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Nowadays, economic and ecologically sound treatment systems are highly encouraged to treat large-scale wastewater emanating from different sources. In the present study, an effort has been made using chitosan as a natural coagulan...
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Nowadays, economic and ecologically sound treatment systems are highly encouraged to treat large-scale wastewater emanating from different sources. In the present study, an effort has been made using chitosan as a natural coagulant and alum as a chemical coagulant for the treatment of raw sewage. The coagulation process has been carried out to evaluate the optimum dose of coagulant under different pH values. Also, the alum and chitosan dosages in different mix proportions have been used to observe the turbidity, conductivity, salinity, TDS, COD, and TSS removal from raw sewage. The optimum pH value of 7.1 has been observed under different coagulants dosages. Also, at alum:chitosan ratio of 1:1 the maximum turbidity removal of 64% has been observed at turbidity concentration of 88 NTU. The synergistic effect is found to be more effective in COD. The results indicated that the synergistic effect shows maximum percent removal with a minimum dose of alum and chitosan, which would yield significant environmental and economic benefits.
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The sEMG (surfaceElectro-Myogram) guided prosthetic arm which is commonly used due to their ease to handle and naturalness. In last few years deep learning revolutionized numerous fields of machine learning, including identificati...
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The sEMG (surfaceElectro-Myogram) guided prosthetic arm which is commonly used due to their ease to handle and naturalness. In last few years deep learning revolutionized numerous fields of machine learning, including identification of visual images, computer vision, protein structure prediction and speech recognition, etc. The recent advances in deep learning and convolutional neural networks revolutionized several fields which motivates us to use Deep Learning technique of Convolutional Neural Network (CNN) to classify different hand motions depending upon nuance set of sEMG signals. Data of ten subjects who were made to perform various hand motions, is acquired. The results show that classification accuracy upto 96.2% is achieved using CNN classifier. Comparative analysis of CNN with other classifiers: Artificial Neural Network (ANN), Support Vector Machine (SVM), Decision tree, logistic regression and Random forest yields an improved accuracy. These results suggest that the proposed method is competent in improving the pattern recognition of myoelectric signals which is key step in development of artificial hand.
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This paper proposes an advanced personality classification and professional profile prediction system. The system grasps from the personality patterns by using advanced data mining to mine user characteristics data. This E based o...
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This paper proposes an advanced personality classification and professional profile prediction system. The system grasps from the personality patterns by using advanced data mining to mine user characteristics data. This E based on its past classifications from the data mining algorithms, and it classifies or predicts the user's personality. Several user characteristics and behaviors are analyzed by this system and based on the patterns observed, it stores its own user characteristics patterns which then are stored in a database. On the basis of personality data which was stored by classification of previous user data, the system predicts user personality. This can further be used for job prediction, subject selection, etc. This system is useful for hiring purposes of companies as well as for characterization of team members already working in a professional environment.
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摘要 :
This paper proposes an advanced personality classification and professional profile prediction system. The system grasps from the personality patterns by using advanced data mining to mine user characteristics data. This E based o...
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This paper proposes an advanced personality classification and professional profile prediction system. The system grasps from the personality patterns by using advanced data mining to mine user characteristics data. This E based on its past classifications from the data mining algorithms, and it classifies or predicts the user's personality. Several user characteristics and behaviors are analyzed by this system and based on the patterns observed, it stores its own user characteristics patterns which then are stored in a database. On the basis of personality data which was stored by classification of previous user data, the system predicts user personality. This can further be used for job prediction, subject selection, etc. This system is useful for hiring purposes of companies as well as for characterization of team members already working in a professional environment.
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A biography of a person is the detailed description of several life events including his education, work, relationships and death. Wikipedia, the free web-based encyclopedia, consists of millions of manually curated biographies of...
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A biography of a person is the detailed description of several life events including his education, work, relationships and death. Wikipedia, the free web-based encyclopedia, consists of millions of manually curated biographies of eminent politicians, film and sports personalities, etc. However, manual curation efforts, even though efficient, suffers from significant delays. In this work, we propose an automatic biography generation framework BioGen. BioGen generates a short collection of biographical sentences clustered into multiple events of life. Evaluation results show that biographies generated by BioGen are significantly closer to manually written biographies in Wikipedia. A working model of this framework is available at nlpbiogen.herokuapp.com/home/.
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摘要 :
A biography of a person is the detailed description of several life events including his education, work, relationships and death. Wikipedia, the free web-based encyclopedia, consists of millions of manually curated biographies of...
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A biography of a person is the detailed description of several life events including his education, work, relationships and death. Wikipedia, the free web-based encyclopedia, consists of millions of manually curated biographies of eminent politicians, film and sports personalities, etc. However, manual curation efforts, even though efficient, suffers from significant delays. In this work, we propose an automatic biography generation framework BioGen. BioGen generates a short collection of biographical sentences clustered into multiple events of life. Evaluation results show that biographies generated by BioGen are significantly closer to manually written biographies in Wikipedia. A working model of this framework is available at nlpbiogen.herokuapp.com/home/.
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