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检索条件"丛书名=Learning and Analytics in Intelligent Systems"

共 229 条记录，以下是151-160 订阅

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Performance Analysis of Apache Spark MLlib Clustering on Batch Data Stored in Cassandra 1

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作者： Anusha, K. UshaRani, K. Department of Computer Science Sri Padmavati Mahila Visvavidyalayam Tirupati India

ISBN: (数字)9783030469399

ISBN: (纸本)9783030469382;9783030469412

With the tremendous increase in the amount of data being generated from variety of sources there is a need of efficient data storage and processing techniques. Some of the sources generating this large amount of data are Weather Sensors, Scientific experiments, etc. This huge voluminous data is termed as BigData. Due to ever-increasing amount of data there is a demand for faster data ingestion and processing. Apache Spark, a dominant processing tool is a publicly available platform for processing outsized data and is mostly intended for iterative machine learning jobs. In this study, an integrated approach i.e., Spark MLlib Clustering on batch weather data stored in Cassandra database is proposed. This helps to analyze our data into number of Clusters which is required and useful for further examination of data. The main idea of this study is to evaluate Batch Processing performance of an integrated approach with two popular clustering algorithms. © 2020, Springer Nature Switzerland AG.

关键词： Big data

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Classification of Cotton Crop Pests Using Big Data analytics 1

引用

作者： Durgabai, R.P.L. Bhargavi, P. Jyothi, S. Department of Computer Science Sri Padmavati Mahila Visvavidyalayam Tirupati517502 India

ISBN: (数字)9783030469399

ISBN: (纸本)9783030469382;9783030469412

Agriculture is the main occupation in Andhra Pradesh (A.P.), the atmosphere and land of A.P. is appropriate for cultivating variety of crops like rice, wheat and cotton. Crop protection is one of the foremost challenges in agriculture. Pest classification during unusual weather conditions is very strong confront and the goal of every farmer is to protect the crops in exact time. Big Data analytics is playing a dominant role in agriculture sectors which helps in making good decisions to prevent any crops loss. Machine learning algorithm is a best analytical platform that automates analytical model building. Classification is a main method of machine learning which is useful to classify the problem and provide better solutions. This paper, demonstrates the implementation of three classifiers K-Nearest Neighbor (K-NN), Naive Bayes (NB), Decision Tree (DT) on cotton pests data, out of which the decision tree classifier proved to be the best for analysis. © 2020, Springer Nature Switzerland AG.

关键词： Big data

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Experimental Evaluation of Traceability Checking Tool for Goal Dependency Modeling 1

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作者： Kaiya, Haruhiko Fujita, Wataru Yamada, Ryotaro Hazeyama, Atsuo Ogata, Shinpei Okubo, Takao Yoshioka, Nobukazu Washizaki, Hironori Kanagawa University Hiratsuka259-1293 Japan Tokyo Gakugei University Tokyo84-8501 Japan Shinshu University Nagano380-0928 Japan IISEC Yokohama221-0835 Japan NII Tokyo100-0003 Japan Waseda University Tokyo169-8555 Japan

ISBN: (数字)9783030539498

ISBN: (纸本)9783030539481;9783030539511

In a complex socio-technical system, a human’s goal is delegated to many actors such as human and machines. Because the delegated goal can be decomposed into several sub-goals by each actor, goals are delegated recursively until an actor provides the means to achieve each sub-goal. We have already proposed a notation and a method called GDMA to represent and analyze the issues above. Because GDMA can be represented in a class diagram, software engineers do not have to use specific tools of GDMA models. To confirm whether a goal is properly achieved by suitable means, we have to trace such delegation and decomposition relationships. However, it is not easy to confirm it in a real-world system because of the system’s complexity. In this paper, we present a tool to check such traceability. The tool is implemented as a plugin of an existing UML modeling editor, and goal dependencies and decompositions are depicted using color. We also evaluate the tool through a comparative experiment. As a result, the tool enables an analyst to check the traceability without omission although it does not improve efficiency of the traceability checking task. © 2020, Springer Nature Switzerland AG.

关键词： Decomposition

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Integrating OpenMTC Framework into OneM2M Architecture for a Secure IoT Environment 1

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作者： Misbahuddin, Mohammed Agrawal, Aditi Basu, Aishani Jain, Ankita C-DAC Bangalore India PESIT Bangalore India

ISBN: (数字)9783030385019

ISBN: (纸本)9783030385002;9783030385033

As the current era of Internet of Things (IoT) and M2M communication advances, intercommunication of devices becomes instrumental for establishing a smart and secure IoT environment. To enable such a smart and secure system, which seamlessly integrates devices like sensors and actuators independent of the underlying legacy networks, a set of standards called oneM2M was devised. Thus, this set of standards has successfully facilitated communication between any two applications which may have different underlying communication protocols. A common service layer implements these set of standards which comes in between the application and the underlying network entity. The overall architecture comprises of the open-source integration middleware platform OpenMTC, which is based on oneM2M standards and is implemented using Python. This paper presents the results of the successful intercommunication between three sensors and actuators each relying on a different communication protocol, namely Wi-Fi, Bluetooth, Serial Communication and Ethernet in a secure IoT environment and the results obtained have successfully proved the efficacy of the proposed system. © 2020, Springer Nature Switzerland AG.

关键词： Python

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Comparative in Silico Studies for the Molecular Basis of Lepidopteran Insect Pests Bio-Control Using Insect’s Own Enzymes 1

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作者： Amardev Rajesh, V. Mamatha, D.M. Bhaskar, M. Department of Biotechnology ANU AP Guntur India Department of Bioscience & Sericulture SPMVV University AP Tirupati India Department of Zoology Sri Venkateswara University AP Tirupati India

ISBN: (数字)9783030469436

ISBN: (纸本)9783030469429;9783030469450

In silico analysis deals with understanding the protein behavior in the biological mechanism of an organism using computational approaches. In lepidopteran insect pest, Juvenile Hormone Epoxide Hydrolase (JHEH) regulates and degenerate the Juvenile Hormone (JH), which is extremely important for the insect growth, development and reproductive physiology. Helicoverpa armigera (Ha) is one such important lepidopteran pest which causes extensive dame to the commercial crops like cotton, legume crops and etc., thereby affecting the agriculture industry. Because of JHEH key role in JH degeneration mechanism, in the present study Ha JHEH gene active site sequence is subjected to blastx to identify its homologs. The Ha JHEH and its homologs were analyzed using various online and offline bioinformatics to explore the sequence, structural and evolutionary information, to find out the possible bio pesticide strategies. Import functional domains of JHEH that contribute in JH degeneration mechanism like putative Catalytic triad, Lid domain and Oxyanion Hole HGWP Motif and other related functional domains were identified in the selected lepidopteran pests for further analysis. © 2020, Springer Nature Switzerland AG.

关键词： Hydrolases

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A Survey on Methods of Ontology learning from Text 1

引用

作者： Lourdusamy, Ravi Abraham, Stanislaus Department of Computer Science Sacred Heart College Tamil Nadu Tirupattur635 601 India

ISBN: (数字)9783030385019

ISBN: (纸本)9783030385002;9783030385033

Ontologies continue to emerge in performing a greater function in various business processes and knowledge sharing in the field of modern information systems. They help to exchange and extend, from syntax to semantic, data and knowledge. They are viewed as a remedy for interoperable semantics which power semantic web. Since the turn of the millennium, ontology learning (OL) from text has received a considerable attention with a sudden surge of textual information for promising research. Remarkably, with intermingling of various disciplines like text mining (TM), statistical analysis techniques (SAT), machine learning (ML), knowledge representation (KR), natural language processing (NLP), etc., more research is on in the area of Ontological Engineering and OL from text. This survey brings out several outcomes of foregone research, discusses challenges and limitations of research in the past decade and points to new challenges in future. © 2020, Springer Nature Switzerland AG.

关键词： Surveys

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Revisiting Principles and Challenges in Natural Language Programming 1

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作者： Sales, Juliano Efson Freitas, André Oliveira, Douglas Koumpis, Adamantios Handschuh, Siegfried Department of Computer Science and Mathematics University of Passau Innstraße 43 Passau94032 Germany Institute of Computer Science University of St. Gallen Rosenbergstrasse 30 St. Gallen9000 Switzerland School of Computer Science University of Manchester Kilburn Building Oxford Road ManchesterM13 9PL United Kingdom Architecture and Analytics Group VLI Logística Rua dos Tapuias 49 Belo Horizonte Brazil Institute of Digital Enabling Bern University of Applied Sciences Brückenstrasse 73 Bern3005 Switzerland

ISBN: (数字)9783030539498

ISBN: (纸本)9783030539481;9783030539511

Automation has faced the risk of reducing its pace due to the shortage of information technology professionals. Although part of the programming demand can be addressed by simple compositions of high-level functions and data flows, non-technical professionals are still unable to build their own software given the intrinsic complexity of coding. Among other types of end-user development, natural language programming has emerged as a strong candidate to fill this gap by developing methods and tools to allow end users to program. The paper revisits some principles of evaluation of traditional programming languages and analyses the new challenges to deliver an effective end-user development platform based on aspects of natural language processing, human-computer interaction, software engineering, and programming education. We advocate that an effective end-user platform is essentially hybrid, combining features from different branches of the end-user development research, having, however, a search mechanism with semantic capabilities at its centre. © 2020, Springer Nature Switzerland AG.

关键词： Semantics

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How the Apriori Algorithm Can Help to Find Semantic Duplicates in Ontology 1

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作者： Astrova, Irina Koschel, Arne Lee, Su Ling Department of Software Science School of IT Tallinn University of Technology Akadeemia tee 21 Tallinn12618 Estonia Faculty IV Department of Computer Science University of Applied Sciences and Arts Hannover Ricklinger Stadtweg 120 Hannover30459 Germany

ISBN: (数字)9783030539498

ISBN: (纸本)9783030539481;9783030539511

Ontology-based data integration attempts to overcome the semantic heterogeneity problem in data integration. Semantic heterogeneity refers to an ambiguous interpretation of terms that describes the meaning of data in heterogeneous resources. However, the presence of semantic duplicates such as similar attributes in the integrated ontologies can lead to incomplete query results. This paper proposes to use the Apriori algorithm from market basket analysis to find similar attributes in an ontology. © 2020, Springer Nature Switzerland AG.

关键词： Data integration

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Adoptability Assessment of AI Service systems 1

引用

作者： Takeuchi, Hironori Oyama, Yukino Yamamoto, Kazuki Musashi University Tokyo Japan

ISBN: (数字)9783030539498

ISBN: (纸本)9783030539481;9783030539511

In this study, we consider the adoption of artificial intelligence (AI) service systems developed in a business domain to other domains. We propose a method to assess whether we can apply an existing AI service system to a different business task. We identify conditions for the adoption of the AI service system, and through experiments, confirm that we can predict whether the example inputs for a new business task can work for the existing system by referring to the conditions without the support of data scientists. © 2020, Springer Nature Switzerland AG.

关键词： Data handling

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Identifications of Webpage Layout Patterns Based on Lines of Vision 1

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作者： Shirogane, Junko Eguchi, Atsuko Iwata, Hajime Fukazawa, Yoshiaki Tokyo Woman’s Christian University Tokyo Japan Waseda University Tokyo Japan Kanagawa Institute of Technology Kanagawa Japan

ISBN: (数字)9783030539498

ISBN: (纸本)9783030539481;9783030539511

Webpage layouts strongly affect usability. Although usability has various elements, this study focuses on readability. To realize a good readability, some layout patterns are well known by webpage contents. Because users do not always see the intended layout patterns by web designers, readability may not be realized. Thus, we propose a method to identify the implemented layout patterns for target webpages using the users’ lines of vision. In our method, blocks that consist of the layout patterns and the order of the blocks, which users see, are specified for a webpage. Users’ lines of vision are analyzed when viewing the webpages, and the implemented layout patterns are identified. Concretely, whether an implemented layout pattern agrees with the intended one is analyzed. If the recorded coordinates of the lines of vision are included in the specified blocks and the blocks are viewed in the specified order, then the implemented and intended layouts of the webpage agree. © 2020, Springer Nature Switzerland AG.

关键词： Websites

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