Pub Date : 1984-12-31DOI: 10.1515/9783112534526-015
M. DiSanti, B. Bonev, G. Villanueva, M. Mumma
In 2006 May, comet 73P/Schwassmann–Wachmann 3 experienced large outburst activity allowing us to study the gas production rate of fresh material released from the nucleus. We observed the comet in a coordinated campaign using millimeter and optical facilities at heliocentric distances between 0.966 and 1.033 AU. During this time, we had the opportunity to follow the post-outburst evolution of fragment B, which evidenced larger production rates in comparison to fragment C, the latter showing a rather stable gas production rate (QHCN ∼ 2 × 1025 molecules s−1). In addition to the investigation of the gas evolution, we studied the possible role of HCN and dust as progenitors for the CN radical. From our joint observations on May 12, we observed a high correlation of CN with HCN and low correlation with the continuum emission (grains). Herewith, our study supports the view of HCN as a major source of CN, although the presence of other sources for cyanide cannot be fully ruled out.
{"title":"C","authors":"M. DiSanti, B. Bonev, G. Villanueva, M. Mumma","doi":"10.1515/9783112534526-015","DOIUrl":"https://doi.org/10.1515/9783112534526-015","url":null,"abstract":"In 2006 May, comet 73P/Schwassmann–Wachmann 3 experienced large outburst activity allowing us to study the gas production rate of fresh material released from the nucleus. We observed the comet in a coordinated campaign using millimeter and optical facilities at heliocentric distances between 0.966 and 1.033 AU. During this time, we had the opportunity to follow the post-outburst evolution of fragment B, which evidenced larger production rates in comparison to fragment C, the latter showing a rather stable gas production rate (QHCN ∼ 2 × 1025 molecules s−1). In addition to the investigation of the gas evolution, we studied the possible role of HCN and dust as progenitors for the CN radical. From our joint observations on May 12, we observed a high correlation of CN with HCN and low correlation with the continuum emission (grains). Herewith, our study supports the view of HCN as a major source of CN, although the presence of other sources for cyanide cannot be fully ruled out.","PeriodicalId":249455,"journal":{"name":"A - K","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1984-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126827133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1984-12-31DOI: 10.1515/9783112534526-013
Ismoilov Nusrat, S. Jang
Artificial neural networks (ANN) have attracted significant attention from researchers because many complex problems can be solved by training them. If enough data are provided during the training process, ANNs are capable of achieving good performance results. However, if training data are not enough, the predefined neural network model suffers from overfitting and underfitting problems. To solve these problems, several regularization techniques have been devised and widely applied to applications and data analysis. However, it is difficult for developers to choose the most suitable scheme for a developing application because there is no information regarding the performance of each scheme. This paper describes comparative research on regularization techniques by evaluating the training and validation errors in a deep neural network model, using a weather dataset. For comparisons, each algorithm was implemented using a recent neural network library of TensorFlow. The experiment results showed that an autoencoder had the worst performance among schemes. When the prediction accuracy was compared, data augmentation and the batch normalization scheme showed better performance than the others.
{"title":"A","authors":"Ismoilov Nusrat, S. Jang","doi":"10.1515/9783112534526-013","DOIUrl":"https://doi.org/10.1515/9783112534526-013","url":null,"abstract":"Artificial neural networks (ANN) have attracted significant attention from researchers because many complex problems can be solved by training them. If enough data are provided during the training process, ANNs are capable of achieving good performance results. However, if training data are not enough, the predefined neural network model suffers from overfitting and underfitting problems. To solve these problems, several regularization techniques have been devised and widely applied to applications and data analysis. However, it is difficult for developers to choose the most suitable scheme for a developing application because there is no information regarding the performance of each scheme. This paper describes comparative research on regularization techniques by evaluating the training and validation errors in a deep neural network model, using a weather dataset. For comparisons, each algorithm was implemented using a recent neural network library of TensorFlow. The experiment results showed that an autoencoder had the worst performance among schemes. When the prediction accuracy was compared, data augmentation and the batch normalization scheme showed better performance than the others.","PeriodicalId":249455,"journal":{"name":"A - K","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1984-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121682811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1984-12-31DOI: 10.1515/9783112534526-021
Bogdan Andronic
Fuzzy set theory is circumscribed to the need to broaden the scope of classical mathematics meaning potentiation possibilities of mathematical modeling of real world systems. One can appreciate that the nature of reality and our way of thinking and the symbolism of interpersonal communication languages are also sources of uncertainty, imprecision, vagueness, ambiguity. The imperative of handling properties not necessarily "perfect determinable", namely "vaguely defined" (but with a measurable degree of uncertainty) has led to the imposition of fuzzy sets theory, which proved to be the systematic frame suitable to management of ambiguity and imprecision. Using fuzzy numbers involves some difficulties (related for example to the relaxation of equalities relative to invertible elements) that could be surpassed by using fuzzy numbers characterizing through families of "confidence intervals".
{"title":"I","authors":"Bogdan Andronic","doi":"10.1515/9783112534526-021","DOIUrl":"https://doi.org/10.1515/9783112534526-021","url":null,"abstract":"Fuzzy set theory is circumscribed to the need to broaden the scope of classical mathematics meaning potentiation possibilities of mathematical modeling of real world systems. One can appreciate that the nature of reality and our way of thinking and the symbolism of interpersonal communication languages are also sources of uncertainty, imprecision, vagueness, ambiguity. The imperative of handling properties not necessarily \"perfect determinable\", namely \"vaguely defined\" (but with a measurable degree of uncertainty) has led to the imposition of fuzzy sets theory, which proved to be the systematic frame suitable to management of ambiguity and imprecision. Using fuzzy numbers involves some difficulties (related for example to the relaxation of equalities relative to invertible elements) that could be surpassed by using fuzzy numbers characterizing through families of \"confidence intervals\".","PeriodicalId":249455,"journal":{"name":"A - K","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1984-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126455934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1984-12-31DOI: 10.1515/9783112534526-009
{"title":"VII. Zu den stilistischen Kennzeichnungen und Anwendungsbedingungen","authors":"","doi":"10.1515/9783112534526-009","DOIUrl":"https://doi.org/10.1515/9783112534526-009","url":null,"abstract":"","PeriodicalId":249455,"journal":{"name":"A - K","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1984-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126098255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1984-12-31DOI: 10.1515/9783112534526-005
{"title":"XI. Zur Definition der Lexeme","authors":"","doi":"10.1515/9783112534526-005","DOIUrl":"https://doi.org/10.1515/9783112534526-005","url":null,"abstract":"","PeriodicalId":249455,"journal":{"name":"A - K","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1984-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134094605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1984-12-31DOI: 10.1515/9783112534526-006
{"title":"IV. Zum Aufbau der Wörterbuchartikel","authors":"","doi":"10.1515/9783112534526-006","DOIUrl":"https://doi.org/10.1515/9783112534526-006","url":null,"abstract":"","PeriodicalId":249455,"journal":{"name":"A - K","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1984-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115863743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1984-12-31DOI: 10.1515/9783112534526-008
{"title":"VI. Zur Darstellung des Kontextes","authors":"","doi":"10.1515/9783112534526-008","DOIUrl":"https://doi.org/10.1515/9783112534526-008","url":null,"abstract":"","PeriodicalId":249455,"journal":{"name":"A - K","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1984-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130212215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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