Crop cultivation is one of the oldest activities of civilization. For a long time, crop production was carried out based on knowledge passed from generation to generation. However, due to the rapid growth in the human population of the world, human knowledge-based cultivation is not enough to meet the demanding need. To address this issue, the usage of machine learning-based tools has been studied in this paper. An experiment has been carried out over 0.3 million data. This dataset identifies 46 (...) prominent parameters for cultivation, which is collected from the Department of Agriculture Extension, Bangladesh. Comparison between neural networks and numbers of machine learning algorithms has been carried out in this research. It is observed that the neural network outperforms the other methods by maintaining an average prediction accuracy of 96.06% for six different crops. Other contemporary machine learning algorithms, namely, support vector machine, random forest, and logistic regression, have average prediction accuracy of around 68.9%, 91.2%, and 62.39%, respectively. (shrink)

A personalized recommender system is broadly accepted as a helpful tool to handle the information overload issue while recommending a related piece of information. This work proposes a hybrid personalized recommender system based on affinity propagation, namely, APHPRS. Affinity propagation is a semisupervised machine learning algorithm used to cluster items based on similarities among them. In our approach, we first calculate the cluster quality and density and then combine their outputs to generate a new ranking score among clusters for the (...) personalized recommendation. In the first phase, user preferences are collected and normalized as items rating matrix. This generated matrix is then clustered offline using affinity propagation and kept in a database for future recommendations. In the second phase, online recommendations are generated by applying the offline model. Negative Euclidian similarity and the quality of clusters are used together to select the best clusters for recommendations. The proposed APHPRS system alleviates problems such as sparsity and cold-start problems. The use of affinity propagation and the hybrid recommendation technique used in the proposed approach helps in improving results against sparsity. Experiments reveal that the proposed APHPRS performs better than most of the existing recommender systems. (shrink)

Die Welt ist alles, was wir in unseren naturwissenschaftlichen Theorien beschreiben können – so eine weit verbreitete Überzeugung, die seit den Tagen des Positivismus unser Weltbild bestimmt. Aber reicht das tatsächlich schon aus? Wer sich am Ideal der wissenschaftlichen Erkenntnis orientiert, neigt dazu, viele nicht-begriffliche Erfahrungsformen zu unterschlagen, die uns aus dem Alltag vertraut sind: Symbolsysteme wie Musik, Literatur oder Bilder, Instanzen der unmittelbaren Erfahrung wie Anschauung, Wahrnehmung oder Gefühl und den Bereich des praktischen Könnens. In der Regel sind wir (...) nicht in der Lage, den Gehalt dieser Phänomene vollständig begrifflich wiederzugeben. Dennoch ist das weite Feld des Nichtbegrifflichen eine unverzichtbare Voraussetzung unserer Sätze und Gedanken: Ohne Kunst, Wahrnehmung und Handeln gibt es kein Denken, keine Wissenschaft, keine Philosophie. Der Band geht der Vielfalt des Nicht-Begrifflichen in ästhetischen, symboltheoretischen und semantischen Untersuchungen nach. Aus ihnen ergibt sich ein umfassender systematischer Überblick über eines der spannendsten und offensten Problemfelder der aktuellen philosophischen Debatte. Mit Beiträgen von: Andreas Bartels, Uwe Baumann, Volker Beeh, Gottfried Boehm, Olaf Breidbach, Joachim Bromand, Gottfried Gabriel, Markus Gabriel, Ernest Wolf Gazo, Annemarie Gethmann-Siefert, Jürgen Goldstein, Jens Halfwassen, Thomas Sören Hoffmann, Wolfgang Harms, Jochen Hörisch, Peter Janich, Guilherme F. R. Kisteumacher, Jakub Kloc-Konkolowicz, Imi Knoebel, Theo Kobusch, Klaus-M. Kodalle, Sibylle Krämer, Guido Kreis, Wolfgang Kubin, Sönke Lorenz, Antonio Cota Marçal, Aliasghar Mosleh, Theodoros Penolidis, Dominik Perler, Hans-Joachim Pieper, Andrzej Przylebski, Birgit Sandkaulen, Matthias Schmoeckel, Oswald Schwemmer, Josef Simon, Pirmin Stekeler-Weithofer, Dieter Teichert, Kai Vogeley, Gottfried Willems und Gereon Wolters. (shrink)