (07:28:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202304.1002.v1

Exploring Stakeholder Engagement Process as The Success Factor for Infrastructure Projects

Kristijan Robert Prebanić, Mladen Vukomanović

Subject: Engineering, Civil Engineering Keywords: stakeholder; engagement; project success; factors; criteria; governance; infrastructure; framework model

Online: 26 April 2023 (15:25:01 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202211.0360.v1

Influence of Local Factors on Coastal Erosion: The Case of Vagueira Beach in Portugal

Luiz Norberto Lacerda Magalhães Filho, Peter Roebeling, Carlos Coelho

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Groins; Dredging; Storm events; Natural factors; Anthropogenic factors; Regression model.

Online: 21 November 2022 (01:19:51 CET)

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Preprint ARTICLE | doi:10.20944/preprints202209.0311.v1

A Dialogue System that Models User's Opinion Based on Information Content

Yoshiki Ohira, Takahisa Uchida, Takashi Minato, Hiroshi Ishiguro

Subject: Computer Science And Mathematics, Computer Science Keywords: opinion model; user modeling; information content; dialogue strategy; dialogue system

Online: 21 September 2022 (02:27:12 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202209.0309.v1

Natural Language Processing Application on Commit Messages: A Case Study on HEP Software

Yue Yang, Elisabetta Ronchieri, Marco Canaparo

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: machine learning; natural language processing; commit messages; change prediction model

Online: 20 September 2022 (14:52:49 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202208.0536.v1

Prediction of Bay of Bengal Extremely Severe Cyclonic Storm "Fani” Using Moving Nested Domain

Kuvar Satya Singh, Sridhara Nayak, Suman Maity, Hara Prasad Nayak, Soma Dutta

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: WRF model; Moving-nest; Fani; Bay of Bengal; Wind Speed

Online: 31 August 2022 (07:48:18 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202206.0339.v1

New Current Oscillator for Electrical Bioimpedance Spectroscopy

David William Cordeiro Marcôndes, Pedro Bertemes-Filho, Aleksander Sade Paterno

Subject: Engineering, Electrical And Electronic Engineering Keywords: Current Oscillator; Pyragas Model; Second-Generation Current Carrier; Bioimpedance Spectroscopy

Online: 24 June 2022 (13:45:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202202.0058.v2

Are Deep Models Robust against Real Distortions? A Case Study on Document Image Classification

Saifullah Saifullah, Shoaib Ahmed Siddiqui, Stefan Agne, Andreas Dengel, Sheraz Ahmed

Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: Document Image Classification; Corruption Robustness; Robustness to Distortions; Model Robustness

Online: 14 June 2022 (08:43:57 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202205.0391.v1

Core Elements Affecting the Circularity of Materials

Aurelija Burinskiene Burinskiene, Olga Lingaitienė, Arturas Jakubavicius

Subject: Business, Economics And Management, Business And Management Keywords: circularity of materials; circular activity; recycling; regression model; key elements

Online: 30 May 2022 (09:59:03 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202112.0437.v1

Determinants of Smallholder Households’ Resilience to Livelihood Insecurity in Goncha District, Northwest Highlands of Ethiopia

Ermias Debie, Amare Wubishet Ayele

Subject: Social Sciences, Geography, Planning And Development Keywords: Mixed farming; Household resilience; livelihood insecurity; Diversification; structural equation model

Online: 27 December 2021 (15:51:04 CET)

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Preprint ARTICLE | doi:10.20944/preprints202112.0213.v1

Assessment of Climate Change Impact on Snowmelt Runoff in Himalayan Region

Rohitashw Kumar, Saika Manzoor, Dinesh Kumar Vishwakarma, N. L. Kushwaha, Ahmed Elbeltagi, Kallem Sushanth, Alban Kuriqi

Subject: Engineering, Automotive Engineering Keywords: GIS; Himalayan region; SRM model; simulation; snowmelt runoff; climate change

Online: 13 December 2021 (16:06:43 CET)

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Preprint ARTICLE | doi:10.20944/preprints202111.0286.v1

A Theoretical Modeling Analysis of Adapted Composite CNT Bundle for High-Speed VLSI Interconnect

Abu Bony Amin, S M Shakil, Muhammad Sana Ullah

Subject: Engineering, Electrical And Electronic Engineering Keywords: Composite CNT bundle; crosstalk delay; interconnect; propagation delay; RLC model

Online: 16 November 2021 (10:06:06 CET)

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Preprint ARTICLE | doi:10.20944/preprints202110.0358.v1

In-place Characterization of On-state Voltage for SiC MOSFETs: Controlled Shoot-through vs. Film Heater

Alessandro Soldati, Matteo Dalboni, Roberto Menozzi, Carlo Concari

Subject: Engineering, Electrical And Electronic Engineering Keywords: on-state voltage; TSEP; junction temperature; model calibration; pulsed measurements

Online: 25 October 2021 (13:49:04 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202109.0365.v1

New Formula for the Identification of Liquefaction Based on the Investigation of the Songyuan Site

Ping Li, Yuan Zhang, Yudong Zhang

Subject: Engineering, Control And Systems Engineering Keywords: Songyuan earthquake; Songyuan site; sand liquefaction; hyperbolic model; discriminant formula

Online: 21 September 2021 (14:12:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202109.0298.v1

A Lagrangian Tool for Simulating the Transport of Chemical Pollutants in the Arabian/Persian Gulf

Raúl Periáñez

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Arabian/Persian Gulf; Lagrangian model; pollutant transport; tide; baroclinic circulation

Online: 17 September 2021 (08:07:30 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202105.0595.v2

Global Surface HCHO Distribution derived from Satellite Observations with Neural Networks Technique

Jian Guan, Bohan Jin, Yizhe Ding, Wen Wang, Guoxiang Li, Pubu Ciren

Subject: Environmental And Earth Sciences, Environmental Science Keywords: surface formaldehyde; neural network model; interval estimation; TROPOMI; global distribution

Online: 30 August 2021 (10:30:42 CEST)

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Working Paper ARTICLE

Analysis of Two Choir Outbreaks in Germany in 2020 Characterizes Long- range Transmission Risks Through SARS-CoV-2

Felix Reichert, Oliver Stier, Anne Hartmann, Claudia Ruscher, Annika Brinkmann, Marica Grossegesse, Markus Neumann, Dirk Werber, Marius Hausner, Mareike Kunze, Bettina Weiß, Janine Michel, Andreas Nitsche, Martin Kriegel, Victor M. Corman, Terry C. Jones, Christian Drosten, Tobias Brommann, Udo Buchholz

Subject: Medicine And Pharmacology, Immunology And Allergy Keywords: SARS-CoV-2; Singing; Disease Outbreaks; Aerosols; Dose-Response Model

Online: 21 June 2021 (14:49:39 CEST)

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Preprint REVIEW | doi:10.20944/preprints202102.0478.v2

Modeling Seizures: From Single Neurons to Networks

Damien Depannemaecker, Alain Destexhe, Viktor Jirsa, Christophe Bernard

Subject: Medicine And Pharmacology, Neuroscience And Neurology Keywords: epilepsy; computational model; seizures; single neurons level; networks; whole brain

Online: 16 June 2021 (12:14:49 CEST)

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Preprint REVIEW | doi:10.20944/preprints202103.0728.v1

Computational Architecture Mediating Inhibitory Control of Coordinated Eye-Hand Movements

Sumitash Jana, Atul Gopal, Aditya Murthy

Subject: Biology And Life Sciences, Anatomy And Physiology Keywords: Eye-hand coordination; Race model; Flexible behavior; Reaction time variability

Online: 30 March 2021 (10:50:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202102.0149.v1

Is There a Slope Discount?

Yi Huang, Geoffrey Hewings

Subject: Business, Economics And Management, Accounting And Taxation Keywords: Land price index; Land slope; Slope discount; Decomposition; Builder’s model

Online: 5 February 2021 (09:24:11 CET)

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Preprint ARTICLE | doi:10.20944/preprints202102.0146.v1

A Novel Approach to Estimating Time-Averaged Volcanic SO₂ Fluxes from Infrared Satellite Measurements

David Hyman, Michael Pavolonis, Justin Sieglaff

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: SO2 emissions; computer vision; time-averaged dispersion model; CrIS; JPSS

Online: 4 February 2021 (21:53:35 CET)

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Preprint ARTICLE | doi:10.20944/preprints202102.0139.v1

Elastostatics of Bernoulli-Euler Beams Resting on Displacement-Driven Nonlocal Foundation

Marzia Sara Vaccaro, Francesco Paolo Pinnola, Francesco Marotti de Sciarra, Raffaele Barretta

Subject: Engineering, Automotive Engineering Keywords: Wieghardt foundation; Bernoulli-Euler beams; nonlocal effects; integral nonlocal model

Online: 4 February 2021 (13:08:54 CET)

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The simplest elasticity model of foundation underlying a slender beam under flexure was conceived by Winkler, requiring local proportionality between soil reactions and beam deflection. Such an approach leads to well-posed elastostatic and elastodynamic problems, but, as highlighted by Wieghardt, it provides elastic responses which are not technically significant for a wide variety of engineering applications. Thus, Winkler's model was replaced by Wieghardt himself by assuming that the beam deflection is the convolution integral between soil reaction field and an averaging kernel. Due to conflict between constitutive and kinematic compatibility requirements, the corresponding elastic problem of an inflected beam resting on Wieghardt foundation results to be ill-posed. Modifications of the original Wieghardt model were proposed by introducing fictitious boundary concentrated forces of constitutive type, which are physically questionable, being significantly influenced on prescribed kinematic boundary conditions. Inherent difficulties and issues are overcome in the present research using a displacement-driven nonlocal integral strategy got by swapping input and output fields involved in Wieghardt's original formulation. That is, nonlocal soil reaction fields are output of integral convolutions of beam deflection fields with an averaging kernel. Equipping the displacement-driven nonlocal integral law with the bi-exponential averaging kernel, an equivalent nonlocal differential problem, supplemented with non-standard constitutive boundary conditions involving nonlocal soil reactions, is established. As a key implication, the integro-differential equations governing the elastostatic problem of an inflected elastic slender beam resting on displacement-driven nonlocal integral foundation are replaced with much simpler differential equations supplemented with kinematic, static and new constitutive boundary conditions. The proposed nonlocal approach is illustrated by examining and analytically solving exemplar problems of structural engineering. Benchmark solutions for numerical analyses are also detected.

Preprint ARTICLE | doi:10.20944/preprints202011.0460.v1

Superfluid Quantum Space as the Unified Field Theory

Srečko Šorli

Subject: Physical Sciences, Acoustics Keywords: unified field model; superfluid quantum space (SQS); gravity; entanglement; time

Online: 17 November 2020 (15:56:31 CET)

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Working Paper ARTICLE

Another Train Paradox

Bernard Delalande, Hirohisa Tamagawa, Vladimir Matveev

Subject: Biology And Life Sciences, Biophysics Keywords: axon; neuron; saltatory conduction; action potential; impulse propagation; HH model

Online: 30 August 2020 (18:39:44 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202008.0437.v1

A Way of Marketing 3D Web in E-commerce, Applying at Car Showrooms Period of Industrial Revolution 4.0

Pham Minh Dat, Nguyen Thi Hang, Nguyen Van Huan

Subject: Business, Economics And Management, Business And Management Keywords: industrial revolution 4.0; enterprise; e-commerce; 3D web marketing model

Online: 20 August 2020 (07:17:04 CEST)

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Preprint CONCEPT PAPER | doi:10.20944/preprints202008.0078.v1

Operationalizing Ensemble Models for Scientific Advice to Fisheries Management

Ernesto Jardim, Manuela Azevedo, Jon Brodziak, Elizabeth N. Brooks, Kelli F. Johnson, Nikolai Klibansky, Colin P. Millar, Coilin Minto, Iago Mosqueira, Richard D.M. Nash, Paris Vasilakopoulos, Brian K. Wells

Subject: Biology And Life Sciences, Aquatic Science Keywords: assessment, conservation, exploitation, management, multimodel, natural resources, ensemble, model, fisheries

Online: 4 August 2020 (04:58:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202007.0669.v1

The Mathematical Construction of the Battery Mechanism Function

Wen Li, Chen Zhang, Lei Mao, Xiaofang Cheng

Subject: Engineering, Energy And Fuel Technology Keywords: volt-ampere characteristics; battery mathematical model; mechanism function; fuel cell

Online: 28 July 2020 (09:39:10 CEST)

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Working Paper ARTICLE

Flattening COVID-19 Curve in Egypt: An Epidemiological Modelling

Ali Hasab

Subject: Medicine And Pharmacology, Epidemiology And Infectious Diseases Keywords: COVID-19; Egypt; Epidemic SIR Model; Pandemic; Flattening the curve

Online: 14 May 2020 (15:12:16 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202003.0033.v1

Impact of Credit Risk on Momentum & Contrarian Strategies: Evidence from South Asian Markets

Ahmed Imran Hunjra, Tahar Tayachi, Rashid Mehmood, Sidra Malik, Zoya Malik

Subject: Business, Economics And Management, Finance Keywords: momentum returns; contrarian returns; credit risk; stock market; KMV model

Online: 3 March 2020 (04:25:40 CET)

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Preprint ARTICLE | doi:10.20944/preprints202003.0022.v1

Deep Arbitrage-Free Learning in a Generalized HJM Framework via Arbitrage-Regularization

Anastasis Kratsios, Cody Hyndman

Subject: Computer Science And Mathematics, Applied Mathematics Keywords: Arbitrage-Regularization; Bond Pricing; Model Selection; Deep Learning; Dynamic PCA

Online: 2 March 2020 (01:15:00 CET)

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Preprint ARTICLE | doi:10.20944/preprints201911.0125.v1

Estimating Zonal Ekman Transport along Coastal Senegal during Passage of Hurricane Fred (2015) from August 30 to 31, 2015

Abdou Lahat Dieng, Siny Ndoye, Gregory S. Jenkins, Saïdou Moustapha Sall, Amadou Thierno Gaye

Subject: Environmental And Earth Sciences, Atmospheric Science And Meteorology Keywords: tropical cyclone; Weather Research and Forecast model; zonal Ekman transport

Online: 12 November 2019 (09:32:21 CET)

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Preprint ARTICLE | doi:10.20944/preprints201909.0332.v1

The Impact of Collaborative Innovation on Ecological Efficiency — Empirical Research Based on China’s Regions

Jianqing Zhang, Song Wang, Fei Fan, Peilei Yang

Subject: Business, Economics And Management, Economics Keywords: ecological efficiency; collaborative innovation; global-malmquist; gravity model; system-gmm

Online: 29 September 2019 (10:42:11 CEST)

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Working Paper ARTICLE

Climate during the Last Glacial Maximum in the Northern Sawatch Range, Colorado, USA

Keith A. Brugger, Chester A. Ruleman, Marc W. Caffee, Cody C. Mason

Subject: Environmental And Earth Sciences, Geophysics And Geology Keywords: Last Glacial Maximum; paleoclimate; temperature-index model; Sawatch Range; Colorado

Online: 8 September 2019 (15:59:45 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201905.0336.v1

Secondary Flow Effects on Deposition of Cohesive Sediment in a Meandering Reach of Yangtze River

Cuicui Qin, Xuejun Shao, Yi Xiao

Subject: Engineering, Civil Engineering Keywords: secondary flow; cohesive; deposition; 2D numerical model; meandering; Yangtze River

Online: 28 May 2019 (11:10:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201904.0069.v1

3-D Segmentation of Lung Nodules Using Hybrid Levelsets

Hina Shakir

Subject: Engineering, Control And Systems Engineering Keywords: hybrid level-sets, active contours, nodule segmentation, hybrid deformable model

Online: 5 April 2019 (15:36:24 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201904.0049.v1

Particle Mass Oscillation through Tachyon Interaction

Luca Nanni

Subject: Physical Sciences, Particle And Field Physics Keywords: Mass oscillation; bradyon-tachyon interaction; infinite-component spinor; Standard Model

Online: 4 April 2019 (12:20:40 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201902.0044.v1

A New Approach to the Technological Aspect of Corporate Sustainable Development

Rolandas Drejeris, Danguole Ozeliene

Subject: Business, Economics And Management, Business And Management Keywords: Sustainable activity; dimensions of sustainability; technological sustainability, sustainable business model

Online: 4 February 2019 (17:03:26 CET)

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Preprint ARTICLE | doi:10.20944/preprints201712.0077.v4

A Cosmological View on Milgrom’s Acceleration Constant

Engel Roza

Subject: Physical Sciences, Nuclear And High Energy Physics Keywords: cosmological constant; MOND; dark matter; dark energy; Lamda-CDM model

Online: 12 November 2018 (08:39:24 CET)

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Preprint ARTICLE | doi:10.20944/preprints201810.0459.v1

Why is the Effect of Live Fuel Moisture Content on Fire Rate of Spread Underestimated in Field Experiments in Shrublands?

Francois Pimont, Julien Ruffault, Nicolas Martin, Jean-Luc Dupuy

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Sample size, Measurement error, Generalized Additive Model, GAM, Réseau Hydrique.

Online: 19 October 2018 (16:53:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201810.0257.v1

Determination of Crude Oil Thickness at Night Using Thermal Imagery

Toomas H. Allik

Subject: Engineering, Marine Engineering Keywords: remote sensing; oil spill thickness measurement; night heat transfer model

Online: 12 October 2018 (05:21:37 CEST)

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Preprint TECHNICAL NOTE | doi:10.20944/preprints201809.0539.v1

Regression Models with Stochastic Regressors: An Expository note

Sulaxana Bharali, Jiten Hazarika

Subject: Computer Science And Mathematics, Probability And Statistics Keywords: Non-normality, Classical Linear Regression Model, Modified Maximum Likelihood Estimation.

Online: 27 September 2018 (10:04:26 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201808.0429.v1

Impact of Heat Pumps Flexibility in a French Residential Eco-District

Camille Pajot, Benoit Delinchant, Yves Maréchal, Damien Frésier

Subject: Engineering, Energy And Fuel Technology Keywords: Peak Shaving; Demand Response; Block of Buildings; Thermal Model; TEASER

Online: 24 August 2018 (09:09:12 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201807.0430.v1

Multi-Criteria Measurement of Farming Organizations Sustainable Innovativeness: Evidence from Lithuania

Rolandas Drejeris, Astrida Miceikiene

Subject: Business, Economics And Management, Business And Management Keywords: sustainable innovativeness; multi-criteria assessment; farms, agriculture, model of measurement

Online: 23 July 2018 (15:11:22 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201807.0272.v1

Carbon Nanocones with Curvature Effects Close to Vertex

Barry J Cox, James M Hill

Subject: Chemistry And Materials Science, Nanotechnology Keywords: carbon nanocones; geometry; rolled-up model; curvature effects; analytical formulae

Online: 16 July 2018 (10:18:50 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201803.0212.v1

Early Fetal Weight Estimation with Expectation Maximization Algorithm

Loc Nguyen, Thu-Hang T. Ho

Subject: Medicine And Pharmacology, Obstetrics And Gynaecology Keywords: fetal weight estimation; regression model; ultrasound measures; expectation maximization algorithm

Online: 26 March 2018 (09:59:51 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201705.0083.v1

Real-time Analysis of a Modified State Observer for Sensorless Induction Motor Drive used in Electric Vehicle Applications

Mohan Krishna S, Febin Daya J L, Sanjeevikumar Padmanaban, Lucian MIHET-POPA

Subject: Engineering, Electrical And Electronic Engineering Keywords: state estimation; model reference; sliding mode; real-time; parameter detuning

Online: 9 May 2017 (11:01:45 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201610.0003.v1

2nd life batteries on a gas turbine power plant to provide area regulation services.

Lluc Canals Casals, Beatriz Amante García

Subject: Engineering, Energy And Fuel Technology Keywords: Aging model; Lithium ion batteries; Second life applications, Area regulation

Online: 3 October 2016 (16:33:54 CEST)

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Preprint ARTICLE | doi:10.20944/preprints201903.0080.v1

Definition of Internet of Things (IoT) Cyber Risk – Discussion on a Transformation Roadmap for Standardisation of Regulations, Risk Maturity, Strategy Design and Impact Assessment

Petar Radanliev, David De Roure, Jason R.C. Nurse, Pete Burnap, Eirini Anthi, Uchenna Ani, La’Treall Maddox, Omar Santos, Rafael Mantilla Montalvo

Subject: Engineering, Control And Systems Engineering Keywords: Internet of Things; Micro Mart model; Goal-Oriented Approach; transformation roadmap; Cyber risk regulations; empirical analysis; cyber risk self-assessment; cyber risk target state

Online: 6 March 2019 (11:47:04 CET)

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Preprint ARTICLE | doi:10.20944/preprints202307.1623.v1

The Efficacy of Multi-Period Long-Term Power Transmission Network Expansion with Penetration of Renewable Sources

Gideon Ude Nnachi, Yskandar Hamam, Coneth Graham Richards

Subject: Engineering, Electrical And Electronic Engineering Keywords: Alternating Current Model, Direct Current Model, Energy Demand; Mixed Integer Linear Programming, Maximum Generation Capacity, Optimal Generation Capacity, Renewable Energy Penetration, Transmission Network Expansion Planning.

Online: 25 July 2023 (05:42:39 CEST)

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Electrical energy demand increase does evolve rapidly due to several socioeconomic factors such as industrialization, population growth, urbanization and of course the evolution of modern technologies in this 4th industrial revolution era. Such rapid increase in energy demand introduces a huge challenge in power system. Such has paved way for network operators to seek for alternative energy resources other than the conventional fossil fuel system. Hence, the penetration of renewable energy into the electricity supply mix has evolved rapidly in the past three decades. However, the grid system has to be well planned ahead to accommodate such increase in energy demand in the long run. Transmission Network Expansion Planning (TNEP) is a well ordered and profitable expansion of power facilities that meets the expected electric energy demand with an allowable degree of reliability. This paper proposes a TNEP model that minimises the network reinforcements, operational costs and costs of renewable energy penetrations, while satisfying the increase in demand. The problem is formulated as a mixed integer linear programming (MILP) problem. The developed model has been tested in several IEEE test systems in multi-period scenarios. The paper also carried out a detailed derivation of the new non-negative variables in terms of the power flow magnitudes, the bus voltage phase angles and the lines’ phase angles for proper mixed integer variables’ decomposition techniques. Moreover, this paper tends to provide additional recommendation in terms of which particular year (within 20 years of planning period) can the network operators install new line(s), new corridor(s) and/or additional generation capacity to the respective existing power networks. Such is achieved by running incremental periods simulations from base year through the planning horizon. The results show the efficacy of the developed model in solving the TNEP problem with a reduced and acceptable computation time even for large power grid system.

Preprint ARTICLE | doi:10.20944/preprints202409.1103.v1

PEDRO: Privacy-Enhancing Decision suppoRt tOol

Paul Van Schaik, Karen V Renaud

Subject: Computer Science And Mathematics, Security Systems Keywords: privacy-enhancing tool; technology adoption; step model; PET decision support tool

Online: 16 September 2024 (09:21:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202409.0644.v1

From Behavior Modes to Fundamental Questions to Answer through System Dynamics Modeling

Martin FG. Schaffernicht

Subject: Business, Economics And Management, Other Keywords: model conceptualization; reference behavior modes; systemic behavior; modeling competence development; validation

Online: 9 September 2024 (09:01:18 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.0249.v1

Three-dimensional Fuzzy Modeling for Nonlinear Distributed Parameter Systems Using Simultaneous Perturbation Stochastic Approximation

Xianxia Zhang, Tangchen Wang, Chong Cheng, Shaopu Wang

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: distributed parameter system; fuzzy model; simultaneous perturbation stochastic approximation; fuzzy modeling

Online: 5 August 2024 (08:22:47 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.0192.v1

Fault Diagnosis of Maritime Equipment Using an Intelligent Framework

L.F. Mendonça, J. M. C. Sousa, S. M. Vieira

Subject: Engineering, Marine Engineering Keywords: intelligent fault diagnosis; model-based fault diagnosis; fuzzy modeling; marine equipment

Online: 5 August 2024 (03:42:36 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202408.0005.v1

Electrochemical Performance of Ti Gr. 2 as Electrodes in Contact with Saline Suspension of Clays during Electroflotation Process

Alvaro Soliz, Felipe M. Galleguillos-Madrid, José Ángel Cobos-Murcia, Sebastián Angulo A., Sebastian Salazar-Avalos, Bernabé Alonso-Fariñas, Carlos Portillo, Alexis Guzmán

Subject: Chemistry And Materials Science, Chemical Engineering Keywords: kaolinite clay; montmorillonite clay; electroflotation; titanium Gr. 2 electrode; superposition model

Online: 1 August 2024 (11:09:30 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202407.0122.v1

Easy Laundry on Mobile Phone

Wisnu Uriawan, Ahmad Juaeni Yunus, Dimas Arya Nurhakim, Citra Aulia, Ahmad Badru Al Husaeni, Adil Zukhruf Firdaus, Annasrulloh Hidayat

Subject: Computer Science And Mathematics, Information Systems Keywords: Application, Shuttle laundry services,SDLC, Waterfall model, Laravel, Black box testing

Online: 2 July 2024 (10:14:55 CEST)

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In this digital era, laundry applications come as an innovative solution to meet the laundry needs of modern people who often have busy schedules and limited time. This research aims to make a significant contribution to our broader understanding of how digital innovations can revolutionize mundane tasks. This research uses the Waterfall model, which is one of the methods in the Software Development Life Cycle (SDLC). The development process begins with the Requirement Analysis stage, where application requirements and specifications are collected and thoroughly analyzed to ensure that the developed application will meet user expectations. After that, the System Design stage is conducted, where the application architecture, user interface design, and database structure are designed in detail to ensure conformity with the previously identified needs.The next stage is Implementation, where program code is written and application features are developed according to the design that has been made. The final stage is Integration and Testing, where all application components are combined and tested thoroughly to detect and fix any errors or bugs that may exist. The results of this study produced a web-based shuttle laundry service application using the Laravel framework called "All Fresh Laundry". This application can order clothes washing services according to its membership, where there are 3 types of membership based on price and of course have different benefits. In addition, the testing phase of this application using black box testing shows that all menu features function properly according to their functions. Each component of the "All Fresh Laundry" app was thoroughly tested to ensure that no errors or malfunctions occurred. The results of this testing make it clear that every feature, from online ordering to laundry status tracking, works well and meets the specifications that have been set, so that this application can provide an optimal and reliable user experience.

Preprint ARTICLE | doi:10.20944/preprints202406.1726.v1

Climate-Smart Agriculture: Optimizing Input Allocation for Sustainable Productivity

Samidh Pal

Subject: Social Sciences, Other Keywords: Climate-smart agriculture; Weather variables; Production function model; Sustainability; Agricultural productivity

Online: 25 June 2024 (10:10:00 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202406.1066.v1

Optimization of a Sonophotocatalysis Water Treatment Process Using Inverse Artificial Neural Networks

YOUNESS EL HAMZAOUI, Nancy Pérez Morga, Beatriz Fernanda Tejero Campos

Subject: Environmental And Earth Sciences, Environmental Science Keywords: artificial intelligence; mathematical model; objective function; optimal parameters; water treatment process

Online: 17 June 2024 (08:34:53 CEST)

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Preprint COMMUNICATION | doi:10.20944/preprints202403.0942.v2

Environmental Surveillance through Machine Learning-Empowered Utilization of Optical Networks

Hasan Awad, Fehmida Usmani, Emanuele Virgillito, Rudi Bratovich, Roberto Proietti, Stefano Straullu, Francesco Aquilino, Rosanna Pastorelli, Vittorio Curri

Subject: Environmental And Earth Sciences, Environmental Science Keywords: Earthquakes; Polarization; Machine-learning; Early-warnings; Optical-Networks; Sensing; Waveplate-model

Online: 7 May 2024 (17:32:06 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202402.0023.v1

A Conceptual Framework to Analyze Urban Digital Twins Interoperability

Mamadou Kaba Traoré

Subject: Computer Science And Mathematics, Information Systems Keywords: Urban Digital Twin; Smart City; Smart Territory; Interoperability; High-Level Model

Online: 1 February 2024 (05:43:43 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.1411.v1

Unsteady Subsonic/Supersonic Flow Simulations in 3D Unstructured Grids over an Acoustic Cavity

Guillermo Araya

Subject: Engineering, Aerospace Engineering Keywords: URANS; SST; SAS; turbulence model; compressible flow; unstructured grid; complex geometry

Online: 18 January 2024 (11:37:31 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0921.v1

Investigating Postconsumer Clothing Wastes for Sustainable Waste Management: A Circular Economy Approach

Samuel Aysheshim, Shalemu Sharew Hailemariam

Subject: Chemistry And Materials Science, Other Keywords: recycling; sustainability; circular Economy; post-consumer clothing waste; business model; composites

Online: 11 January 2024 (12:09:19 CET)

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Preprint ARTICLE | doi:10.20944/preprints202401.0864.v1

Lattice Boltzmann Method-based Numerical Simulation for Heavy Metal Migration Process during Deep-sea Mining

Lei Yin, Dongdong Chen, Yunqi Yang, Xuedan Wei, Houping Dai, Juan Zeng, Hanxin Huo

Subject: Environmental And Earth Sciences, Waste Management And Disposal Keywords: Deep sea mining; Heavy metals migration; Coupling model; Lattice Boltzmann method

Online: 11 January 2024 (09:19:14 CET)

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Preprint CONCEPT PAPER | doi:10.20944/preprints202312.2279.v1

Accelerated CognitiveWarfare via the Dual Use of Large Language Models

Tam Nguyen

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: cognitive warfare; large language model; artificial intelligence; cognitive behavioral therapy; cybersecurity

Online: 29 December 2023 (13:15:29 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.1807.v1

Evaluation of Multiphase Flow Models in Wellbores

Lixing Lin

Subject: Engineering, Energy And Fuel Technology Keywords: Multiphase flow; Drift-flux model; Matlab programming; Nodal analysis; Production engineering.

Online: 25 December 2023 (11:14:36 CET)

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Well deliverability optimization is essential for oil and gas production and nodal analysis is a common tool used for selecting suitable production parameters. To accurately calculate upstream and downstream pressures at various production rates at a certain selected node, proper modeling of multiphase flow in wellbores is necessary. However, this process is complex due to the inconsistent velocities of the fluids (i.e., oil, gas, and water) and the interaction between the liquids under high temperature and pressure. Empirical models, such as Hagedorn and Brown (1965), Beggs and Brill (1973), and Mukherjee and Brill (1983 and 1985), and the drift-flux model (Zuber 1965) are commonly used for multiphase flow calculations in wellbores. In this paper, we programmed and evaluated three multiphase flow models (Hagedorn-Brown, Mukherjee-Brill, and drift-flux) using Matlab. The programming includes holdup calculation, pressure gradient calculation, pressure traverse calculation, inflow curve determination, inflow performance relationship (IPR) curve determination, and well deliverability determination. Additionally, we conducted a case study to examine the sensitivity of parameters and compare and analyze the results of pressure traverse, tubing intake curve, and deliverability determination between the drift-flux and Mukherjee-Brill models. Sensitivity analysis was conducted on two of the seven parameters in the drift-flux model, and the effects of production and reservoir parameters on well deliverability were analyzed. The case study results indicated that the Mukherjee-Brill model predicted slightly higher bottomhole pressure compared to the drift-flux model at a fixed oil flow rate, but its well deliverability determination was lower. Furthermore, the drift-flux model showed that the pressure increased with an increase in the distribution coefficient for bubble flow (C0_bubble), while the beta parameter had little impact on the calculated pressure in the studied range. The well deliverability increased when the tubing size and reservoir pressure increased, or the tubing head pressure decreased.

Preprint ARTICLE | doi:10.20944/preprints202312.1181.v1

Application of Geographic Information Systems in Analysing Topographic Roughness for Nyanga District of Zimbabwe

Ezra Chipatiso

Subject: Computer Science And Mathematics, Data Structures, Algorithms And Complexity Keywords: Topographic Roughness Index; Geographic Information Systems; Digital Elevation Model; Focal Statistics

Online: 15 December 2023 (14:53:52 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.0705.v1

Numerical analysis of the TRC shells: Basic principles

Iurii Vakaliuk, Silke Scheerer, Manfred Curbach

Subject: Engineering, Civil Engineering Keywords: Textile reinforced concrete; TRC; shell; material characteristics; material model; numerical investigation

Online: 11 December 2023 (15:17:08 CET)

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Preprint ARTICLE | doi:10.20944/preprints202312.0444.v1

Approaches of Combining Machine Learning with NMR-based Pore Structure Characterization for Reservoir Evaluation

Wenjun Zhao, Tangyan Liu, Jian Yang, Zhuo Zhang, Cheng Feng, Jizhou Tang

Subject: Engineering, Energy And Fuel Technology Keywords: Machine learning; Intelligent evaluation and prediction; Spherical-Tubular model; Petrophysical parameters

Online: 7 December 2023 (03:07:53 CET)

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Tight gas, a category of Deep Green Energy Resources, rely on advanced intelligent monitoring methods for their extraction. Conventional logging for reservoir evaluation relies on logging data and the manual setting of evaluation criteria to classify reservoirs. However, the complexity and heterogeneity of tight reservoirs pose challenges in accurately identifying target layers by using traditional well-logging techniques. Machine learning may hold the key to solving this problem, as it enables computers to learn without being explicitly programmed and manually added rules. Therefore, it is possible to make reservoir evaluation via using machine learning methods. In this paper, the reservoir quality index (RQI) and porous geometric parameters obtained from the optimized inversion of the spherical-tubular model are adopted to evaluate the reservoir. Then, three different machine learning approaches, the random forest (RF) algorithm, support vector machine (SVM) algorithm, and extreme gradient boosting (XGB) algorithm, are utilized for reservoir classification. The selected dataset covers more than 7,000 samples from five wells. The data from four wells are arranged as the training dataset, and the data of the remaining one well is designed as the testing dataset to calculate the prediction accuracies of different machine learning algorithms. Among them, accuracies of RF, SVM, and XGB are all higher than 90%, and XGB owns the highest result by reaching 97%. Machine learning based approaches can greatly assist reservoir prediction by implementing the well-logging data. The research highlights the application of reservoir classification with a higher prediction accuracy by combining machine learning algorithms with NMR logging based pore structure characterization, which can provide a guideline for sweet spot identification within the tight formation. This not only optimizes resource extraction but also aligns with the global shift towards clean and renewable energy sources, promoting sustainability and reducing the carbon footprint associated with conventional energy production. In summary, the fusion of machine learning and NMR logging based reservoir evaluation plays a crucial role in advancing both energy efficiency and the transition to cleaner energy sources.

Preprint ARTICLE | doi:10.20944/preprints202311.0919.v1

Injectivity Assessment of Radial-Lateral Wells for CO₂ Storage in Marine Gas Hydrate Reservoirs

Boyun Guo, Peng Zhang

Subject: Environmental And Earth Sciences, Waste Management And Disposal Keywords: CO2 storage; radial-lateral well; well injectivity; permissible pressure; analytical model.

Online: 14 November 2023 (11:27:41 CET)

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Preprint ARTICLE | doi:10.20944/preprints202310.1473.v1

Remote Diagnosis on Upper Respiratory Tract Infections Based on Neural Network with Few Symptom Words – a Feasibility Study

Chung-Hung Tsai, Kuan-Hung Liu, Da-Chuan Cheng

Subject: Medicine And Pharmacology, Clinical Medicine Keywords: natural language; remote diagnosis; GPT-2 model; deep learning; symptom words

Online: 24 October 2023 (08:34:37 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202310.1162.v1

RS Transformer: A Two-Stage Region Proposal Using the Swin Transformer for Few-Shot Pest Detection in Automated Agricultural Monitoring Systems

Tengyue Wu, Liantao Shi, Lei Zhang, Xingkai Wen, Jianjun Lu, Zhengguo Li

Subject: Computer Science And Mathematics, Artificial Intelligence And Machine Learning Keywords: Swin Transformer; Pest detection; Diffusion model; Feature extraction; Few-shot learning

Online: 18 October 2023 (17:20:58 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202310.0242.v1

Influence of Dose, Particle Size &Amp; Concentration on Dermal Penetration Efficacy of Curcumin

Em-on Chaiprateep, Sabrina Wiemann, Ralph W Eckert, Christian S. Raab, Soma Sengupta, Cornelia M. Keck

Subject: Medicine And Pharmacology, Dermatology Keywords: nanocrystals; curcumin; aqueous meniscus; dermal penetration; ex-vivo model; porcine skin

Online: 5 October 2023 (02:10:32 CEST)

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Preprint ARTICLE | doi:10.20944/preprints202308.1139.v2

The Impact of Agricultural Credit on the Growth of the Agricultural Sector in Angola

Mario A. Caetano Joao, Abreu Monteiro de Castro

Subject: Business, Economics And Management, Econometrics And Statistics Keywords: agricultural sector; agricultural credit; economic growth; Angola; ARDL model; econometric analysis

Online: 26 September 2023 (13:53:32 CEST)

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