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Using Contextual Text Mining and Ontology Methods to Establish a Novel Technology Trend and Associative Analysis Framework for Sustainable Energy Development in Taiwan

Using Contextual Text Mining and Ontology Methods to Establi...

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IEEE international conference on Big data

作者： Yi-Hao Hsiao Chia-Yi Chuang Megn-Chi Huang Chia-Lee Yang Jyh-Horng Wu National Center for High-Performance Computing National Applied Research Laboratories Hsinchu Taiwan Science & Technology Policy Research and Information Center National Applied Research Laboratories Taipei Taiwan

ISBN: (纸本)9781665480468

In 2015, the United Nations proposed 17 Sustainable Development Goals, SDGs, as the guidelines for all countries in the world to promote sustainable development before 2030. Government Research Bulletin (GRB), the research projects and technical reports sponsored by government, which has long-term, numerous, complete research method, technology development and policy analysis information in Taiwan. Therefore, it is an important and effective way to explore SDG-related information from a large amount of GRB text. In this paper, a novel technologies trend and associative analysis framework which uses contextual text mining and ontology methods is proposed and applied to SDG 7, which "Affordable and Clean Energy". First, we integrate dictionary-based method and semantic textual similarity analysis algorithm to obtain a SDG 7 classifier which can exactly and quickly classify a large amount number of GRB text to SDG 7. Then, two major SDG 7 analysis procedures based on the classification results are implemented. One is using contextual text mining algorithm to obtain energy technologies trend information. The other is adopting ontology method to establish energy technologies associative analysis concept map. According to the analysis results mentioned above, we are able to efficiently incorporate the energy technology with long-term trend, energy technology associative information, and the most influential authors on the specify energy technology in order to generate a global strategy for continuous improvement in Taiwan.

关键词： Text mining Government Semantics Ontologies Big data Writing Market research

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data Management and Visual Information Processing using Machine Learning

Data Management and Visual Information Processing using Mach...

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international conference on Contemporary computing and Informatics (IC3I)

作者： Arhath Kumar Shivani Joshi Shaik Vaseem Akram Joel Alanya-Beltran Mohammed Saleh Al Ansari Vikas Tripathi Department of MCA NMAM institute of Technology Nitte (Deemed to be University) Karnataka Department of computer Science & Engineering GL Bajaj Institute of Technology & Management Greater Noida Uttar Pradesh Uttaranchal Institute of Technology Uttaranchal University Dehradun Uttarakhand India Department of Electronic Universidad Tecnológica del Perú Perú Department of Chemical Engineering College of Engineering University of Bahrain Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

“Machine learning (ML) ”-based large-scale data insights are the foundation of many contemporary data-driven technologies. ML systems offer ways to define and carry out certain ML workloads effectively and flexibly. Because of information-driven application highlights, information-driven responsibility elements, and framework designs affected by customary information the executives draw near, data the board is at the centre of numerous ML frameworks. Moreover, a ton of present-day information-driven arrangements are based on AI (ML)- based on enormous data bits of knowledge. A few ML occupations can be characterized and executed effectively and deftly utilizing ML frameworks. data the executives are at the underpinning of numerous ML frameworks are reasonable to information-driven application qualities, information-driven responsibilities attributes, and framework models affected by old-style information the board techniques. Various ML clients with different ML lifecycle obligations and ML abilities are available in many Calculations. Information researchers are ML clients who have specialized information in ML and examination to control the information and make ML models for the business. The potential issues with data management that might arise in settings where machine learning procedures are used in the real world. Because we have first-hand experience with such huge pipelines, we can home in on issues relating to the interpretation of training data as well as its validation, cleaning, and enrichment. The objective of this article is to draw attention to these issues, establish links to previous efforts in the database area, and identify research questions that have not yet been solved.

关键词： Training Visualization Computer vision Technological innovation Biological system modeling Training data Machine learning

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Profitable Investment in PV and BES Integrated with EV Charging Stations in Croatia - Myth or Reality?

Profitable Investment in PV and BES Integrated with EV Charg...

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international Multidisciplinary conference on Computer and Energy science (SpliTech)

作者： Mirna Grž anić Alen Hrga Tomislav Capuder Department of Energy and Power Systems Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (纸本)9781665488280

The increasing number of electric vehicles (EVs) poses a challenge to the power system operation and manage-ment. To deal with the growing consumption together with the uncertainty related to the time of arrival at the charging station and EV state of energy, the paper investigates the profitability of investment in different low-carbon (LC) technologies in the EV charging stations based on real-EV-data optimization. The model considers several real-life charging points in Croatia at different location (high-way, parking lot in the capital city and parking lot at the sea-side). Analyses show that the investment in PV and BES is profitable under current retail market options resulting in 3% to 70% cost reduction wit different LC technology options, while recently introduced EV charging reimbursement shortens the period of investment in LC technology for 8 years.

关键词： Costs Uncertainty Profitability Power system dynamics Urban areas Pricing Electric vehicle charging

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Design and implementation of special data Encyclopedia system 2021

Design and implementation of special Data Encyclopedia syste...

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2021 10th international conference on Internet computing for science and Engineering

作者： Jianhong Feng Yuwei Zhou Zhaohong Yang Hongyu Wang Unit 32366 of the Chinese People's Liberation Army China Department of information and communication Army Academy of Armored Forces China

ISBN: (纸本)9781450384957

Abstract:The traditional data construction in the military field mainly focuses on the vertical business field, realizing the digitization of the military business and failing to meet the application requirements of horizontal data *** paper realizes the design of a special data encyclopedia system in the military field, and uses advanced big data processing technologies such as web crawler, knowledge spectrum, and full-text retrieval to realize the horizontal integration of data in the military field, mine the value of data in the military field, and improve the practicability and timeliness of data.

关键词： Web crawler Knowledge map data encyclopedia Full text search

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Key Technology and Application of Customer data Security Prevention and Control in Public Service Enterprises 10th

Key Technology and Application of Customer Data Security Pre...

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10th international conference on Computer Engineering and Networks, CENet 2020

作者： Huang, Xiuli Shi, Congcong Guo, Qian Gao, Xianzhou Yu, Pengfei State Grid Key Laboratory of Information and Network Security Global Energy Interconnection Research Institute Co. Ltd. Nanjing210003 China

ISBN: (纸本)9789811584619

As the value of the big data is revealed, the problem of security prevention and control of customer service data is highlighted. Once the leakage of sensitive customer information will cause serious legal consequences. At present, State Grid Corporation has effectively resisted the risk of data collection, storage, and transmission through internal and external network isolation and data encryption. However, at the data application level, due to frequent data sharing and business collaboration, new risks of leakage continue to emerge in data mining, data interaction between systems, terminal data access, etc. This article first analyzes the risks faced by data security in terminal data access, cross-domain data transfer, and open data sharing. Then, it proposes terminal data access behavior management and control technology, data cross-domain transfer security interaction technology, and data differentiated privacy protection technology in open sharing. Finally, t on the basis of technical research, the core equipment of data protection was developed and tested, and verified the effectiveness of the technology in practice. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sensitive data

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Event Detection Based on Semantic Terms from Social data Stream 6th

Event Detection Based on Semantic Terms from Social Data Str...

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6th international conference on Advanced Machine Learning technologies and Applications, AMLTA 2021

作者： Gamal, Ahmed Abdelkader, Hatem Abdelwahab, Amira Faculty of Computers and Information Menofia University Shibin Al Kawm Egypt College of Computer Science and Information Technology King Faisal University Al Hofuf Saudi Arabia

ISBN: (纸本)9783030697167

Event detection is an interesting area of study that has taken a great deal of attention throughout the last years due to the extensive social media data availability. Problems with event detection have been explored in various social media sources such as Twitter, Flickr, YouTube, and Facebook. The event Detection process includes many challenges, including processing huge volumes of information and high noise levels. The event depends on many basic determinants of which are what, where, and when. Tweets that express a real-world event include semantic terms that match these determinants. The paper presents an incremental approach to clustering based on these determinants and semantic terms that express an event to detect social media events, especially from Twitter. The event detection framework includes three main components: pre-processing, on-line clustering, and event search and detection modules. By implementing some experiments on the proposed framework using a set of large and real-world data, it becomes clear to us that the results are positive. The framework detects events effectively from Twitter compared to other approaches. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Supervised Machine Learning Model for Accent Recognition in English Speech Using Sequential MFCC Features

Supervised Machine Learning Model for Accent Recognition in ...

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international conference on Artificial Intelligence and data Engineering, AIDE 2019

作者： Honnavalli, Dweepa Shylaja, S.S. Department of Computer Science PES University Bangalore India

ISBN: (纸本)9789811535130

Human–machine interfaces are rapidly evolving. They are moving from the traditional methods of input like keyboard and mouse to modern methods like gestures and voice. It is imperative to improve voice recognition and response since there is a growing market of technologies, world-wide, that use this interface. Majority of English speakers around the world have accents which are not exposed to speech recognition systems on a greater scale. In order to bridge the comprehension gap between these systems and the users, the systems need to be tuned according to the accent of the user. Accent classification is an important feature that can be used to increase the accuracy of comprehension of speech recognition systems. This paper recognizes Indian and American English speakers and distinguishes them based on their accents by constructing sequential MFCC features from the frames of the audio sample, oversampling the under-represented data and employing supervised learning techniques. The accuracies of these techniques reach a maximum of 95% with an average of 76%. Neural networks emerge as the top classifier and perform the best in terms of evaluation metrics. The results gleaned indicate that concatenating MFCC features sequentially and applying an apposite supervised learning technique on the data provide a good solution to the problem of detecting and classifying accents. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Supervised learning

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DBMS, NoSQL and Securing data: The relationship and the recommendation

DBMS, NoSQL and Securing Data: The relationship and the reco...

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2020 international conference on Innovation and Intelligence for Informatics, computing and technologies, 3ICT 2020

作者： Abahussain, Omar Alqaddoumi, Abdulla University of Bahrain Department of Computer Science Sakhir Bahrain

ISBN: (纸本)9781728196732

In modern days, database systems usage keep increasing where they have become an essential part of our life in storing records. As technology advances, databases receive updates or new improved methods that, alongside it, risks emerge and increase if left unresolved or unaware of such ongoing risks. Such risks would lead to data availability, integrity, and confidentiality to be broken and leaked out into the hands of cybercriminals. This paper aims to show two types of databases, analyze their security, and propose a solution to securing and maintaining the availability, integrity, and confidentiality of the data stored in the database. © 2020 IEEE.

关键词： database systems

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Analysis of the Integration of 5G with Artificial Intelligence

Analysis of the Integration of 5G with Artificial Intelligen...

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international conference on Futuristic technologies (INCOFT)

作者： Preetam Singh Gaur Deependra Rastogi Department of Life & Basic Sciences School of Life & Basic Sciences Jaipur National University Jaipur India Department of Computer Science and Engineering Galgotias University Greater Noida Uttar Pradesh India

All as it proceeds to create and is progressively executed in a rising number of settings, this innovation will ultimately develop to where it will cause a change in outlook, moving away from the conventional traffic administration worldview and toward one that is established on a model of a natural chain that considers its variables. Integration of 5G innovation into modern areas will bring about a critical expansion in the productivity of modern result and will rush the course of carefully changing and redesigning modern areas.. The integration of 5G and man-made intelligence innovation will reshape the future instruction data climate by achieving incendiary mechanical progressions and instructive application situations. This will bring about a remade future instruction data climate. The expansion in the quantity of remote correspondences networks has gotten the way for the advancement free from state of the art advances like driverless cars, automated airplane frameworks, automated mechanical technology, the Web of Things, and augmented reality. The fifth era of remote correspondence networks is promising to convey immense information speeds, incredibly low inactivity, and exceptional constancy, which are all necessities for the advancements that require them. These mechanical headways are: (5G) Right now in the improvement of 5G advances, it is bounteously clear that there are a considerable number of troublesome and complex hubs that should be tackled. General information to take advantage of the innovations that are as of now open, an enormous number of enhancement methods and the consolidation of helper frameworks are required. The execution of artificial intelligence gives a significant open door to the goal of genuinely exceptionally confounded setup issues. It is a familiar way of thinking that man-made intelligence based approaches will be a crucial consider the shrewd circulation of assets across base stations in 5G networks, or, to put it another way, i

关键词： Productivity Technological innovation Base stations 5G mobile communication Autonomous automobiles Quality of experience Artificial intelligence

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Feedback Vocal Rehabilitation Software Applied to Mobile Devices for Maximum Phonation Time 6th

Feedback Vocal Rehabilitation Software Applied to Mobile Dev...

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6th international conference on Advanced Machine Learning technologies and Applications, AMLTA 2021

作者： Lin, Jia-Yi Huang, Yu-Chi Horng, Gwo-Jiun Hsu, Chien-Cin Chen, Chao-Chun Department of Computer Science and Information Engineering Institute of Manufacturing Information and Systems National Cheng Kung University Tainan Taiwan Graduate Institute of Audiology and Speech Therapy National Kaohsiung Normal University Kaohsiung Taiwan Department of Computer Science and Information Engineering Southern Taiwan University of Science and Technology Tainan Taiwan Chi Mei Hospital Tainan Taiwan

ISBN: (纸本)9783030697167

The key to the maximum phonation time (MPT) is how much lung capacity you have. If the MPT is too short, one cannot cut the sentences inappropriate time and lead to communication difficulties. However, there is no research on the effect of using feedback software for vocal rehabilitation in the past, especially for those who cannot increase their vital capacity through exercise. Therefore, we designed two tests for the experiment in our study. First, using mobile devices to collect MPT and Intensity Level (IL) data in a quiet space of 40 adults whose cognitive status is normal, and analyzing their characteristic changes. Then, we use the mobile device to perform MPT feedback rehabilitation and collect two characteristic data again. The purpose of our study is to understand the effects of using feedback vocal rehabilitation software. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： data acquisition

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