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检索条件"任意字段=International Conference on Advances in Data-driven Computing and Intelligent Systems, ADCIS 2022"

共 558 条记录，以下是341-350 订阅

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data-driven Stillbirth Prediction and Analysis of Risk Factors in Pregnancy

Data-Driven Stillbirth Prediction and Analysis of Risk Facto...

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international conference on Recent Trends in Machine Learning, IOT, Smart Cities and Applications, ICMISC 2020

作者： Unnikrishnan, Aravind Chandrasekaran, K. Shukla, Anupam Department of Computer Science and Engineering Indian Institute of Information Technology Pune India Department of Computer Science and Enigneering National Institute of Technology Karnataka SurathkalKarnataka India

ISBN: (纸本)9789811572333

One of the main issues in developing countries is the lack of policies for ensuring good public health conditions in rural areas. Maternal and child health care is one such area that has not improved in developing countries. Although child health has improved noticeably over the years, infant or under-5-mortality has not become any better. There remain major knowledge gaps in our understanding of how factors such as prenatal care, antenatal care, social and economic backgrounds, living conditions and lifestyle of pregnant women and their family members affect the pregnancy outcomes. Understanding such factors that affect the poor pregnancy outcome helps in formulating plans to prevent such issues and to treat them effectively. Determining health policies will be easier from a deeper analysis of such factors involved. This paper discusses some of the key machine learning techniques to predict the pregnancy outcome as a stillbirth or not and analyze some of the factors that majorly cause stillbirth. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Developing countries

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intelligent Inference Agent for Safety systems Events 15th

Intelligent Inference Agent for Safety Systems Events

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15th international conference on Dependability of Computer systems (DepCoS-RELCOMEX)

作者： Mazurkiewicz, Jacek Walkowiak, Tomasz Sugier, Jaroslaw Sliwinski, Przemyslaw Helt, Krzysztof Wroclaw Univ Sci & Technol Fac Elect Ul Wybrzee Wyspianskiego 27 PL-50370 Wroclaw Poland Teleste Sp Zoo Ul Szybowcowa 31 PL-54130 Wroclaw Poland

ISBN: (纸本)9783030482558;9783030482565

The paper describes the idea of the intelligent agent based on the ontogenic neural networks. The agent is created for inference problem needed in some safety systems. The main goal of the agent is to find if the aggregated data collected from the different sensors should point actual state of the system as alarm. The neural approach to the agent structure allows to combine the diverse nature of the sensors output into single clear answer. The ontogenic type of the neural network is the key to tune the topology to real needs driven by the scale and the safety systems features. The size of the training vectors can be limited as well as the number of the training epochs. Better results of alarm state prediction we can expect when we use the hybrid combination of agents focused on some specific types of events. This way the idea of the Complex Event Processing (CEP) safety systems seems to be sensible where Event Processing Agents (EPA) are also intelligent tools created based on already data sets collected previously.

关键词： Ontogenic neural network Safety system intelligent agent

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13th international conference on Interactive Mobile Communication, Technologies and Learning, IMCL 2019

13th International Conference on Interactive Mobile Communic...

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13th international conference on Interactive Mobile Communication, Technologies and Learning, IMCL 2019

ISBN: (纸本)9783030499310

The proceedings contain 105 papers. The special focus in this conference is on Interactive Mobile Communication, Technologies and Learning. The topics include: A Fiber Wireless A-RoF/IFoF Uplink Transmission of up to 0.6 Gb/s User data Rate Over a 32-Element 60 GHz Beam-Steering Antenna for 5G Fronthaul Networks;an eHealth-Care driven Perspective on 5G Networks and Infrastructure;25 Gb/s Colorless Transmitter Based on Reflective Electroabsorption Modulator for Ultra-Dense WDM-PON Application;Challenges of Using Phased Array Antennas in Commercial Backhaul Equipment at 26 GHz;towards intelligent Multi-Access Edge computing Using Machine Learning;Performance Analysis of NB-IoT Random Access Channel;work-in-Progress: Development of a Framework for Incorporating Usability Aspects with Digital Didactical Design for Mobile/Tablet Based Learning in Pre-primary Education;Promoting Authentic Student Assessment for STEM Project-Based Learning Activities;predictive Modeling Concerning Mobile Learning Advance;assessing Early Grade Mathematics Learner Outcomes Using m-Learning: The Case of JumpStart South Africa;Users’ and Experts’ Evaluation of TARGET: A Serious Game for Mitigating Performance Enhancement Culture in Youth;poster: Exploring the Educational Affordances of an Academic ePortfolio for Engineer Students Through a Self-regulated Learning Framework;m-Health as a Tool in the Cognitive Flexibility of the Elderly;Critical Categorization of Android and IOS Applications Available for STEAM Education in Early Childhood;museum Exhibits that Interact with Pupils’ Mobile Devices. The Case of Hellenic Maritime Museum;linkLearn: Blockchain Technology as a Learning Tool;can Elementary Students Co-design the Learning Content of Educational Apps: The We!Design!Fractions Participatory Design Approach;pedagogical Considerations for Mobile-Based Augmented Reality Learning Environments;dynamic Mobile Student Response System.

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Cloud computing, Machine Learning, and Secure data Sharing enabled through Blockchain

Cloud Computing, Machine Learning, and Secure Data Sharing e...

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international conference on Contemporary computing and Informatics (IC3I)

作者： Rajesh Singh Akkaraju Sailesh Chandra Babeetta Bbhagat Jeidy Panduro-Ramirez Anil Pandurang Gaikwad Bhasker Pant Uttaranchal Institute of Technology Uttaranchal University Uttarakhand India Doctoral Scholar School of Business and Management Christ (Deemed to be) University Bangalore Karnataka India Department of Computer Science & Information Technology Chhatrapati Shivaji Maharaj University Navi Mumbai Department of Business Universidad Tecnológica Del Perú Perú JSPM’S JSCOE-MCA Department Savitribai Phule Pune University Pune Maharashtra India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

Blockchain technologies are sweeping the globe. Cloud computing & secure data sharing have emerged as new technologies, owing to current advances in machine learning. Conventional machine learning algorithms need the collection & processing of training information on centralized systems. With the introduction of new decentralized machine learning algorithms & cloud computing, ML on-device information learning is now a reality. IoT gadgets may outsource training duties to cloud computing services to enable AI at the network’s perimeter. Furthermore, these dispersed edges intelligence architectures bring additional issues, also including consumer confidentiality & information safety. Blockchain has been proposed as a viable alternative to these issues. Blockchain, as a dispersed intelligent database, has evolved as a revolutionary innovation for the future phase of multiple industries’ uses due to its decentralized, accessible, & safe structure. This system also includes trustworthy automatic scripting running & unchangeable information recordings. As quantum technologies have proven more viable in the latest days, blockchain has faced prospective challenges from quantum computations. In this paper, we summarize the existing material in the study fields of blockchain-based cloud computing, machine learning, and secure data sharing, as well as a basic orientation to post-quantum blockchain to offer a summary of the existing state-of-the-art in these cutting-edge innovations.

关键词： Training Cloud computing Technological innovation Quantum computing Machine learning algorithms Machine learning Blockchains

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Development of data-driven Agent Model for Consumer Shopping Behavior in Commercial Facility 19th

Development of Data-Driven Agent Model for Consumer Shopping...

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19th international conference on Geometry and Graphics, ICGG 2020

作者： Yasufuku, Kensuke Izumoto, Junichi Abe, Hirokazu Osaka University Osaka Japan Takenaka Corporation Takenaka Japan

ISBN: (纸本)9783030634025

The use of ICT is becoming common in architectural design. It is expected that the increasing use of simulations and various AI technologies will lead to further improvements in the evaluation of spatial performance during the design stage. This study develops a data-driven agent model to simulate consumer shopping behavior in a commercial facility, with the ultimate aim of identifying the optimal store arrangement and passage shape. The subject commercial facility is a shopping center with 232 stores and 68,640 square meters of floor space. Four stories of the facility are above ground and one story is below. The data obtained from the facility and used in the model included (1) the number of entering/exiting visitors, (2) the purchase histories of membership cardholders, and (3) the number of visitors passing various points in the facility’s passageways. The membership cards of shoppers gave the authors access to 300,000 to 400,000 purchase histories of approximately 100,000 cardholders per month. To model consumer shopping behavior, the transition probabilities of moving between stores were generated from the available purchase histories. The study’s reproducibility was verified by comparing the simulated results to actual data on the number of remaining visitors, exiting visitors and visitors passing through specific points in the passages. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Consumer behavior

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Robust UI Automation Using Deep Learning and Optical Character Recognition (OCR)

Robust UI Automation Using Deep Learning and Optical Charact...

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international conference on Recent Trends in Machine Learning, IOT, Smart Cities and Applications, ICMISC 2020

作者： Singh, Mithilesh Kumar Fernandes, Warren Mark Rashid, Mohammad Saad Intelligent RPA SAP Labs Bangalore India STE SAP Labs Bangalore India PSCC SAP Labs Bangalore India

ISBN: (纸本)9789811572333

In the complete software development life cycle (SDLC), testing and maintenance stand slowest, and the reason being entire process is manual or manually maintained automation. Over time, companies have realized that it is very costly and time consuming. The biggest reason for manual maintenance of automation is its dependency on dynamic properties of the UI elements (xpath, class, ID) which directly depend on document object model (DOM). Cloud releases are very frequent, and changes in the UI properties are expected. In this paper, we are presenting a UI technology agnostic approach, which does not depend on the DOM and UI properties of the application rather behaves like a human and visually parses the screen. We use artificial intelligence to detect the UI elements, and even, just a mock-up of a screen can be parsed this way. This also enables test-driven development (TDD) of UI, among many other use cases. We used annotated UI image data for training our deep learning model, and the method has been validated with 94% accuracy on new UI elements. This approach does not require manual maintenance of the generated automates unless there is a functional change in the application. We propose UI technology agnostic, zero touch, self-healing UI automation. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Software testing

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Generating Abstract Test Cases from User Requirements using MDSE and NLP

Generating Abstract Test Cases from User Requirements using ...

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IEEE international conference on Software Quality, Reliability and Security (QRS)

作者： Sai Chaithra Allala Juan P. Sotomayor Dionny Santiago Tariq M. King Peter J. Clarke School of Computing and Information Sciences Florida International University Miami USA EPAM 41 University Drive Suite 202 Newton PA USA

Model-driven software engineering (MDSE) has emerged as a popular and commonly used method for designing software systems in which models are the primary development artifact over the last decade. MDSE has resulted in the trend toward further automating the software process. However, the generation of test cases from user requirements still lags in reaching the required level of automation. Given that most user requirements are written in natural language, the recent advances in natural language processing (NLP) provide an opportunity to further automate the test generation *** this paper, we exploit the advances in MDSE and NLP to generate abstract test cases from user requirements written in structured natural language and the respective data model. We accomplish this by creating meta-models for user requirements and abstract test cases and defining the appropriate transformation rules. To support this transformation, helper methods are defined to extract the relevant information from user requirements related to testing. To show the feasibility of the approach, we developed a prototype and conducted a case study with use cases and test cases from a Payroll Management System.

关键词： Prototypes Software quality Software systems Market research Natural language processing Software reliability Test pattern generators

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Application Research of "Target-driven Problem Traction" Teaching Method in "Radar Signal and data Processing" Course 1

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2nd international conference on Decision Science and Management, ICDSM 2019

作者： Zeng, Hui-Yong Wang, Xin Xu, Tong Wang, Shi-Qiang Air and Missile-Defence College Air Force Engineering University Xi’an710051 China

ISBN: (数字)9789811535888

ISBN: (纸本)9789811535871

In view of the nature, content, characteristics, and outstanding problems embedded in the "Radar Signal and data Processing" course designed for the radar engineering professionals, "target-driven question traction" teaching methods are best suited, and it effectively engages the classroom. Use problem solving as a classroom goal to motivate students to think independently, and experience exploration, theoretical analysis, and experimental verification under the guidance of faculty, and finally answer the target problem. Through three practical teaching cases, the specific implementation of the teaching method in the classroom is explained in detail. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Students

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"A Fresh Squeeze on data": Exploring Gender Differences in Self-efficacy and Career Interest in computing Science and Artificial Intelligence Among Elementary Students 24th

"A Fresh Squeeze on Data": Exploring Gender Differences in S...

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24th international conference on Artificial Intelligence in Education (AIED)

作者： Li, Shuhan Hasty, Annabel Wilson, Eryka Aliabadi, Roozbeh Columbia Univ New York NY 10025 USA Quest Acad Palatine IL 60067 USA Keiser Univ Ft Lauderdale FL 33309 USA ReadyAI Pittsburgh PA 15206 USA

ISBN: (纸本)9783031363351;9783031363368

Artificial intelligence (AI) is a growing field in both global job markets and educational spaces. This non-experimental quantitative study aims to explore how the educational program A Fresh Squeeze on data affects students' self-efficacy and career choices and whether gender will differentiate the learning outcomes. Under the social cognitive career theory framework, this study designs questionnaires as data collection instrument. The results suggest that the program significantly improves students' comfortability with AI-related subjects but not for career interest or other measurements in self-efficacy. Unexpectedly, the program's effect is not divided by gender. Nevertheless, this study opens up conversations about assisting students from underrepresented backgrounds to envision success in AI courses and career pathways through an activity-driven curriculum. The paper also informs educators and researchers to devise culturally responsive pedagogy in teaching AI that empowers young girls before they develop a gendered career view.

关键词： K-12 Education AI Education Gender Equity Self-Efficacy Career Interest

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A Web-Based Support for the Management and Evaluation of Measurement data from Stress-Strain and Continuous-Cooling-Transformation Experiments 40th

A Web-Based Support for the Management and Evaluation of Mea...

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40th Anniversary international conference on Information systems Architecture and Technology (ISAT)

作者： Kramer, Ronny Ruenger, Gudula Tech Univ Chemnitz Dept Comp Sci D-09107 Chemnitz Germany

ISBN: (纸本)9783030304409;9783030304393

Mechanical engineers are often faced with the challenge to keep track of the results of experiments done within their own institutions or other research groups. The lack of this knowledge may cause a potential waste of resources and time since experiments might be repeated if the existence of previous experiments is unknown or the data cannot be reused. The main problem with managing scientific data is the huge amount of experiments, the lack of public access to the results, and often missing meta-data which would be needed to compare the results. This article considers experiments and data resulting from experiments of Stress-Strain and Continuous-Cooling-Transformation experiments. It is shown how a web-driven data management process starting from the planning of experiments through to the evaluation of the measurement data could be supported by an appropriate work-flow to make sure that all meta-data is preserved to find and reuse the results.

关键词： data management data evaluation Web-based Material science

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