@article{SchuchKaps,
  author    = {Schuch, Kai and Kaps, Christian},
  title     = {Maturation and Structure Formation Processes in Binders with Aqueous Alkali-Silicate Solutions},
  doi       = {10.25643/bauhaus-universitaet.3597},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20170907-35979},
  pages     = {1 -- 16},
  abstract  = {Maturation and structure formation processes can lead to crack formation in silicate and aluminosilicate binders (e.g. for coating materials...) through restricted deformation, loss of strength and thus to loss of durability. These processes are evaluated with silicate materials with an outlook on aluminosilicate binders.},
  subject      = {Waterglass},
  language  = {en}
}
@article{Zhang,
  author    = {Zhang, Yongzheng},
  title     = {Nonlocal dynamic Kirchhoff plate formulation based on nonlocal operator method},
  series = {Engineering with Computers},
  volume    = {2022},
  journal   = {Engineering with Computers},
  publisher = {Springer},
  address   = {London},
  doi       = {10.1007/s00366-021-01587-1},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220209-45849},
  pages     = {1 -- 35},
  abstract  = {In this study, we propose a nonlocal operator method (NOM) for the dynamic analysis of (thin) Kirchhoff plates. The nonlocal Hessian operator is derived based on a second-order Taylor series expansion. The NOM does not require any shape functions and associated derivatives as 'classical' approaches such as FEM, drastically facilitating the implementation. Furthermore, NOM is higher order continuous, which is exploited for thin plate analysis that requires C1 continuity. The nonlocal dynamic governing formulation and operator energy functional for Kirchhoff plates are derived from a variational principle. The Verlet-velocity algorithm is used for the time discretization. After confirming the accuracy of the nonlocal Hessian operator, several numerical examples are simulated by the nonlocal dynamic Kirchhoff plate formulation.},
  subject      = {Angewandte Mathematik},
  language  = {en}
}
@article{RabczukGuoZhuangetal.,
  author    = {Rabczuk, Timon and Guo, Hongwei and Zhuang, Xiaoying and Chen, Pengwan and Alajlan, Naif},
  title     = {Stochastic deep collocation method based on neural architecture search and transfer learning for heterogeneous porous media},
  series = {Engineering with Computers},
  volume    = {2022},
  journal   = {Engineering with Computers},
  publisher = {Springer},
  address   = {London},
  doi       = {10.1007/s00366-021-01586-2},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220209-45835},
  pages     = {1 -- 26},
  abstract  = {We present a stochastic deep collocation method (DCM) based on neural architecture search (NAS) and transfer learning for heterogeneous porous media. We first carry out a sensitivity analysis to determine the key hyper-parameters of the network to reduce the search space and subsequently employ hyper-parameter optimization to finally obtain the parameter values. The presented NAS based DCM also saves the weights and biases of the most favorable architectures, which is then used in the fine-tuning process. We also employ transfer learning techniques to drastically reduce the computational cost. The presented DCM is then applied to the stochastic analysis of heterogeneous porous material. Therefore, a three dimensional stochastic flow model is built providing a benchmark to the simulation of groundwater flow in highly heterogeneous aquifers. The performance of the presented NAS based DCM is verified in different dimensions using the method of manufactured solutions. We show that it significantly outperforms finite difference methods in both accuracy and computational cost.},
  subject      = {Maschinelles Lernen},
  language  = {en}
}
@article{KapsSchuchStaeblein,
  author    = {Kaps, Christian and Schuch, Kai and St{\"a}blein, Stefan},
  title     = {Silicate coatings for concrete components with waterglass systems by means of neutral salt initiation},
  doi       = {10.25643/bauhaus-universitaet.2588},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20160601-25888},
  pages     = {1 -- 14},
  abstract  = {The objective of the investigations was the proof of the use of the neutral salt initiation as a construction material in the protecting silicate coating of concrete components, e.g. factory finished parts or reinforced concrete construction parts, by means of waterglass fused silica suspensions},
  subject      = {Silicate},
  language  = {en}
}
@article{Lahmer,
  author    = {Lahmer, Tom},
  title     = {FEM-Based determination of real and complex elastic, dielectric, and piezoelectric moduli in piezoceramic materials},
  series = {IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control},
  journal   = {IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control},
  doi       = {10.25643/bauhaus-universitaet.3608},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20171030-36083},
  abstract  = {We propose an enhanced iterative scheme for the precise reconstruction of piezoelectric material parameters from electric impedance and mechanical displacement measurements. It is based on finite-element simulations of the full three-dimensional piezoelectric equations, combined with an inexact Newton or nonlinear Landweber iterative inversion scheme. We apply our method to two piezoelectric materials and test its performance. For the first material, the manufacturer provides a full data set; for the second one, no material data set is available. For both cases, our inverse scheme, using electric impedance measurements as input data, performs well.},
  subject      = {Finite-Elemente-Methode},
  language  = {en}
}
@article{AlYasiriMutasharGuerlebecketal.,
  author    = {Al-Yasiri, Zainab Riyadh Shaker and Mutashar, Hayder Majid and G{\"u}rlebeck, Klaus and Lahmer, Tom},
  title     = {Damage Sensitive Signals for the Assessment of the Conditions of Wind Turbine Rotor Blades Using Electromagnetic Waves},
  series = {Infrastructures},
  volume    = {2022},
  journal   = {Infrastructures},
  number    = {Volume 7, Issue 8 (August 2022), article 104},
  editor    = {Shafiullah, GM},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/infrastructures7080104},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20220831-47093},
  pages     = {18},
  abstract  = {One of the most important renewable energy technologies used nowadays are wind power turbines. In this paper, we are interested in identifying the operating status of wind turbines, especially rotor blades, by means of multiphysical models. It is a state-of-the-art technology to test mechanical structures with ultrasonic-based methods. However, due to the density and the required high resolution, the testing is performed with high-frequency waves, which cannot penetrate the structure in depth. Therefore, there is a need to adopt techniques in the fields of multiphysical model-based inversion schemes or data-driven structural health monitoring. Before investing effort in the development of such approaches, further insights and approaches are necessary to make the techniques applicable to structures such as wind power plants (blades). Among the expected developments, further accelerations of the so-called "forward codes" for a more efficient implementation of the wave equation could be envisaged. Here, we employ electromagnetic waves for the early detection of cracks. Because in many practical situations, it is not possible to apply techniques from tomography (characterized by multiple sources and sensor pairs), we focus here on the question of whether the existence of cracks can be determined by using only one source for the sent waves.},
  subject      = {Windkraftwerk},
  language  = {en}
}
@article{Legatiuk,
  author    = {Legatiuk, Dmitrii},
  title     = {Mathematical Modelling by Help of Category Theory: Models and Relations between Them},
  series = {mathematics},
  volume    = {2021},
  journal   = {mathematics},
  number    = {volume 9, issue 16, article 1946},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/math9161946},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210817-44844},
  pages     = {17},
  abstract  = {The growing complexity of modern practical problems puts high demand on mathematical modelling. Given that various models can be used for modelling one physical phenomenon, the role of model comparison and model choice is becoming particularly important. Methods for model comparison and model choice typically used in practical applications nowadays are computationbased, and thus time consuming and computationally costly. Therefore, it is necessary to develop other approaches to working abstractly, i.e., without computations, with mathematical models. An abstract description of mathematical models can be achieved by the help of abstract mathematics, implying formalisation of models and relations between them. In this paper, a category theory-based approach to mathematical modelling is proposed. In this way, mathematical models are formalised in the language of categories, relations between the models are formally defined and several practically relevant properties are introduced on the level of categories. Finally, an illustrative example is presented, underlying how the category-theory based approach can be used in practice. Further, all constructions presented in this paper are also discussed from a modelling point of view by making explicit the link to concrete modelling scenarios.},
  subject      = {Kategorientheorie},
  language  = {en}
}
@article{GhazvineiDarvishiMosavietal.,
  author    = {Ghazvinei, Pezhman Taherei and Darvishi, Hossein Hassanpour and Mosavi, Amir and Yusof, Khamaruzaman bin Wan and Alizamir, Meysam and Shamshirband, Shahaboddin and Chau, Kwok-Wing},
  title     = {Sugarcane growth prediction based on meteorological parameters using extreme learning machine and artificial neural network},
  series = {Engineering Applications of Computational Fluid Mechanics},
  volume    = {2018},
  journal   = {Engineering Applications of Computational Fluid Mechanics},
  number    = {12,1},
  publisher = {Taylor \& Francis},
  doi       = {10.1080/19942060.2018.1526119},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20181017-38129},
  pages     = {738 -- 749},
  abstract  = {Management strategies for sustainable sugarcane production need to deal with the increasing complexity and variability of the whole sugar system. Moreover, they need to accommodate the multiple goals of different industry sectors and the wider community. Traditional disciplinary approaches are unable to provide integrated management solutions, and an approach based on whole systems analysis is essential to bring about beneficial change to industry and the community. The application of this approach to water management, environmental management and cane supply management is outlined, where the literature indicates that the application of extreme learning machine (ELM) has never been explored in this realm. Consequently, the leading objective of the current research was set to filling this gap by applying ELM to launch swift and accurate model for crop production data-driven. The key learning has been the need for innovation both in the technical aspects of system function underpinned by modelling of sugarcane growth. Therefore, the current study is an attempt to establish an integrate model using ELM to predict the concluding growth amount of sugarcane. Prediction results were evaluated and further compared with artificial neural network (ANN) and genetic programming models. Accuracy of the ELM model is calculated using the statistics indicators of Root Means Square Error (RMSE), Pearson Coefficient (r), and Coefficient of Determination (R2) with promising results of 0.8, 0.47, and 0.89, respectively. The results also show better generalization ability in addition to faster learning curve. Thus, proficiency of the ELM for supplementary work on advancement of prediction model for sugarcane growth was approved with promising results.},
  subject      = {K{\"u}nstliche Intelligenz},
  language  = {en}
}
@article{FaizollahzadehArdabiliNajafiAlizamiretal.,
  author    = {Faizollahzadeh Ardabili, Sina and Najafi, Bahman and Alizamir, Meysam and Mosavi, Amir and Shamshirband, Shahaboddin and Rabczuk, Timon},
  title     = {Using SVM-RSM and ELM-RSM Approaches for Optimizing the Production Process of Methyl and Ethyl Esters},
  series = {Energies},
  journal   = {Energies},
  number    = {11, 2889},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/en11112889},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20181025-38170},
  pages     = {1 -- 20},
  abstract  = {The production of a desired product needs an effective use of the experimental model. The present study proposes an extreme learning machine (ELM) and a support vector machine (SVM) integrated with the response surface methodology (RSM) to solve the complexity in optimization and prediction of the ethyl ester and methyl ester production process. The novel hybrid models of ELM-RSM and ELM-SVM are further used as a case study to estimate the yield of methyl and ethyl esters through a trans-esterification process from waste cooking oil (WCO) based on American Society for Testing and Materials (ASTM) standards. The results of the prediction phase were also compared with artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), which were recently developed by the second author of this study. Based on the results, an ELM with a correlation coefficient of 0.9815 and 0.9863 for methyl and ethyl esters, respectively, had a high estimation capability compared with that for SVM, ANNs, and ANFIS. Accordingly, the maximum production yield was obtained in the case of using ELM-RSM of 96.86\% for ethyl ester at a temperature of 68.48 °C, a catalyst value of 1.15 wt. \%, mixing intensity of 650.07 rpm, and an alcohol to oil molar ratio (A/O) of 5.77; for methyl ester, the production yield was 98.46\% at a temperature of 67.62 °C, a catalyst value of 1.1 wt. \%, mixing intensity of 709.42 rpm, and an A/O of 6.09. Therefore, ELM-RSM increased the production yield by 3.6\% for ethyl ester and 3.1\% for methyl ester, compared with those for the experimental data.},
  subject      = {Biodiesel},
  language  = {en}
}
@article{MorgenthalEickRauetal.,
  author    = {Morgenthal, Guido and Eick, Jan Frederick and Rau, Sebastian and Taraben, Jakob},
  title     = {Wireless Sensor Networks Composed of Standard Microcomputers and Smartphones for Applications in Structural Health Monitoring},
  series = {Sensors - Special Issue Selected Papers from 7th Asia-Pacific Workshop on Structural Health Monitoring},
  volume    = {2019},
  journal   = {Sensors - Special Issue Selected Papers from 7th Asia-Pacific Workshop on Structural Health Monitoring},
  number    = {Volume 19, Issue 9, 2070},
  publisher = {MDPI},
  doi       = {10.3390/s19092070},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190514-39123},
  pages     = {22},
  abstract  = {Wireless sensor networks have attracted great attention for applications in structural health monitoring due to their ease of use, flexibility of deployment, and cost-effectiveness. This paper presents a software framework for WiFi-based wireless sensor networks composed of low-cost mass market single-board computers. A number of specific system-level software components were developed to enable robust data acquisition, data processing, sensor network communication, and timing with a focus on structural health monitoring (SHM) applications. The framework was validated on Raspberry Pi computers, and its performance was studied in detail. The paper presents several characteristics of the measurement quality such as sampling accuracy and time synchronization and discusses the specific limitations of the system. The implementation includes a complementary smartphone application that is utilized for data acquisition, visualization, and analysis. A prototypical implementation further demonstrates the feasibility of integrating smartphones as data acquisition nodes into the network, utilizing their internal sensors. The measurement system was employed in several monitoring campaigns, three of which are documented in detail. The suitability of the system is evaluated based on comparisons of target quantities with reference measurements. The results indicate that the presented system can robustly achieve a measurement performance commensurate with that required in many typical SHM tasks such as modal identification. As such, it represents a cost-effective alternative to more traditional monitoring solutions.},
  subject      = {Structural Health Monitoring},
  language  = {en}
}
@article{KavrakovLegatiukGuerlebecketal.,
  author    = {Kavrakov, Igor and Legatiuk, Dmitrii and G{\"u}rlebeck, Klaus and Morgenthal, Guido},
  title     = {A categorical perspective towards aerodynamic models for aeroelastic analyses of bridge decks},
  series = {Royal Society Open Science},
  journal   = {Royal Society Open Science},
  number    = {Volume 6, Issue 3},
  doi       = {/10.1098/rsos.181848},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20190314-38656},
  pages     = {20},
  abstract  = {Reliable modelling in structural engineering is crucial for the serviceability and safety of structures. A huge variety of aerodynamic models for aeroelastic analyses of bridges poses natural questions on their complexity and thus, quality. Moreover, a direct comparison of aerodynamic models is typically either not possible or senseless, as the models can be based on very different physical assumptions. Therefore, to address the question of principal comparability and complexity of models, a more abstract approach, accounting for the effect of basic physical assumptions, is necessary. This paper presents an application of a recently introduced category theory-based modelling approach to a diverse set of models from bridge aerodynamics. Initially, the categorical approach is extended to allow an adequate description of aerodynamic models. Complexity of the selected aerodynamic models is evaluated, based on which model comparability is established. Finally, the utility of the approach for model comparison and characterisation is demonstrated on an illustrative example from bridge aeroelasticity. The outcome of this study is intended to serve as an alternative framework for model comparison and impact future model assessment studies of mathematical models for engineering applications.},
  subject      = {Br{\"u}cke},
  language  = {en}
}
@article{ChenSchwingKarlovšeketal.,
  author    = {Chen, Zhen and Schwing, Moritz and Karlovšek, Jurij and Wagner, Norman and Scheuermann, Alexander},
  title     = {Broadband Dielectric Measurement Methods for Soft Geomaterials: Coaxial Transmission Line Cell and Open-Ended Coaxial Probe},
  series = {International Journal of Engineering and Technology},
  volume    = {2014},
  journal   = {International Journal of Engineering and Technology},
  number    = {volume 6, number 5},
  doi       = {10.7763/IJET.2014.V6.728},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210408-43984},
  pages     = {373 -- 380},
  abstract  = {Broadband dielectric measurement methods based on vector network analyzer coupled with coaxial transmission line cell (CC) and open-ended coaxial probe (OC) are simply reviewed, by which the dielectric behaviors in the frequency range of 1 MHz to 3 GHz of two practical geomaterials are investigated. Kaolin after modified compaction with different water contents is measured by using CC. The results are consistent with previous study on standardized compacted kaolin and suggest that the dielectric properties at frequencies below 100 MHz are not only a function of water content but also functions of other soil state parameters including dry density. The hydration process of a commercial grout is monitored in real time by using OC. It is found that the time dependent dielectric properties can accurately reveal the different stages of the hydration process. These measurement results demonstrate the practicability of the introduced methods in determining dielectric properties of soft geomaterials.},
  subject      = {Impedanzspektroskopie},
  language  = {en}
}
@article{AlkamLahmer,
  author    = {Alkam, Feras and Lahmer, Tom},
  title     = {A robust method of the status monitoring of catenary poles installed along high-speed electrified train tracks},
  series = {Results in Engineering},
  volume    = {2021},
  journal   = {Results in Engineering},
  number    = {volume 12, article 100289},
  publisher = {Elsevier},
  address   = {Amsterdam},
  doi       = {10.1016/j.rineng.2021.100289},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20211011-45212},
  pages     = {1 -- 8},
  abstract  = {Electric trains are considered one of the most eco-friendly and safest means of transportation. Catenary poles are used worldwide to support overhead power lines for electric trains. The performance of the catenary poles has an extensive influence on the integrity of the train systems and, consequently, the connected human services. It became a must nowadays to develop SHM systems that provide the instantaneous status of catenary poles in- service, making the decision-making processes to keep or repair the damaged poles more feasible. This study develops a data-driven, model-free approach for status monitoring of cantilever structures, focusing on pre-stressed, spun-cast ultrahigh-strength concrete catenary poles installed along high-speed train tracks. The pro-posed approach evaluates multiple damage features in an unfied damage index, which leads to straightforward interpretation and comparison of the output. Besides, it distinguishes between multiple damage scenarios of the poles, either the ones caused by material degradation of the concrete or by the cracks that can be propagated during the life span of the given structure. Moreover, using a logistic function to classify the integrity of structure avoids the expensive learning step in the existing damage detection approaches, namely, using the modern machine and deep learning methods. The findings of this study look very promising when applied to other types of cantilever structures, such as the poles that support the power transmission lines, antenna masts, chimneys, and wind turbines.},
  subject      = {Fahrleitung},
  language  = {en}
}
@article{Dressel,
  author    = {Dressel, Dennys},
  title     = {Reaktivit{\"a}t von H{\"u}ttensand : Thermodynamische Grundlagen und Anwendung},
  doi       = {10.25643/bauhaus-universitaet.2677},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20160829-26778},
  pages     = {178},
  abstract  = {Die thermodynamischen Grundlagen der Hydratation von H{\"u}ttensand als Hauptbestandteil von Zementen werden erforscht. Hierbei werden thermodynamische Bildungs- und Reaktionsdaten experimentell bestimmt und berechnet. Dar{\"u}ber hinaus wird der Prozess der Feststoffaufl{\"o}sung von H{\"u}ttensand in w{\"a}ssrigen L{\"o}sungen untersucht. L{\"o}sungs- und F{\"a}llungsprozesse werden unter verschiedenen Konditionen gemessen, ausgewertet und diskutiert. Die Ergebnisse werden im weiteren Verlauf zur Bestimmung der Hydratationsgrades in Pasten sowie zum besseren Verst{\"a}ndnis in der Wechselwirkung zwischen H{\"u}ttensanden und Mahlhilfsstoffen genutzt und angewandt.},
  subject      = {H{\"u}ttensand},
  language  = {de}
}
@article{Kleiner,
  author    = {Kleiner, Florian},
  title     = {Optimization and semi-automatic evaluation of a frosting process for a soda lime silicate glass based on phosphoric acid},
  series = {International Journal of Applied Glass Science},
  journal   = {International Journal of Applied Glass Science},
  publisher = {John Wiley \& Sons},
  doi       = {10.1111/ijag.15866},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210701-44548},
  pages     = {1 -- 8},
  abstract  = {Chemical glass frosting processes are widely used to create visual attractive glass surfaces. A commonly used frosting bath mainly contains ammonium bifluoride (NH4HF2) mixed with hydrochloric acid (HCl). The frosting process consists of several baths. Firstly, the preliminary bath to clean the object. Secondly, the frosting bath which etches the rough light scattering structure into the glass surface. Finally, the washing baths to clean the frosted object. This is where the constituents of the preceding steps accumulate and have to be filtered from the sewage. In the present contribution, phosphoric acid (H3PO4) was used as a substitute for HCl to reduce the amount of ammonium (NH4+) and chloride (Cl-) dissolved in the waste water. In combination with magnesium carbonate (MgCO3), it allows the precipitation of ammonium within the sewage as ammonium magnesium phosphate (MgNH4PO4). However, a trivial replacement of HCl by H3PO4 within the frosting process causes extensive frosting errors, such as inhomogeneous size distributions of the structures or domains that are not fully covered by these structures. By modifying the preliminary bath composition, it was possible to improve the frosting result considerably. To determine the optimal composition of the preliminary bath, a semi-automatic evaluation method has been developed. This method renders the objective comparison of the resulting surface quality possible.},
  subject      = {Silicatglas},
  language  = {en}
}
@article{StaubachMachacekSkowroneketal.2020,
  author    = {Staubach, Patrick and Machacek, Jan and Skowronek, Josefine and Wichtmann, Torsten},
  title     = {Vibratory pile driving in water-saturated sand: Back-analysis of model tests using a hydro-mechanically coupled CEL method},
  series = {Soils and Foundations},
  volume    = {2021},
  journal   = {Soils and Foundations},
  number    = {Volume 61, Issue 1},
  publisher = {Elsevier, Science Direct},
  address   = {Amsterdam},
  doi       = {10.1016/j.sandf.2020.11.005},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20210203-43571},
  pages     = {144 -- 159},
  year      = {2020},
  abstract  = {The development of a hydro-mechanically coupled Coupled-Eulerian-Lagrangian (CEL) method and its application to the back-analysisof vibratory pile driving model tests in water-saturated sand is presented. The predicted pile penetration using this approachis in good agreement with the results of the model tests as well as with fully Lagrangian simulations. In terms of pore water pressure, however, the results of the CEL simulation show a slightly worse accordance with the model tests compared to the Lagrangian simulation. Some shortcomings of the hydro-mechanically coupled CEL method in case of frictional contact problems and pore fluids with high bulk modulus are discussed. Lastly, the CEL method is applied to the simulation of vibratory driving of open-profile piles under partially drained conditions to study installation-induced changes in the soil state. It is concluded that the proposed method is capable of realistically reproducing the most important mechanisms in the soil during the driving process despite its addressed shortcomings.},
  subject      = {Plastische Deformation},
  language  = {en}
}
@article{SadeghzadehMaddahAhmadietal.,
  author    = {Sadeghzadeh, Milad and Maddah, Heydar and Ahmadi, Mohammad Hossein and Khadang, Amirhosein and Ghazvini, Mahyar and Mosavi, Amir Hosein and Nabipour, Narjes},
  title     = {Prediction of Thermo-Physical Properties of TiO2-Al2O3/Water Nanoparticles by Using Artificial Neural Network},
  series = {Nanomaterials},
  volume    = {2020},
  journal   = {Nanomaterials},
  number    = {Volume 10, Issue 4, 697},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/nano10040697},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200421-41308},
  abstract  = {In this paper, an artificial neural network is implemented for the sake of predicting the thermal conductivity ratio of TiO2-Al2O3/water nanofluid. TiO2-Al2O3/water in the role of an innovative type of nanofluid was synthesized by the sol-gel method. The results indicated that 1.5 vol.\% of nanofluids enhanced the thermal conductivity by up to 25\%. It was shown that the heat transfer coefficient was linearly augmented with increasing nanoparticle concentration, but its variation with temperature was nonlinear. It should be noted that the increase in concentration may cause the particles to agglomerate, and then the thermal conductivity is reduced. The increase in temperature also increases the thermal conductivity, due to an increase in the Brownian motion and collision of particles. In this research, for the sake of predicting the thermal conductivity of TiO2-Al2O3/water nanofluid based on volumetric concentration and temperature functions, an artificial neural network is implemented. In this way, for predicting thermal conductivity, SOM (self-organizing map) and BP-LM (Back Propagation-Levenberq-Marquardt) algorithms were used. Based on the results obtained, these algorithms can be considered as an exceptional tool for predicting thermal conductivity. Additionally, the correlation coefficient values were equal to 0.938 and 0.98 when implementing the SOM and BP-LM algorithms, respectively, which is highly acceptable. View Full-Text},
  subject      = {W{\"a}rmeleitf{\"a}higkeit},
  language  = {en}
}
@article{SaadatfarKhosraviHassannatajJoloudarietal.,
  author    = {Saadatfar, Hamid and Khosravi, Samiyeh and Hassannataj Joloudari, Javad and Mosavi, Amir and Shamshirband, Shahaboddin},
  title     = {A New K-Nearest Neighbors Classifier for Big Data Based on Efficient Data Pruning},
  series = {Mathematics},
  volume    = {2020},
  journal   = {Mathematics},
  number    = {volume 8, issue 2, article 286},
  publisher = {MDPI},
  doi       = {10.3390/math8020286},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200225-40996},
  pages     = {12},
  abstract  = {The K-nearest neighbors (KNN) machine learning algorithm is a well-known non-parametric classification method. However, like other traditional data mining methods, applying it on big data comes with computational challenges. Indeed, KNN determines the class of a new sample based on the class of its nearest neighbors; however, identifying the neighbors in a large amount of data imposes a large computational cost so that it is no longer applicable by a single computing machine. One of the proposed techniques to make classification methods applicable on large datasets is pruning. LC-KNN is an improved KNN method which first clusters the data into some smaller partitions using the K-means clustering method; and then applies the KNN for each new sample on the partition which its center is the nearest one. However, because the clusters have different shapes and densities, selection of the appropriate cluster is a challenge. In this paper, an approach has been proposed to improve the pruning phase of the LC-KNN method by taking into account these factors. The proposed approach helps to choose a more appropriate cluster of data for looking for the neighbors, thus, increasing the classification accuracy. The performance of the proposed approach is evaluated on different real datasets. The experimental results show the effectiveness of the proposed approach and its higher classification accuracy and lower time cost in comparison to other recent relevant methods.},
  subject      = {Maschinelles Lernen},
  language  = {en}
}
@article{ShamshirbandBabanezhadMosavietal.,
  author    = {Shamshirband, Shahaboddin and Babanezhad, Meisam and Mosavi, Amir and Nabipour, Narjes and Hajnal, Eva and Nadai, Laszlo and Chau, Kwok-Wing},
  title     = {Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants},
  series = {Engineering Applications of Computational Fluid Mechanics},
  volume    = {2020},
  journal   = {Engineering Applications of Computational Fluid Mechanics},
  number    = {volume 14, issue 1},
  publisher = {Taylor \& Francis},
  doi       = {10.1080/19942060.2020.1715842},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200227-41013},
  pages     = {367 -- 378},
  abstract  = {A novel combination of the ant colony optimization algorithm (ACO)and computational fluid dynamics (CFD) data is proposed for modeling the multiphase chemical reactors. The proposed intelligent model presents a probabilistic computational strategy for predicting various levels of three-dimensional bubble column reactor (BCR) flow. The results prove an enhanced communication between ant colony prediction and CFD data in different sections of the BCR.},
  subject      = {Maschinelles Lernen},
  language  = {en}
}
@article{AmirinasabShamshirbandChronopoulosetal.,
  author    = {Amirinasab, Mehdi and Shamshirband, Shahaboddin and Chronopoulos, Anthony Theodore and Mosavi, Amir and Nabipour, Narjes},
  title     = {Energy-Efficient Method for Wireless Sensor Networks Low-Power Radio Operation in Internet of Things},
  series = {electronics},
  volume    = {2020},
  journal   = {electronics},
  number    = {volume 9, issue 2, 320},
  publisher = {MDPI},
  doi       = {10.3390/electronics9020320},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200213-40954},
  pages     = {20},
  abstract  = {The radio operation in wireless sensor networks (WSN) in Internet of Things (IoT)applications is the most common source for power consumption. Consequently, recognizing and controlling the factors affecting radio operation can be valuable for managing the node power consumption. Among essential factors affecting radio operation, the time spent for checking the radio is of utmost importance for monitoring power consumption. It can lead to false WakeUp or idle listening in radio duty cycles and ContikiMAC. ContikiMAC is a low-power radio duty-cycle protocol in Contiki OS used in WakeUp mode, as a clear channel assessment (CCA) for checking radio status periodically. This paper presents a detailed analysis of radio WakeUp time factors of ContikiMAC. Furthermore, we propose a lightweight CCA (LW-CCA) as an extension to ContikiMAC to reduce the Radio Duty-Cycles in false WakeUps and idle listening though using dynamic received signal strength indicator (RSSI) status check time. The simulation results in the Cooja simulator show that LW-CCA reduces about 8\% energy consumption in nodes while maintaining up to 99\% of the packet delivery rate (PDR).},
  subject      = {Internet der Dinge},
  language  = {en}
}
@article{NabipourDehghaniMosavietal.,
  author    = {Nabipour, Narjes and Dehghani, Majid and Mosavi, Amir and Shamshirband, Shahaboddin},
  title     = {Short-Term Hydrological Drought Forecasting Based on Different Nature-Inspired Optimization Algorithms Hybridized With Artificial Neural Networks},
  series = {IEEE Access},
  volume    = {2020},
  journal   = {IEEE Access},
  number    = {volume 8},
  publisher = {IEEE},
  doi       = {10.1109/ACCESS.2020.2964584},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200213-40796},
  pages     = {15210 -- 15222},
  abstract  = {Hydrological drought forecasting plays a substantial role in water resources management. Hydrological drought highly affects the water allocation and hydropower generation. In this research, short term hydrological drought forecasted based on the hybridized of novel nature-inspired optimization algorithms and Artificial Neural Networks (ANN). For this purpose, the Standardized Hydrological Drought Index (SHDI) and the Standardized Precipitation Index (SPI) were calculated in one, three, and six aggregated months. Then, three states where proposed for SHDI forecasting, and 36 input-output combinations were extracted based on the cross-correlation analysis. In the next step, newly proposed optimization algorithms, including Grasshopper Optimization Algorithm (GOA), Salp Swarm algorithm (SSA), Biogeography-based optimization (BBO), and Particle Swarm Optimization (PSO) hybridized with the ANN were utilized for SHDI forecasting and the results compared to the conventional ANN. Results indicated that the hybridized model outperformed compared to the conventional ANN. PSO performed better than the other optimization algorithms. The best models forecasted SHDI1 with R2 = 0.68 and RMSE = 0.58, SHDI3 with R 2 = 0.81 and RMSE = 0.45 and SHDI6 with R 2 = 0.82 and RMSE = 0.40.},
  subject      = {Maschinelles Lernen},
  language  = {en}
}
@article{MousaviSteinkeJuniorTeixeiraetal.,
  author    = {Mousavi, Seyed Nasrollah and Steinke J{\´u}nior, Renato and Teixeira, Eder Daniel and Bocchiola, Daniele and Nabipour, Narjes and Mosavi, Amir and Shamshirband, Shahaboddin},
  title     = {Predictive Modeling the Free Hydraulic Jumps Pressure through Advanced Statistical Methods},
  series = {Mathematics},
  volume    = {2020},
  journal   = {Mathematics},
  number    = {Volume 8, Issue 3, 323},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/math8030323},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200402-41140},
  pages     = {16},
  abstract  = {Pressure fluctuations beneath hydraulic jumps potentially endanger the stability of stilling basins. This paper deals with the mathematical modeling of the results of laboratory-scale experiments to estimate the extreme pressures. Experiments were carried out on a smooth stilling basin underneath free hydraulic jumps downstream of an Ogee spillway. From the probability distribution of measured instantaneous pressures, pressures with different probabilities could be determined. It was verified that maximum pressure fluctuations, and the negative pressures, are located at the positions near the spillway toe. Also, minimum pressure fluctuations are located at the downstream of hydraulic jumps. It was possible to assess the cumulative curves of pressure data related to the characteristic points along the basin, and different Froude numbers. To benchmark the results, the dimensionless forms of statistical parameters include mean pressures (P*m), the standard deviations of pressure fluctuations (σ*X), pressures with different non-exceedance probabilities (P*k\%), and the statistical coefficient of the probability distribution (Nk\%) were assessed. It was found that an existing method can be used to interpret the present data, and pressure distribution in similar conditions, by using a new second-order fractional relationships for σ*X, and Nk\%. The values of the Nk\% coefficient indicated a single mean value for each probability.},
  subject      = {Maschinelles Lernen},
  language  = {en}
}
@article{FathiSajadzadehMohammadiSheshkaletal.,
  author    = {Fathi, Sadegh and Sajadzadeh, Hassan and Mohammadi Sheshkal, Faezeh and Aram, Farshid and Pinter, Gergo and Felde, Imre and Mosavi, Amir},
  title     = {The Role of Urban Morphology Design on Enhancing Physical Activity and Public Health},
  series = {International Journal of Environmental Research and Public Health},
  volume    = {2020},
  journal   = {International Journal of Environmental Research and Public Health},
  number    = {Volume 17, Issue 7, 2359},
  publisher = {MDPI},
  address   = {Basel},
  doi       = {10.3390/ijerph17072359},
  url       = {http://nbn-resolving.de/urn:nbn:de:gbv:wim2-20200402-41225},
  pages     = {29},
  abstract  = {Along with environmental pollution, urban planning has been connected to public health. The research indicates that the quality of built environments plays an important role in reducing mental disorders and overall health. The structure and shape of the city are considered as one of the factors influencing happiness and health in urban communities and the type of the daily activities of citizens. The aim of this study was to promote physical activity in the main structure of the city via urban design in a way that the main form and morphology of the city can encourage citizens to move around and have physical activity within the city. Functional, physical, cultural-social, and perceptual-visual features are regarded as the most important and effective criteria in increasing physical activities in urban spaces, based on literature review. The environmental quality of urban spaces and their role in the physical activities of citizens in urban spaces were assessed by using the questionnaire tool and analytical network process (ANP) of structural equation modeling. Further, the space syntax method was utilized to evaluate the role of the spatial integration of urban spaces on improving physical activities. Based on the results, consideration of functional diversity, spatial flexibility and integration, security, and the aesthetic and visual quality of urban spaces plays an important role in improving the physical health of citizens in urban spaces. Further, more physical activities, including motivation for walking and the sense of public health and happiness, were observed in the streets having higher linkage and space syntax indexes with their surrounding texture.},
  subject      = {Morphologie},
  language  = {en}
}