TY - JOUR A1 - Dehghani, Majid A1 - Salehi, Somayeh A1 - Mosavi, Amir A1 - Nabipour, Narjes A1 - Shamshirband, Shahaboddin A1 - Ghamisi, Pedram T1 - Spatial Analysis of Seasonal Precipitation over Iran: Co-Variation with Climate Indices JF - ISPRS, International Journal of Geo-Information N2 - Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing the variation in precipitation can effectively help the water resources decision-makers in water resources management. Large-scale circulation drivers have a considerable impact on precipitation in different parts of the world. In this research, the impact of El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran was investigated. For this purpose, 103 synoptic stations with at least 30 years of data were utilized. The Spearman correlation coefficient between the indices in the previous 12 months with seasonal precipitation was calculated, and the meaningful correlations were extracted. Then, the month in which each of these indices has the highest correlation with seasonal precipitation was determined. Finally, the overall amount of increase or decrease in seasonal precipitation due to each of these indices was calculated. Results indicate the Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal precipitation, respectively. Additionally, these indices have the highest impact on the precipitation in winter, autumn, spring, and summer, respectively. SOI has a diverse impact on winter precipitation compared to the PDO and NAO, while in the other seasons, each index has its special impact on seasonal precipitation. Generally, all indices in different phases may decrease the seasonal precipitation up to 100%. However, the seasonal precipitation may increase more than 100% in different seasons due to the impact of these indices. The results of this study can be used effectively in water resources management and especially in dam operation. KW - Maschinelles Lernen KW - Machine learning KW - spatiotemporal database KW - spatial analysis KW - seasonal precipitation KW - spearman correlation coefficient Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200128-40740 UR - https://www.mdpi.com/2220-9964/9/2/73 VL - 2020 IS - Volume 9, Issue 2, 73 PB - MDPI ER - TY - THES A1 - Abu Bakar, Ilyani Akmar T1 - Computational Analysis of Woven Fabric Composites: Single- and Multi-Objective Optimizations and Sensitivity Analysis in Meso-scale Structures N2 - This study permits a reliability analysis to solve the mechanical behaviour issues existing in the current structural design of fabric structures. Purely predictive material models are highly desirable to facilitate an optimized design scheme and to significantly reduce time and cost at the design stage, such as experimental characterization. The present study examined the role of three major tasks; a) single-objective optimization, b) sensitivity analyses and c) multi-objective optimization on proposed weave structures for woven fabric composites. For single-objective optimization task, the first goal is to optimize the elastic properties of proposed complex weave structure under unit cells basis based on periodic boundary conditions. We predict the geometric characteristics towards skewness of woven fabric composites via Evolutionary Algorithm (EA) and a parametric study. We also demonstrate the effect of complex weave structures on the fray tendency in woven fabric composites via tightness evaluation. We utilize a procedure which does not require a numerical averaging process for evaluating the elastic properties of woven fabric composites. The fray tendency and skewness of woven fabrics depends upon the behaviour of the floats which is related to the factor of weave. Results of this study may suggest a broader view for further research into the effects of complex weave structures or may provide an alternative to the fray and skewness problems of current weave structure in woven fabric composites. A comprehensive study is developed on the complex weave structure model which adopts the dry woven fabric of the most potential pattern in singleobjective optimization incorporating the uncertainties parameters of woven fabric composites. The comprehensive study covers the regression-based and variance-based sensitivity analyses. The second task goal is to introduce the fabric uncertainties parameters and elaborate how they can be incorporated into finite element models on macroscopic material parameters such as elastic modulus and shear modulus of dry woven fabric subjected to uni-axial and biaxial deformations. Significant correlations in the study, would indicate the need for a thorough investigation of woven fabric composites under uncertainties parameters. The study describes here could serve as an alternative to identify effective material properties without prolonged time consumption and expensive experimental tests. The last part focuses on a hierarchical stochastic multi-scale optimization approach (fine-scale and coarse-scale optimizations) under geometrical uncertainties parameters for hybrid composites considering complex weave structure. The fine-scale optimization is to determine the best lamina pattern that maximizes its macroscopic elastic properties, conducted by EA under the following uncertain mesoscopic parameters: yarn spacing, yarn height, yarn width and misalignment of yarn angle. The coarse-scale optimization has been carried out to optimize the stacking sequences of symmetric hybrid laminated composite plate with uncertain mesoscopic parameters by employing the Ant Colony Algorithm (ACO). The objective functions of the coarse-scale optimization are to minimize the cost (C) and weight (W) of the hybrid laminated composite plate considering the fundamental frequency and the buckling load factor as the design constraints. Based on the uncertainty criteria of the design parameters, the appropriate variation required for the structural design standards can be evaluated using the reliability tool, and then an optimized design decision in consideration of cost can be subsequently determined. T3 - ISM-Bericht // Institut für Strukturmechanik, Bauhaus-Universität Weimar - 2020,1 KW - Verbundwerkstoff KW - Gewebeverbundwerkstoff KW - woven composites Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200605-41762 SN - 1610-7381 ER - TY - JOUR A1 - Sadeghzadeh, Milad A1 - Maddah, Heydar A1 - Ahmadi, Mohammad Hossein A1 - Khadang, Amirhosein A1 - Ghazvini, Mahyar A1 - Mosavi, Amir Hosein A1 - Nabipour, Narjes T1 - Prediction of Thermo-Physical Properties of TiO2-Al2O3/Water Nanoparticles by Using Artificial Neural Network JF - Nanomaterials N2 - 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 KW - Wärmeleitfähigkeit KW - Fluid KW - Neuronales Netz KW - Thermal conductivity KW - Nanofluid KW - Artificial neural network Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200421-41308 UR - https://www.mdpi.com/2079-4991/10/4/697 VL - 2020 IS - Volume 10, Issue 4, 697 PB - MDPI CY - Basel ER - TY - JOUR A1 - Karimimoshaver, Mehrdad A1 - Hajivaliei, Hatameh A1 - Shokri, Manouchehr A1 - Khalesro, Shakila A1 - Aram, Farshid A1 - Shamshirband, Shahaboddin T1 - A Model for Locating Tall Buildings through a Visual Analysis Approach JF - Applied Sciences N2 - Tall buildings have become an integral part of cities despite all their pros and cons. Some current tall buildings have several problems because of their unsuitable location; the problems include increasing density, imposing traffic on urban thoroughfares, blocking view corridors, etc. Some of these buildings have destroyed desirable views of the city. In this research, different criteria have been chosen, such as environment, access, social-economic, land-use, and physical context. These criteria and sub-criteria are prioritized and weighted by the analytic network process (ANP) based on experts’ opinions, using Super Decisions V2.8 software. On the other hand, layers corresponding to sub-criteria were made in ArcGIS 10.3 simultaneously, then via a weighted overlay (map algebra), a locating plan was created. In the next step seven hypothetical tall buildings (20 stories), in the best part of the locating plan, were considered to evaluate how much of theses hypothetical buildings would be visible (fuzzy visibility) from the street and open spaces throughout the city. These processes have been modeled by MATLAB software, and the final fuzzy visibility plan was created by ArcGIS. Fuzzy visibility results can help city managers and planners to choose which location is suitable for a tall building and how much visibility may be appropriate. The proposed model can locate tall buildings based on technical and visual criteria in the future development of the city and it can be widely used in any city as long as the criteria and weights are localized. KW - Gebäude KW - Energieeffizienz KW - Sustainability KW - Infrastructures KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210122-43350 UR - https://www.mdpi.com/2076-3417/10/17/6072 VL - 2020 IS - Volume 10, issue 17, article 6072 SP - 1 EP - 25 PB - MDPI CY - Basel ER - TY - JOUR A1 - Shabani, Sevda A1 - Samadianfard, Saeed A1 - Sattari, Mohammad Taghi A1 - Mosavi, Amir A1 - Shamshirband, Shahaboddin A1 - Kmet, Tibor A1 - Várkonyi-Kóczy, Annamária R. T1 - Modeling Pan Evaporation Using Gaussian Process Regression K-Nearest Neighbors Random Forest and Support Vector Machines; Comparative Analysis JF - Atmosphere N2 - Evaporation is a very important process; it is one of the most critical factors in agricultural, hydrological, and meteorological studies. Due to the interactions of multiple climatic factors, evaporation is considered as a complex and nonlinear phenomenon to model. Thus, machine learning methods have gained popularity in this realm. In the present study, four machine learning methods of Gaussian Process Regression (GPR), K-Nearest Neighbors (KNN), Random Forest (RF) and Support Vector Regression (SVR) were used to predict the pan evaporation (PE). Meteorological data including PE, temperature (T), relative humidity (RH), wind speed (W), and sunny hours (S) collected from 2011 through 2017. The accuracy of the studied methods was determined using the statistical indices of Root Mean Squared Error (RMSE), correlation coefficient (R) and Mean Absolute Error (MAE). Furthermore, the Taylor charts utilized for evaluating the accuracy of the mentioned models. The results of this study showed that at Gonbad-e Kavus, Gorgan and Bandar Torkman stations, GPR with RMSE of 1.521 mm/day, 1.244 mm/day, and 1.254 mm/day, KNN with RMSE of 1.991 mm/day, 1.775 mm/day, and 1.577 mm/day, RF with RMSE of 1.614 mm/day, 1.337 mm/day, and 1.316 mm/day, and SVR with RMSE of 1.55 mm/day, 1.262 mm/day, and 1.275 mm/day had more appropriate performances in estimating PE values. It was found that GPR for Gonbad-e Kavus Station with input parameters of T, W and S and GPR for Gorgan and Bandar Torkmen stations with input parameters of T, RH, W and S had the most accurate predictions and were proposed for precise estimation of PE. The findings of the current study indicated that the PE values may be accurately estimated with few easily measured meteorological parameters. KW - Maschinelles Lernen KW - Machine learning KW - Deep learning Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200110-40561 UR - https://www.mdpi.com/2073-4433/11/1/66 VL - 2020 IS - Volume 11, Issue 1, 66 ER - TY - JOUR A1 - Harirchian, Ehsan A1 - Lahmer, Tom A1 - Buddhiraju, Sreekanth A1 - Mohammad, Kifaytullah A1 - Mosavi, Amir T1 - Earthquake Safety Assessment of Buildings through Rapid Visual Screening JF - Buildings N2 - Earthquake is among the most devastating natural disasters causing severe economical, environmental, and social destruction. Earthquake safety assessment and building hazard monitoring can highly contribute to urban sustainability through identification and insight into optimum materials and structures. While the vulnerability of structures mainly depends on the structural resistance, the safety assessment of buildings can be highly challenging. In this paper, we consider the Rapid Visual Screening (RVS) method, which is a qualitative procedure for estimating structural scores for buildings suitable for medium- to high-seismic cases. This paper presents an overview of the common RVS methods, i.e., FEMA P-154, IITK-GGSDMA, and EMPI. To examine the accuracy and validation, a practical comparison is performed between their assessment and observed damage of reinforced concrete buildings from a street survey in the Bingöl region, Turkey, after the 1 May 2003 earthquake. The results demonstrate that the application of RVS methods for preliminary damage estimation is a vital tool. Furthermore, the comparative analysis showed that FEMA P-154 creates an assessment that overestimates damage states and is not economically viable, while EMPI and IITK-GGSDMA provide more accurate and practical estimation, respectively. KW - Maschinelles Lernen KW - Machine learning KW - Erdbeben KW - buildings KW - earthquake safety assessment KW - earthquake KW - extreme events KW - seismic assessment KW - natural hazard KW - mitigation KW - rapid visual screening Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200331-41153 UR - https://www.mdpi.com/2075-5309/10/3/51 VL - 2020 IS - Volume 10, Issue 3 PB - MDPI ER - TY - JOUR A1 - Saqlai, Syed Muhammad A1 - Ghani, Anwar A1 - Khan, Imran A1 - Ahmed Khan Ghayyur, Shahbaz A1 - Shamshirband, Shahaboddin A1 - Nabipour, Narjes A1 - Shokri, Manouchehr T1 - Image Analysis Using Human Body Geometry and Size Proportion Science for Action Classification JF - Applied Sciences N2 - Gestures are one of the basic modes of human communication and are usually used to represent different actions. Automatic recognition of these actions forms the basis for solving more complex problems like human behavior analysis, video surveillance, event detection, and sign language recognition, etc. Action recognition from images is a challenging task as the key information like temporal data, object trajectory, and optical flow are not available in still images. While measuring the size of different regions of the human body i.e., step size, arms span, length of the arm, forearm, and hand, etc., provides valuable clues for identification of the human actions. In this article, a framework for classification of the human actions is presented where humans are detected and localized through faster region-convolutional neural networks followed by morphological image processing techniques. Furthermore, geometric features from human blob are extracted and incorporated into the classification rules for the six human actions i.e., standing, walking, single-hand side wave, single-hand top wave, both hands side wave, and both hands top wave. The performance of the proposed technique has been evaluated using precision, recall, omission error, and commission error. The proposed technique has been comparatively analyzed in terms of overall accuracy with existing approaches showing that it performs well in contrast to its counterparts. KW - Bildanalyse KW - Mensch KW - Größenverhältnis KW - Geometrie KW - Körper KW - action recognition KW - rule based classification KW - human body proportions KW - human blob KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200904-42322 UR - https://www.mdpi.com/2076-3417/10/16/5453 VL - 2020 IS - volume 10, issue 16, article 5453 PB - MDPI CY - Basel ER - TY - JOUR A1 - Batra, Ritika T1 - Gauging the stakeholders’ perspective: towards PPP in building sectors and housing JF - Journal of Housing and the Built Environment N2 - While Public-Private Partnership (PPP) is widely adopted across various sectors, it raises a question on its meagre utilisation in the housing sector. This paper, therefore, gauges the perspective of the stakeholders in the building industry towards the application of PPP in various building sectors together with housing. It assesses the performance reliability of PPP for housing by learning possible take-aways from other sectors. The role of key stakeholders in the industry becomes highly responsible for an informed understanding and decision-making. To this end, a two-tier investigation was conducted including surveys and expert interviews, with several stakeholders in the PPP industry in Europe, involving the public sector, private sector, consultants, as well as other community/user representatives. The survey results demonstrated the success rate with PPPs, major factors important for PPPs such as profitability or end-user acceptability, the prevalent practices and trends in the PPP world, and the majority of support expressed in favour of the suitability of PPP for housing. The interviews added more detailed dimensions to the understanding of the PPP industry, its functioning and enabling the formation of a comprehensive outlook. The results present the perspective, approaches, and experiences of stakeholders over PPP practices, current trends and scenarios and their take on PPP in housing. It shall aid in understanding the challenges prevalent in the PPP approach for implementation in housing and enable the policymakers and industry stakeholders to make provisions for higher uptake to accelerate housing provision. KW - Öffentlich-private Partnerschaft KW - Städtischer Wohnungsmarkt KW - Public-Private Partnerships KW - Housing Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210413-44124 UR - https://link.springer.com/article/10.1007/s10901-020-09754-4 VL - 2020 IS - volume 35 SP - 1123 EP - 1156 PB - SpringerNature CY - Cham ER - TY - JOUR A1 - Homaei, Mohammad Hossein A1 - Soleimani, Faezeh A1 - Shamshirband, Shahaboddin A1 - Mosavi, Amir A1 - Nabipour, Narjes A1 - Varkonyi-Koczy, Annamaria R. T1 - An Enhanced Distributed Congestion Control Method for Classical 6LowPAN Protocols Using Fuzzy Decision System JF - IEEE Access N2 - The classical Internet of things routing and wireless sensor networks can provide more precise monitoring of the covered area due to the higher number of utilized nodes. Because of the limitations in shared transfer media, many nodes in the network are prone to the collision in simultaneous transmissions. Medium access control protocols are usually more practical in networks with low traffic, which are not subjected to external noise from adjacent frequencies. There are preventive, detection and control solutions to congestion management in the network which are all the focus of this study. In the congestion prevention phase, the proposed method chooses the next step of the path using the Fuzzy decision-making system to distribute network traffic via optimal paths. In the congestion detection phase, a dynamic approach to queue management was designed to detect congestion in the least amount of time and prevent the collision. In the congestion control phase, the back-pressure method was used based on the quality of the queue to decrease the probability of linking in the pathway from the pre-congested node. The main goals of this study are to balance energy consumption in network nodes, reducing the rate of lost packets and increasing quality of service in routing. Simulation results proved the proposed Congestion Control Fuzzy Decision Making (CCFDM) method was more capable in improving routing parameters as compared to recent algorithms. KW - Internet der dinge KW - IOT KW - Internet of things KW - wireless sensor network KW - congestion control KW - fuzzy decision making KW - back-pressure Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200213-40805 UR - https://ieeexplore.ieee.org/document/8967114 IS - volume 8 SP - 20628 EP - 20645 PB - IEEE ER - TY - THES A1 - Hossein Nezhad Shirazi, Ali T1 - Multi-Scale Modeling of Lithium ion Batteries: a thermal management approach and molecular dynamic studies N2 - Rechargeable lithium ion batteries (LIBs) play a very significant role in power supply and storage. In recent decades, LIBs have caught tremendous attention in mobile communication, portable electronics, and electric vehicles. Furthermore, global warming has become a worldwide issue due to the ongoing production of greenhouse gases. It motivates solutions such as renewable sources of energy. Solar and wind energies are the most important ones in renewable energy sources. By technology progress, they will definitely require batteries to store the produced power to make a balance between power generation and consumption. Nowadays,rechargeable batteries such as LIBs are considered as one of the best solutions. They provide high specific energy and high rate performance while their rate of self-discharge is low. Performance of LIBs can be improved through the modification of battery characteristics. The size of solid particles in electrodes can impact the specific energy and the cyclability of batteries. It can improve the amount of lithium content in the electrode which is a vital parameter in capacity and capability of a battery. There exist diferent sources of heat generation in LIBs such as heat produced during electrochemical reactions, internal resistance in battery. The size of electrode's electroactive particles can directly affect the produced heat in battery. It will be shown that the smaller size of solid particle enhance the thermal characteristics of LIBs. Thermal issues such as overheating, temperature maldistribution in the battery, and thermal runaway have confined applications of LIBs. Such thermal challenges reduce the Life cycle of LIBs. As well, they may lead to dangerous conditions such as fire or even explosion in batteries. However, recent advances in fabrication of advanced materials such as graphene and carbon nanotubes with extraordinary thermal conductivity and electrical properties propose new opportunities to enhance their performance. Since experimental works are expensive, our objective is to use computational methods to investigate the thermal issues in LIBS. Dissipation of the heat produced in the battery can improve the cyclability and specific capacity of LIBs. In real applications, packs of LIB consist several battery cells that are used as the power source. Therefore, it is worth to investigate thermal characteristic of battery packs under their cycles of charging/discharging operations at different applied current rates. To remove the produced heat in batteries, they can be surrounded by materials with high thermal conductivity. Parafin wax absorbs high energy since it has a high latent heat. Absorption high amounts of energy occurs at constant temperature without phase change. As well, thermal conductivity of parafin can be magnified with nano-materials such as graphene, CNT, and fullerene to form a nano-composite medium. Improving the thermal conductivity of LIBs increase the heat dissipation from batteries which is a vital issue in systems of battery thermal management. The application of two-dimensional (2D) materials has been on the rise since exfoliation the graphene from bulk graphite. 2D materials are single-layered in an order of nanosizes which show superior thermal, mechanical, and optoelectronic properties. They are potential candidates for energy storage and supply, particularly in lithium ion batteries as electrode material. The high thermal conductivity of graphene and graphene-like materials can play a significant role in thermal management of batteries. However, defects always exist in nano-materials since there is no ideal fabrication process. One of the most important defects in materials are nano-crack which can dramatically weaken the mechanical properties of the materials. Newly synthesized crystalline carbon nitride with the stoichiometry of C3N have attracted many attentions due to its extraordinary mechanical and thermal properties. The other nano-material is phagraphene which shows anisotropic mechanical characteristics which is ideal in production of nanocomposite. It shows ductile fracture behavior when subjected under uniaxial loadings. It is worth to investigate their thermo-mechanical properties in its pristine and defective states. We hope that the findings of our work not only be useful for both experimental and theoretical researches but also help to design advanced electrodes for LIBs. KW - Akkumulator KW - Battery KW - Batterie Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200214-40986 ER - TY - JOUR A1 - Artus, Mathias A1 - Koch, Christian T1 - State of the art in damage information modeling for RC bridges – A literature review JF - Advanced Engineering Informatics N2 - In Germany, bridges have an average age of 40 years. A bridge consumes between 0.4% and 2% of its construction cost per year over its entire life cycle. This means that up to 80% of the construction cost are additionally needed for operation, inspection, maintenance, and destruction. Current practices rely either on paperbased inspections or on abstract specialist software. Every application in the inspection and maintenance sector uses its own data model for structures, inspections, defects, and maintenance. Due to this, data and properties have to be transferred manually, otherwise a converter is necessary for every data exchange between two applications. To overcome this issue, an adequate model standard for inspections, damage, and maintenance is necessary. Modern 3D models may serve as a single source of truth, which has been suggested in the Building Information Modeling (BIM) concept. Further, these models offer a clear visualization of the built infrastructure, and improve not only the planning and construction phases, but also the operation phase of construction projects. BIM is established mostly in the Architecture, Engineering, and Construction (AEC) sector to plan and construct new buildings. Currently, BIM does not cover the whole life cycle of a building, especially not inspection and maintenance. Creating damage models needs the building model first, because a defect is dependent on the building component, its properties and material. Hence, a building information model is necessary to obtain meaningful conclusions from damage information. This paper analyzes the requirements, which arise from practice, and the research that has been done in modeling damage and related information for bridges. With a look at damage categories and use cases related to inspection and maintenance, scientific literature is discussed and synthesized. Finally, research gaps and needs are identified and discussed. KW - Building Information Modeling KW - Brücke KW - Inspektion KW - Literaturrecherche KW - Datenmodell Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20220506-46390 UR - https://www.sciencedirect.com/science/article/abs/pii/S1474034620301427?via%3Dihub VL - 2020 IS - volume 46, article 101171 SP - 1 EP - 16 PB - Elsevier Science CY - Amsterdam ER - TY - JOUR A1 - Meng, Yinghui A1 - Noman Qasem, Sultan A1 - Shokri, Manouchehr A1 - Shamshirband, Shahaboddin T1 - Dimension Reduction of Machine Learning-Based Forecasting Models Employing Principal Component Analysis JF - Mathematics N2 - In this research, an attempt was made to reduce the dimension of wavelet-ANFIS/ANN (artificial neural network/adaptive neuro-fuzzy inference system) models toward reliable forecasts as well as to decrease computational cost. In this regard, the principal component analysis was performed on the input time series decomposed by a discrete wavelet transform to feed the ANN/ANFIS models. The models were applied for dissolved oxygen (DO) forecasting in rivers which is an important variable affecting aquatic life and water quality. The current values of DO, water surface temperature, salinity, and turbidity have been considered as the input variable to forecast DO in a three-time step further. The results of the study revealed that PCA can be employed as a powerful tool for dimension reduction of input variables and also to detect inter-correlation of input variables. Results of the PCA-wavelet-ANN models are compared with those obtained from wavelet-ANN models while the earlier one has the advantage of less computational time than the later models. Dealing with ANFIS models, PCA is more beneficial to avoid wavelet-ANFIS models creating too many rules which deteriorate the efficiency of the ANFIS models. Moreover, manipulating the wavelet-ANFIS models utilizing PCA leads to a significant decreasing in computational time. Finally, it was found that the PCA-wavelet-ANN/ANFIS models can provide reliable forecasts of dissolved oxygen as an important water quality indicator in rivers. KW - Maschinelles Lernen KW - machine learning KW - dimensionality reduction KW - wavelet transform KW - water quality KW - principal component analysis KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200811-42125 UR - https://www.mdpi.com/2227-7390/8/8/1233 VL - 2020 IS - volume 8, issue 8, article 1233 PB - MDPI CY - Basel ER - TY - THES A1 - Freire, Kamai T1 - Panafricanism and African Revolution in Brazilian Music N2 - This research departs from the teachings of Kwame Ture on the difference between mobilization and organization in the panafricanist struggle to analyze then the use of Music within the anti-racist and anti-colonialist struggle in Brazil. KW - Saz KW - Pan-Africanism KW - Musik KW - Antikolonialismus KW - Antirassismus KW - African Revolution KW - Music KW - Brazilian Music KW - Musicology KW - Post-colonial studies KW - anti-racist KW - anti-colonialist Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210216-43536 ER - TY - JOUR A1 - Mousavi, Seyed Nasrollah A1 - Steinke Júnior, Renato A1 - Teixeira, Eder Daniel A1 - Bocchiola, Daniele A1 - Nabipour, Narjes A1 - Mosavi, Amir A1 - Shamshirband, Shahaboddin T1 - Predictive Modeling the Free Hydraulic Jumps Pressure through Advanced Statistical Methods JF - Mathematics N2 - 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. KW - Maschinelles Lernen KW - Machine learning KW - mathematical modeling KW - extreme pressure KW - hydraulic jump KW - stilling basin KW - standard deviation of pressure fluctuations KW - statistical coeffcient of the probability distribution Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200402-41140 UR - https://www.mdpi.com/2227-7390/8/3/323 VL - 2020 IS - Volume 8, Issue 3, 323 PB - MDPI CY - Basel ER - TY - JOUR A1 - Harirchian, Ehsan A1 - Lahmer, Tom A1 - Kumari, Vandana A1 - Jadhav, Kirti T1 - Application of Support Vector Machine Modeling for the Rapid Seismic Hazard Safety Evaluation of Existing Buildings JF - Energies N2 - The economic losses from earthquakes tend to hit the national economy considerably; therefore, models that are capable of estimating the vulnerability and losses of future earthquakes are highly consequential for emergency planners with the purpose of risk mitigation. This demands a mass prioritization filtering of structures to identify vulnerable buildings for retrofitting purposes. The application of advanced structural analysis on each building to study the earthquake response is impractical due to complex calculations, long computational time, and exorbitant cost. This exhibits the need for a fast, reliable, and rapid method, commonly known as Rapid Visual Screening (RVS). The method serves as a preliminary screening platform, using an optimum number of seismic parameters of the structure and predefined output damage states. In this study, the efficacy of the Machine Learning (ML) application in damage prediction through a Support Vector Machine (SVM) model as the damage classification technique has been investigated. The developed model was trained and examined based on damage data from the 1999 Düzce Earthquake in Turkey, where the building’s data consists of 22 performance modifiers that have been implemented with supervised machine learning. KW - Erdbeben KW - Maschinelles Lernen KW - earthquake vulnerability assessment KW - rapid visual screening KW - machine learning KW - support vector machine KW - buildings KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200707-41915 UR - https://www.mdpi.com/1996-1073/13/13/3340 VL - 2020 IS - volume 13, issue 13, 3340 PB - MDPI CY - Basel ER - TY - JOUR A1 - Schirmer, Ulrike A1 - Osburg, Andrea T1 - A new method for the quantification of adsorbed styrene acrylate copolymer particles on cementitious surfaces: a critical comparative study JF - SN Applied Sciences N2 - The amount of adsorbed styrene acrylate copolymer (SA) particles on cementitious surfaces at the early stage of hydration was quantitatively determined using three different methodological approaches: the depletion method, the visible spectrophotometry (VIS) and the thermo-gravimetry coupled with mass spectrometry (TG–MS). Considering the advantages and disadvantages of each method, including the respectively required sample preparation, the results for four polymer-modified cement pastes, varying in polymer content and cement fineness, were evaluated. To some extent, significant discrepancies in the adsorption degrees were observed. There is a tendency that significantly lower amounts of adsorbed polymers were identified using TG-MS compared to values determined with the depletion method. Spectrophotometrically generated values were ​​lying in between these extremes. This tendency was found for three of the four cement pastes examined and is originated in sample preparation and methodical limitations. The main influencing factor is the falsification of the polymer concentration in the liquid phase during centrifugation. Interactions in the interface between sediment and supernatant are the cause. The newly developed method, using TG–MS for the quantification of SA particles, proved to be suitable for dealing with these revealed issues. Here, instead of the fluid phase, the sediment is examined with regard to the polymer content, on which the influence of centrifugation is considerably lower. KW - Zement KW - Polymere KW - polymer adsorption KW - cement KW - visible spectrophotometry KW - depletion method KW - mass spectrometry Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210804-44729 UR - https://link.springer.com/article/10.1007/s42452-020-03825-5 VL - 2020 IS - Volume 2, article 2061 SP - 1 EP - 11 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Harirchian, Ehsan A1 - Jadhav, Kirti A1 - Mohammad, Kifaytullah A1 - Aghakouchaki Hosseini, Seyed Ehsan A1 - Lahmer, Tom T1 - A Comparative Study of MCDM Methods Integrated with Rapid Visual Seismic Vulnerability Assessment of Existing RC Structures JF - Applied Sciences N2 - Recently, the demand for residence and usage of urban infrastructure has been increased, thereby resulting in the elevation of risk levels of human lives over natural calamities. The occupancy demand has rapidly increased the construction rate, whereas the inadequate design of structures prone to more vulnerability. Buildings constructed before the development of seismic codes have an additional susceptibility to earthquake vibrations. The structural collapse causes an economic loss as well as setbacks for human lives. An application of different theoretical methods to analyze the structural behavior is expensive and time-consuming. Therefore, introducing a rapid vulnerability assessment method to check structural performances is necessary for future developments. The process, as mentioned earlier, is known as Rapid Visual Screening (RVS). This technique has been generated to identify, inventory, and screen structures that are potentially hazardous. Sometimes, poor construction quality does not provide some of the required parameters; in this case, the RVS process turns into a tedious scenario. Hence, to tackle such a situation, multiple-criteria decision-making (MCDM) methods for the seismic vulnerability assessment opens a new gateway. The different parameters required by RVS can be taken in MCDM. MCDM evaluates multiple conflicting criteria in decision making in several fields. This paper has aimed to bridge the gap between RVS and MCDM. Furthermore, to define the correlation between these techniques, implementation of the methodologies from Indian, Turkish, and Federal Emergency Management Agency (FEMA) codes has been done. The effects of seismic vulnerability of structures have been observed and compared. KW - Erdbebensicherheit KW - damaged buildings KW - earthquake safety assessment KW - soft computing techniques KW - rapid visual screening KW - seismic risk estimation KW - Multi-criteria decision making KW - vulnerability assessment KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200918-42360 UR - https://www.mdpi.com/2076-3417/10/18/6411/htm VL - 2020 IS - Volume 10, issue 18, article 6411 PB - MDPI CY - Basel ER - TY - JOUR A1 - Harirchian, Ehsan A1 - Lahmer, Tom T1 - Improved Rapid Visual Earthquake Hazard Safety Evaluation of Existing Buildings Using a Type-2 Fuzzy Logic Model JF - Applied Sciences N2 - Rapid Visual Screening (RVS) is a procedure that estimates structural scores for buildings and prioritizes their retrofit and upgrade requirements. Despite the speed and simplicity of RVS, many of the collected parameters are non-commensurable and include subjectivity due to visual observations. This might cause uncertainties in the evaluation, which emphasizes the use of a fuzzy-based method. This study aims to propose a novel RVS methodology based on the interval type-2 fuzzy logic system (IT2FLS) to set the priority of vulnerable building to undergo detailed assessment while covering uncertainties and minimizing their effects during evaluation. The proposed method estimates the vulnerability of a building, in terms of Damage Index, considering the number of stories, age of building, plan irregularity, vertical irregularity, building quality, and peak ground velocity, as inputs with a single output variable. Applicability of the proposed method has been investigated using a post-earthquake damage database of reinforced concrete buildings from the Bingöl and Düzce earthquakes in Turkey. KW - Fuzzy-Logik KW - Erdbeben KW - Fuzzy Logic KW - Rapid Visual Screening KW - Vulnerability assessment KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200331-41161 UR - https://www.mdpi.com/2076-3417/10/7/2375 VL - 2020 IS - Volume 10, Issue 3, 2375 PB - MDPI CY - Basel ER - TY - THES A1 - Reformat, Martin T1 - Zementmahlung - Untersuchungen zum Zusammenhang von Mahlaggregat und Materialeigenschaften N2 - Die Mahlung als Zerkleinerungsprozess stellt seit den Anfängen der Menschheit eine der wichtigsten Verarbeitungsformen von Materialien aller Art dar - von der Getreidemahlung, über das Aufschließen von Heilkräutern in Mörsern bis hin zur Herstellung von Tonern für Drucker und Kopierer. Besonders die Zementmahlung ist in modernen Gesellschaften sowohl ein wirtschaftlicher als auch ein ökologischer Faktor. Mehr als zwei Drittel der elektrischen Energie der Zementproduktion werden für Rohmehl- und Klinker- bzw. Kompositmaterialmahlung verbraucht. Dies ist nur ein Grund, warum der Mahlprozess zunehmend in den Fokus vieler Forschungs- und Entwicklungsvorhaben rückt. Die Komplexität der Zementmahlung steigt im zunehmenden Maße an. Die simple „Mahlung auf Zementfeinheit“ ist seit langem obsolet. Zemente werden maßgeschneidert, mit verschiedensten Kombinationsprodukten, getrennt oder gemeinsam, in unterschiedlichen Mahlaggregaten oder mit ganz neuen Ansätzen gefertigt. Darüber hinaus gewinnt auch der Sektor des Baustoffrecyclings, mit allen damit verbundenen Herausforderungen, immer mehr an Bedeutung. Bei der Fragestellung, wie der Mahlprozess einerseits leistungsfähige Produkte erzeugen kann und andererseits die zunehmenden Anforderungen an Nachhaltigkeit erfüllt, steht das Mahlaggregat im Mittelpunkt der Betrachtungen. Dementsprechend gliedert sich, neben einer eingehenden Literaturrecherche zum Wissensstand, die vorliegende Arbeit in zwei übergeordnete Teile: Im ersten Teil werden Untersuchungen an konventionellen Mahlaggregaten mit in der Zementindustrie verwendeten Kernprodukten wie Portlandzementklinker, Kalkstein, Flugasche und Hüttensand angestellt. Um eine möglichst effektive Mahlung von Zement und Kompositmaterialien zu gewährleisten, ist es wichtig, die Auswirkung von Mühlenparametern zu kennen. Hierfür wurde eine umfangreiche Versuchsmatrix aufgestellt und abgearbeitet. Das Spektrum der Analysemethoden war ebenfalls umfangreich und wurde sowohl auf die gemahlenen Materialien als auch auf die daraus hergestellten Zemente und Betone angewendet. Es konnte gezeigt werden, dass vor allem die Unterscheidung zwischen Mahlkörpermühlen und mahlkörperlosen Mühlen entscheidenden Einfluss auf die Granulometrie und somit auch auf die Zementperformance hat. Besonders stark wurden die Verarbeitungseigenschaften, insbesondere der Wasseranspruch und damit auch das Porengefüge und schließlich Druckfestigkeiten sowie Dauerhaftigkeitseigenschaften der aus diesen Zementen hergestellten Betone, beeinflusst. Bei Untersuchungen zur gemeinsamen Mahlung von Kalkstein und Klinker führten ungünstige Anreicherungseffekte des gut mahlbaren Kalksteins sowie tonigen Nebenbestandteilen zu einer schlechteren Performance in allen Zementprüfungen. Der zweite Teil widmet sich der Hochenergiemahlung. Die dahinterstehende Technik wird seit Jahrzehnten in anderen Wirtschaftsbranchen, wie der Pharmazie, Biologie oder auch Lebensmittelindustrie angewendet und ist seit einiger Zeit auch in der Zementforschung anzutreffen. Beispielhaft seien hier die Planeten- und Rührwerkskugelmühle als Vertreter genannt. Neben grundlegenden Untersuchungen an Zementklinker und konventionellen Kompositmaterialien wie Hüttensand und Kalkstein wurde auch die Haupt-Zementklinkerphase Alit untersucht. Die Hochenergiemahlung von konventionellen Kompositmaterialien generierte zusätzliche Reaktivität bei gleicher Granulometrie gegenüber der herkömmlichen Mahlung. Dies wurde vor allem bei per se reaktivem Zementklinker als auch bei latent-hydraulischem Hüttensand beobachtet. Gemahlene Flugaschen konnten nur im geringen Maße weiter aktiviert werden. Der generelle Einfluss von Oberflächenvergrößerung, Strukturdefekten und Relaxationseffekten eines Mahlproduktes wurden eingehend untersucht und gewichtet. Die Ergebnisse bei der Hochenergiemahlung von Alit zeigten, dass die durch Mahlung eingebrachten Strukturdefekte eine Erhöhung der Reaktivität zur Folge haben. Hierbei konnte festgestellt werden, das maßgeblich Oberflächendefekte, strukturelle (Volumen-)defekte und als Konterpart Selbstheilungseffekte die reaktivitätsbestimmenden Faktoren sind. Weiterhin wurden Versuche zur Mahlung von Altbetonbrechsand durchgeführt. Im Speziellen wurde untersucht, inwieweit eine Rückführung von Altbetonbrechsand, als unverwertbarer Teil des Betonbruchs, in Form eines Zement-Kompositmaterials in den Baustoffkreislauf möglich ist. Die hierfür verwendete Mahltechnik umfasst sowohl konventionelle Mühlen als auch Hochenergiemühlen. Es wurden Kompositzemente mit variiertem Recyclingmaterialanteil hergestellt und auf grundlegende Eigenschaften untersucht. Zur Bewertung der Produktqualität wurde der sogenannte „Aktivierungskoeffizient“ eingeführt. Es stellte sich heraus, dass die Rückführung von Altbetonbrechsand als potentielles Kompositmaterial wesentlich vom Anteil des Zementsteins abhängt. So konnte beispielsweise reiner Zementstein als aufgemahlenes Kompositmaterial eine bessere Performance gegenüber dem mit Gesteinskörnung beaufschlagtem Altbetonbrechsand ausweisen. Bezogen auf die gemessenen Hydratationswärmen und Druckfestigkeiten nahm der Aktivierungskoeffzient mit fallendem Abstraktionsgrad ab. Ebenfalls sank der Aktivierungskoeffizient mit steigendem Substitutionsgrad. Als Vergleich wurden dieselben Materialien in konventionellen Mühlen aufbereitet. Die hier erzielten Ergebnisse können teilweise der Hochenergiemahlung als gleichwertig beurteilt werden. Folglich ist bei der Aktivierung von Recyclingmaterialien weniger die Mahltechnik als der Anteil an aktivierbarem Zementstein ausschlaggebend. N2 - Grinding as a comminution process has been one of the most important forms of processing of all kinds of materials since the beginning of mankind - from grain grinding over digesting medicinal herbs in mortars to producing toners for printers and copiers. Cement grinding in particular is both an economic and an ecological factor in modern societies. More than two-thirds of the electrical energy of cement production is consumed for raw meal and clinker or composite material grinding. This is just one reason why the milling process is increasingly becoming the focus of many research and development projects. And the complexity of cement grinding is increasing. The simple demand to grind to a certain cement fineness is obsolete. Cements are custom-made with a variety of combination products, comminuted separately or together in different grinding units or made with completely new approaches. In addition, the sector of building materials recycling - with all the associated challenges - also wins more and more importance. In terms of the question of how the grinding process could produce high-performance products on the one hand and the increasing demands on sustainability on the other hand, the grinding devices are the focus of the considerations. Accordingly, in addition to an in-depth literature review on the state of knowledge, the present work is divided into two major parts: In the first part investigations are made on conventional grinding devices with core products used in the cement industry, such as Portland cement clinker, limestone, fly ash and granulated blast furnace slag. To ensure the most effective grinding of cement and composite materials, it is important to know the effect of grinding parameters. For this, an extensive experimental matrix was set up and processed. The spectrum of analysis methods was also extensive and was applied to both the milled materials and the cements and concretes made from them. It could be shown that especially the distinction between grinding media mills and non-grinding media mills has a decisive influence on the granulometry and thus also on the cement performance. The processing properties, especially the water demand and thus the pore structure and finally compressive strength and durability properties of the concretes made from these cements, have been strong influenced, particularly. In studies on the common grinding of limestone and clinker an unfavorable enrichment of easily grindable limestone and clayey secondary constituents led to a poorer performance in all cement tests. The second part is devoted to high-energy milling. The technology behind it has been used for decades in other sectors of the economy, such as pharmacy, biology and the food industry and has also been used in cement research for some time. As representatives, the planetary and stirred media ball mill may be mentioned here. In addition to basic investigations on cement clinker and conventional composite materials such as blast furnace slag and limestone, the main Portland cement clinker phase alite was also investigated. The high-energy milling of conventional composite materials generated additional reactivity with the same granulometry compared to conventional grinding. This was observed especially on per se reactive Portland cement clinker as well as on latent-hydraulic blast furnace slag. Ground fly ash could be activated only to a small extent. The general influence of surface enlargement, structural defects and relaxation effects of a ground product were thoroughly investigated and weighted as well. The high-energy milling results of alite showed that the structural defects introduced by milling result in an increased reactivity. It was found that mainly surface defects, structural (volume) defects and as counterpart self-healing effects are the factors determining reactivity. Furthermore, attempts were made to grind concrete waste sand (CDW). In particular, it was examined to what extent a return of CDW, as an unvaluable part of the concrete fracture, in the form of a cement composite material in the building material cycle is possible. The grinding technique used for this purpose includes both conventional mills and high-energy mills. Composite cements with a varied proportion of recycled material were produced and examined for their fundamental properties. For the evaluation of the product quality the so-called äctivation coefficient"was introduced. It was found that the return of used concrete crushed sand as a potential composite significantly depends on the content of the cement paste. For example, pure cement paste as a milled composite showed better performance than the aggregated contaminated CDW. Based on the measured heat of hydration and compressive strengths, the activation coefficient decreased with decreasing degree of abstraction and the activation coefficient also decreased with increasing degree of substitution. For comparison, the same materials were prepared in conventional mills. The results obtained here can be partly considered as equivalent to high-energy milling. Consequently, when activating recycled materials, the grinding technique is less important than the amount of activatable cement paste. KW - Zement KW - Beton KW - Mahlung KW - Zementmahlung KW - Mahlaggregat KW - Vertical roller mill Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20201102-42794 SN - 978-3-00-067121-0 ER - TY - JOUR A1 - Harirchian, Ehsan A1 - Kumari, Vandana A1 - Jadhav, Kirti A1 - Raj Das, Rohan A1 - Rasulzade, Shahla A1 - Lahmer, Tom T1 - A Machine Learning Framework for Assessing Seismic Hazard Safety of Reinforced Concrete Buildings JF - Applied Sciences N2 - Although averting a seismic disturbance and its physical, social, and economic disruption is practically impossible, using the advancements in computational science and numerical modeling shall equip humanity to predict its severity, understand the outcomes, and equip for post-disaster management. Many buildings exist amidst the developed metropolitan areas, which are senile and still in service. These buildings were also designed before establishing national seismic codes or without the introduction of construction regulations. In that case, risk reduction is significant for developing alternatives and designing suitable models to enhance the existing structure’s performance. Such models will be able to classify risks and casualties related to possible earthquakes through emergency preparation. Thus, it is crucial to recognize structures that are susceptible to earthquake vibrations and need to be prioritized for retrofitting. However, each building’s behavior under seismic actions cannot be studied through performing structural analysis, as it might be unrealistic because of the rigorous computations, long period, and substantial expenditure. Therefore, it calls for a simple, reliable, and accurate process known as Rapid Visual Screening (RVS), which serves as a primary screening platform, including an optimum number of seismic parameters and predetermined performance damage conditions for structures. In this study, the damage classification technique was studied, and the efficacy of the Machine Learning (ML) method in damage prediction via a Support Vector Machine (SVM) model was explored. The ML model is trained and tested separately on damage data from four different earthquakes, namely Ecuador, Haiti, Nepal, and South Korea. Each dataset consists of varying numbers of input data and eight performance modifiers. Based on the study and the results, the ML model using SVM classifies the given input data into the belonging classes and accomplishes the performance on hazard safety evaluation of buildings. KW - Erdbeben KW - Vulnerability KW - Earthquake KW - damaged buildings KW - earthquake safety assessment KW - soft computing techniques KW - rapid visual screening KW - Machine Learning KW - vulnerability assessment KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20201022-42744 UR - https://www.mdpi.com/2076-3417/10/20/7153 VL - 2020 IS - Volume 10, issue 20, article 7153 PB - MDPI CY - Basel ER - TY - JOUR A1 - Tutal, Adrian A1 - Partschefeld, Stephan A1 - Schneider, Jens A1 - Osburg, Andrea T1 - Effects of Bio-Based Plasticizers, Made From Starch, on the Properties of Fresh and Hardened Metakaolin-Geopolymer Mortar: Basic Investigations JF - Clays and Clay Minerals N2 - Conventional superplasticizers based on polycarboxylate ether (PCE) show an intolerance to clay minerals due to intercalation of their polyethylene glycol (PEG) side chains into the interlayers of the clay mineral. An intolerance to very basic media is also known. This makes PCE an unsuitable choice as a superplasticizer for geopolymers. Bio-based superplasticizers derived from starch showed comparable effects to PCE in a cementitious system. The aim of the present study was to determine if starch superplasticizers (SSPs) could be a suitable additive for geopolymers by carrying out basic investigations with respect to slump, hardening, compressive and flexural strength, shrinkage, and porosity. Four SSPs were synthesized, differing in charge polarity and specific charge density. Two conventional PCE superplasticizers, differing in terms of molecular structure, were also included in this study. The results revealed that SSPs improved the slump of a metakaolin-based geopolymer (MK-geopolymer) mortar while the PCE investigated showed no improvement. The impact of superplasticizers on early hardening (up to 72 h) was negligible. Less linear shrinkage over the course of 56 days was seen for all samples in comparison with the reference. Compressive strengths of SSP specimens tested after 7 and 28 days of curing were comparable to the reference, while PCE led to a decline. The SSPs had a small impact on porosity with a shift to the formation of more gel pores while PCE caused an increase in porosity. Throughout this research, SSPs were identified as promising superplasticizers for MK-geopolymer mortar and concrete. KW - Geopolymere KW - Metakaolin KW - Superplasticizer Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20210804-44737 UR - https://link.springer.com/article/10.1007%2Fs42860-020-00084-8 VL - 2020 IS - volume 68, No. 5 SP - 413 EP - 427 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Buschow, Christopher T1 - Practice-driven journalism research: Impulses for a dynamic understanding of journalism in the context of its reorganization JF - Studies in Communication Sciences N2 - This paper proposes a practice-theoretical journalism research approach for an alternate and innovative perspective of digital journalism’s current empirical challenges. The practice-theoretical approach is introduced by demonstrating its explanatory power in relation to demarcation problems, technological changes, economic challenges and challenges to journalism’s legitimacy. Its respective advantages in dealing with these problems are explained and then compared to established journalism theories. The particular relevance of the theoretical perspective is due to (1) its central decision to observe journalistic practices, (2) the transgression of conventional journalistic boundaries, (3) the denaturalization of journalistic norms and laws, (4) the explicit consideration of a material, socio-technical dimension of journalism, (5) a focus on the conflicting relationship between journalistic practices and media management practices, and (6) prioritizing order generation over stability. KW - Journalismus KW - journalism KW - journalism theories KW - practice theory KW - theory development KW - digitization Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200819-42162 UR - https://www.hope.uzh.ch/scoms/article/view/j.scoms.2020.02.006 VL - 2020 SP - 1 EP - 15 ER - TY - JOUR A1 - Buschow, Christopher T1 - Why Do Digital Native News Media Fail? An Investigation of Failure in the Early Start-Up Phase JF - Media and Communication N2 - Digital native news media have great potential for improving journalism. Theoretically, they can be the sites where new products, novel revenue streams and alternative ways of organizing digital journalism are discovered, tested, and advanced. In practice, however, the situation appears to be more complicated. Besides the normal pressures facing new businesses, entrepreneurs in digital news are faced with specific challenges. Against the background of general and journalism specific entrepreneurship literature, and in light of a practice–theoretical approach, this qualitative case study research on 15 German digital native news media outlets empirically investigates what barriers curb their innovative capacity in the early start-up phase. In the new media organizations under study here, there are—among other problems—a high degree of homogeneity within founding teams, tensions between journalistic and economic practices, insufficient user orientation, as well as a tendency for organizations to be underfinanced. The patterns of failure investigated in this study can raise awareness, help news start-ups avoid common mistakes before actually entering the market, and help industry experts and investors to realistically estimate the potential of new ventures within the digital news industry. KW - Journalismus KW - Digitalisierung KW - Neue Medien KW - Entrepreneurship KW - digital-born news media KW - digital native news media KW - entrepreneurial journalism KW - news start-ups KW - practice theories KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200417-41347 UR - https://www.cogitatiopress.com/mediaandcommunication/article/view/2677 VL - 2020 IS - Volume 8, Issue 2 SP - 51 EP - 61 PB - Cogitatio Press CY - Lissabon ER - TY - JOUR A1 - Becher, Lia A1 - Völker, Conrad A1 - Rodehorst, Volker A1 - Kuhne, Michael T1 - Background-oriented schlieren technique for two-dimensional visualization of convective indoor air flows JF - Optics and Lasers in Engineering N2 - This article focuses on further developments of the background-oriented schlieren (BOS) technique to visualize convective indoor air flow, which is usually defined by very small density gradients. Since the light rays deflect when passing through fluids with different densities, BOS can detect the resulting refractive index gradients as integration along a line of sight. In this paper, the BOS technique is used to yield a two-dimensional visualization of small density gradients. The novelty of the described method is the implementation of a highly sensitive BOS setup to visualize the ascending thermal plume from a heated thermal manikin with temperature differences of minimum 1 K. To guarantee steady boundary conditions, the thermal manikin was seated in a climate laboratory. For the experimental investigations, a high-resolution DLSR camera was used capturing a large field of view with sufficient detail accuracy. Several parameters such as various backgrounds, focal lengths, room air temperatures, and distances between the object of investigation, camera, and structured background were tested to find the most suitable parameters to visualize convective indoor air flow. Besides these measurements, this paper presents the analyzing method using cross-correlation algorithms and finally the results of visualizing the convective indoor air flow with BOS. The highly sensitive BOS setup presented in this article complements the commonly used invasive methods that highly influence weak air flows. KW - Raumklima KW - Raumluftströmungen KW - Flow visualization KW - Convective indoor air flow KW - Background-oriented schlieren KW - Human thermal plume KW - Cross-correlation Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20220810-46972 N1 - This article is published by Elsevier in Optics and Lasers in Engineering 134 (2020) 106282 and may be found at https://doi.org/10.1016/j.optlaseng.2020.106282 Copyright © 2020 Elsevier Ltd. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the authors and Elsevier Ltd. VL - 2020 IS - Volume 134, article 106282 ER - TY - JOUR A1 - Saadatfar, Hamid A1 - Khosravi, Samiyeh A1 - Hassannataj Joloudari, Javad A1 - Mosavi, Amir A1 - Shamshirband, Shahaboddin T1 - A New K-Nearest Neighbors Classifier for Big Data Based on Efficient Data Pruning JF - Mathematics N2 - 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. KW - Maschinelles Lernen KW - Machine learning KW - K-nearest neighbors KW - KNN KW - classifier KW - big data KW - clustering KW - cluster shape KW - cluster density KW - classification KW - reinforcement learning KW - data science KW - computation KW - artificial intelligence KW - OA-Publikationsfonds2020 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200225-40996 UR - https://www.mdpi.com/2227-7390/8/2/286 VL - 2020 IS - volume 8, issue 2, article 286 PB - MDPI ER - TY - JOUR A1 - Hassannataj Joloudari, Javad A1 - Hassannataj Joloudari, Edris A1 - Saadatfar, Hamid A1 - GhasemiGol, Mohammad A1 - Razavi, Seyyed Mohammad A1 - Mosavi, Amir A1 - Nabipour, Narjes A1 - Shamshirband, Shahaboddin A1 - Nadai, Laszlo T1 - Coronary Artery Disease Diagnosis: Ranking the Significant Features Using a Random Trees Model JF - International Journal of Environmental Research and Public Health, IJERPH N2 - Heart disease is one of the most common diseases in middle-aged citizens. Among the vast number of heart diseases, coronary artery disease (CAD) is considered as a common cardiovascular disease with a high death rate. The most popular tool for diagnosing CAD is the use of medical imaging, e.g., angiography. However, angiography is known for being costly and also associated with a number of side effects. Hence, the purpose of this study is to increase the accuracy of coronary heart disease diagnosis through selecting significant predictive features in order of their ranking. In this study, we propose an integrated method using machine learning. The machine learning methods of random trees (RTs), decision tree of C5.0, support vector machine (SVM), and decision tree of Chi-squared automatic interaction detection (CHAID) are used in this study. The proposed method shows promising results and the study confirms that the RTs model outperforms other models. KW - Maschinelles Lernen KW - Machine learning KW - Deep learning KW - coronary artery disease KW - heart disease diagnosis KW - health informatics KW - data science KW - big data KW - predictive model KW - ensemble model KW - random forest KW - industry 4.0 Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200213-40819 UR - https://www.mdpi.com/1660-4601/17/3/731 VL - 2020 IS - Volume 17, Issue 3, 731 PB - MDPI ER - TY - JOUR A1 - Schönig, Barbara T1 - Paradigm Shifts in Social Housing After Welfare‐State Transformation : Learning from the German Experience JF - International Journal of Urban and Regional Research N2 - Welfare‐state transformation and entrepreneurial urban politics in Western welfare states since the late 1970s have yielded converging trends in the transformation of the dominant Fordist paradigm of social housing in terms of its societal function and institutional and spatial form. In this article I draw from a comparative case study on two cities in Germany to show that the resulting new paradigm is simultaneously shaped by the idiosyncrasies of the country's national housing regime and local housing policies. While German governments have successively limited the societal function of social housing as a legitimate instrument only for addressing exceptional housing crises, local policies on providing and organizing social housing within this framework display significant variation. However, planning and design principles dominating the spatial forms of social housing have been congruent. They may be interpreted as both an expression of the marginalization of social housing within the restructured welfare housing regime and a tool of its implementation according to the logics of entrepreneurial urban politics. KW - Deutschland KW - Sozialer Wohnungsbau KW - Wohnungspolitik KW - Social Housing KW - Welfare State KW - Housing Policy Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200709-41966 UR - https://onlinelibrary.wiley.com/doi/full/10.1111/1468-2427.12914 VL - 2020 PB - John Wiley & Sons ER - TY - CHAP A1 - Bee, Julia T1 - Collagen, Montagen, Anordnen, Umordnen - Wie mit Bildern experimentieren T2 - Experimente lernen, Techniken tauschen, ein spekulatives Handbuch N2 - Experimente lernen, Techniken tauschen. Ein spekulatives Handbuch Das spekulative Handbuch bietet vielfältige Techniken für ein radikales Lernen und Vermitteln. Es umfasst konkrete Anleitungen, Erfahrungen und theoretische Überlegungen. Die Texte beteiligen sich an der Konzeption einer Vermittlung, die das gemeinsame Experimentieren (wieder) einführt. Im Seminarraum, in Workshops, auf Festivals, in Fluren, Parks und der Stadt finden Lernen und Verlernen statt. Texte und Anleitungen u. a. zu: Filmessays, Collagen, Banküberfällen, der Universität der Toten, wildem Schreiben, konzeptuellem speed Dating, neurodiversem Lernen, Format-Denken, dem Theater der Sorge, dem Schreiblabor, dem Körperstreik. KW - Montage KW - Collage KW - Künstlerische Forschung KW - Didaktik KW - Vermittlung Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20201008-42504 UR - https://nocturne-plattform.de/text/collagen-montagen-anordnen-umordnen-wie-mit-bildern-experimentieren SP - 29 EP - 49 PB - Noturne CY - Berlin/Weimar ER - TY - JOUR A1 - Dokhanchi, Najmeh Sadat A1 - Arnold, Jörg A1 - Vogel, Albert A1 - Völker, Conrad T1 - Measurement of indoor air temperature distribution using acoustic travel-time tomography: Optimization of transducers location and sound-ray coverage of the room JF - Measurement N2 - Acoustic travel-time TOMography (ATOM) allows the measurement and reconstruction of air temperature distributions. Due to limiting factors, such as the challenge of travel-time estimation of the early reflections in the room impulse response, which heavily depends on the position of transducers inside the measurement area, ATOM is applied mainly outdoors. To apply ATOM in buildings, this paper presents a numerical solution to optimize the positions of transducers. This optimization avoids reflection overlaps, leading to distinguishable travel-times in the impulse response reflectogram. To increase the accuracy of the measured temperature within tomographic voxels, an additional function is employed to the proposed numerical method to minimize the number of sound-path-free voxels, ensuring the best sound-ray coverage of the room. Subsequently, an experimental set-up has been performed to verify the proposed numerical method. The results indicate the positive impact of the optimal positions of transducers on the distribution of ATOM-temperatures. KW - Bauphysik KW - Bauklimatik KW - Akustische Laufzeit-Tomographie Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20220524-46473 UR - https://www.sciencedirect.com/science/article/abs/pii/S0263224120304723?via%3Dihub VL - 2020 IS - Volume 164, article 107934 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Amirinasab, Mehdi A1 - Shamshirband, Shahaboddin A1 - Chronopoulos, Anthony Theodore A1 - Mosavi, Amir A1 - Nabipour, Narjes T1 - Energy‐Efficient Method for Wireless Sensor Networks Low‐Power Radio Operation in Internet of Things JF - electronics N2 - 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). KW - Internet der Dinge KW - Internet of things KW - wireless sensor networks KW - ContikiMAC KW - energy efficiency KW - duty-cycles KW - clear channel assessments KW - fog computing KW - smart sensors KW - signal processing KW - received signal strength indicator KW - OA-Publikationsfonds2020 KW - RSSI Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200213-40954 UR - https://www.mdpi.com/2079-9292/9/2/320 VL - 2020 IS - volume 9, issue 2, 320 PB - MDPI ER - TY - JOUR A1 - Wellbrock, Christian-Mathias A1 - Arango Kure, Maria A1 - Buschow, Christopher T1 - Competition and Media Performance: A Cross-National Analysis of Corporate Goals of Media Companies in 12 Countries JF - International Journal of Communication N2 - Despite digitization and platformization, mass media and established media companies still play a crucial role in the provision of journalistic content in democratic societies. Competition is one key driver of (media) company behavior and is considered to have an impact on the media’s performance. However, theory and empirical research are ambiguous about the relationship. The objective of this article is to empirically analyze the effect of competition on media performance in a cross-national context. We assessed media performance of media companies as the importance of journalistic goals within their stated corporate goal system. We conducted a content analysis of letters to the shareholders in annual reports of more than 50 media companies from 2000 to 2014 to operationalize journalistic goal importance. When employing a fixed effects regression analysis, as well as a fuzzy set qualitative comparative analysis, results suggest that competition has a positive effect on the importance of journalistic goals, while the existence of a strong public service media sector appears to have the effect of “crowding out” commercial media companies. KW - Öffentlich-rechtlicher Rundfunk KW - Wettbewerb KW - Leistungsverhalten KW - media performance KW - competition KW - public service media KW - fuzzy set qualitative comparative analysis KW - fixed effects regression KW - Performance Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20201221-43175 UR - https://ijoc.org/index.php/ijoc/article/view/13576 VL - 2020 IS - Vol 14 (2020) SP - 6154 EP - 6181 PB - USC, University of Southern California CY - Annenberg, California ER - TY - THES A1 - Krtilova, Katerina T1 - Gesten des Denkens. Vilém Flussers Medienphilosophie N2 - In einer systematischen Interpretation von Vilém Flussers Werk schlägt die Arbeit vor, Flussers Ansatz als einen medienphilosophischen zu verstehen, insofern er das „wie“ der medienphilosophischen Fragestellung in den Mittelpunkt rückt. Medien werden nicht erst dann zu einem wesentlichen Bestandteil von Flussers Philosophie, wenn er sie explizit zum Gegenstand seiner Untersuchungen der gegenwärtigen Kultur und Gesellschaft oder historischer Rückblicke macht; Denken vollzieht sich immer in Medien oder medialen Praktiken, es wird nicht nur von ihnen (mit) geprägt – ohne Medien gäbe es kein Denken und umgekehrt verändert sich Philosophie mit den (jeweils) neuen Medien. Ausgehend von Begriffen oder eher Denkfiguren, die neben dem „was“ des jeweils verhandelten Themas auch das „wie“ der Reflexion selbst adressieren, wird der „Umbruch in der Struktur des Denkens“ zugleich als Beschreibung von Medienumbrüchen verstanden – mit dem Fluchtpunkt des Sprungs in das Universum der Komputation – und als Vollzug der gegenwärtigen Veränderung der „Methode des Denkens“. Flussers (Ver)Suche einer Reflexion, die nicht mehr durch das Medium Schrift strukturiert ist, sondern sowohl alten Medien wie dem Bild – bzw. Praktiken des Abbildens, Darstellens, Einbildens usw. – als auch neuen Medien – dem Komputieren – Geltung verschafft, laufen auf eine widersprüchliche Diagnose des neuen Universums der Komputation (anders: der technischen Bilder) hinaus : eine kybermetisch inspirierte Vision der frei modellierbaren Wirklichkeit(en) einerseits und die Dystopie einer Welt, in der Apparaten Denken, Wahrnehmen und Handeln beherrschen andererseits. Die Arbeit zeigt auf, wie Flusser zu dieser Aporie der Medienreflexion – die weit über Flussers Werk hinaus virulent bleibt – gelangt und wie sie, ausgehend von seiner Figur der Geste, im Sinne einer performativen Medienreflexion gelöst werden könnte. KW - Medientheorie KW - Medienphilosophie KW - Medienphilosophie KW - Performativität KW - Vilém Flusser KW - digitale Kultur KW - technische Bilder Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200123-40679 ER - TY - RPRT A1 - Buschow, Christopher A1 - Wellbrock, Christian-Mathias T1 - Die Innovationslandschaft des Journalismus in Deutschland N2 - Das vorliegende Gutachten befasst sich mit der Innovationslandschaft des deutschen Journalismus. Innovation wird als eine essenzielle Voraussetzung verstanden, um tragfähige Lösungsansätze für die gegenwärtigen Probleme des Journa-lismus zu entwickeln. Im Mittelpunkt des Gutachtens steht die Frage, wie Innovationspolitik im Journalismus – d. h. die Unterstützung von Innovation durch die öffentliche Hand – funktionstüchtig ausgestaltet werden kann. Dabei wird dem Innovationssysteme-Ansatz gefolgt, welcher Probleme, Barrieren und Hemmnisse identifiziert, die der Innovationsfähigkeit des Journalismus in Deutschland grundlegend im Wege stehen. KW - Journalismus KW - Innovation KW - Deutschland KW - Journalismus KW - Innovationsfähigkeit KW - Forschungsbericht Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:gbv:wim2-20200924-42407 UR - https://www.medienanstalt-nrw.de/fileadmin/user_upload/NeueWebsite_0120/Zum_Nachlesen/Gutachten_Innovationslandschaft_Journalismus.pdf ER -