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A New K-Nearest Neighbors Classifier for Big Data Based on Efficient Data Pruning
No full textThe 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however, identifying the neighbors in a large amount of data imposes a large computational cost so that it is no longer applicable by a single computing machine.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
Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants
No full textA 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
Money for Nothing and Content for Free?
No full textWie können journalistische Angebote nachhaltig finanziert werden? Dies bleibt die Kernfrage für Medienhäuser und journalistische Neugründungen bei der Entwicklung und beim Aufbau tragfähiger digitaler Geschäftsmodelle.
Die Autoren des vorliegenden Bandes vermitteln einen breiten Überblick über den Wissensstand zum Thema Paid Content, Plattformen und Zahlungsbereitschaft im Journalismus und eröffnen innovative Blickwinkel auf neuartige Plattformmodelle ebenso wie auf Motive und Bedürfnisse der Nutzerinnen und Nutzer digitaljournalistischer Inhalte. Auf Grundlage empirischer Forschung werden Handlungsempfehlungen für die nutzerzentrierte Ausgestaltung von Paid-Content-Angeboten sowie neue Perspektiven auf Zahlungsbereitschaft im digitalen Journalismus erschlossen – relevant sowohl für die Wissenschaft wie auch für die Medienpraxis
Collagen, Montagen, Anordnen, Umordnen - Wie mit Bildern experimentieren
No full textExperimente 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
Formation of Geopolymers Using Sodium Silicate Solution and Aluminum Orthophosphate
No full textThis paper reports the formation and structure of fast setting geopolymers activated by using three sodium silicate solutions with different modules (1.6, 2.0 and 2.4) and a berlinite-type aluminum orthophosphate. By varying the concentration of the aluminum orthophosphate, different Si/Al-ratios were established (6, 3 and 2). Reaction kinetics of binders were determined by isothermal calorimetric measurements at 20 °C. X-ray diffraction analysis as well as nuclear magnetic resonance (NMR) measurements were performed on binders to determine differences in structure by varying the alkalinity of the sodium silicate solutions and the Si/Al-ratio. The calorimetric results indicated that the higher the alkalinity of the sodium silicate solution, the higher the solubility and degree of conversion of the aluminum orthophosphate. The results of X-ray diffraction and Rietveldt analysis, as well as the NMR measurements, confirmed the assumption of the calorimetric experiments that first the aluminum orthophosphate was dissolved and then a polycondensation to an amorphous aluminosilicate network occurred. The different amounts of amorphous phases formed as a function of the alkalinity of the sodium silicate solution, indicate that tetrahydroxoaluminate species were formed during the dissolution of the aluminum orthophosphate, which reduce the pH value. This led to no further dissolution of the aluminum orthophosphate, which remained unreacted
Fractional-Order Fuzzy Control Approach for Photovoltaic/Battery Systems under Unknown Dynamics, Variable Irradiation and Temperature
No full textFor this paper, the problem of energy/voltage management in photovoltaic (PV)/battery systems was studied, and a new fractional-order control system on basis of type-3 (T3) fuzzy logic systems (FLSs) was developed. New fractional-order learning rules are derived for tuning of T3-FLSs such that the stability is ensured. In addition, using fractional-order calculus, the robustness was studied versus dynamic uncertainties, perturbation of irradiation, and temperature and abruptly faults in output loads, and, subsequently, new compensators were proposed. In several examinations under difficult operation conditions, such as random temperature, variable irradiation, and abrupt changes in output load, the capability of the schemed controller was verified. In addition, in comparison with other methods, such as proportional-derivative-integral (PID), sliding mode controller (SMC), passivity-based control systems (PBC), and linear quadratic regulator (LQR), the superiority of the suggested method was demonstrated
Panafricanism and African Revolution in Brazilian Music
No full textThis 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
Music as living heritage
Get PDFWhat is cultural heritage, and why has it received so much public interest in recent years? Almost three decades after the World Organization UNESCO defined and established international recognition of Cultural and Natural Heritage sites and devised ways of protecting them, a completely new approach to cultural heritage emerged with the UNESCO
Convention for the Safeguarding of the Intangible Cultural Heritage in 2003. This global agreement for the maintenance, protection and dissemination of cultural manifestations and achievements that are not tangible objects or immobile monuments, like previous items classified as World Heritage, was a remarkable milestone of international cultural politics. This new understanding of cultural heritage owes much to representatives from Asian, African, and Latin American countries. In fact, just a few years after the promulgation of the 2003 Convention, the world cultural heritage map had already lost much of its European predominance. Asian countries such as China, Japan, South Korea, and India very soon showed up with lists of manifestations of their centenary (in some cases even millenary) national cultural heritages
Extreme Learning Machine-Based Model for Solubility Estimation of Hydrocarbon Gases in Electrolyte Solutions
Get PDFCalculating hydrocarbon components solubility of natural gases is known as one of the important issues for operational works in petroleum and chemical engineering. In this work, a novel solubility estimation tool has been proposed for hydrocarbon gases—including methane, ethane, propane, and butane—in aqueous electrolyte solutions based on extreme learning machine (ELM) algorithm. Comparing the ELM outputs with a comprehensive real databank which has 1175 solubility points yielded R-squared values of 0.985 and 0.987 for training and testing phases respectively. Furthermore, the visual comparison of estimated and actual hydrocarbon solubility led to confirm the ability of proposed solubility model. Additionally, sensitivity analysis has been employed on the input variables of model to identify their impacts on hydrocarbon solubility. Such a comprehensive and reliable study can help engineers and scientists to successfully determine the important thermodynamic properties, which are key factors in optimizing and designing different industrial units such as refineries and petrochemical plants
Spatial Analysis of Seasonal Precipitation over Iran: Co-Variation with Climate Indices
Get PDFTemporary 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