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检索条件"任意字段=7th International Conference on Extending Database Technology"

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the Essential Factors of Web 3.0 Affecting 7 Layers of Decentralized Web in Business or Industry 7

The Essential Factors of Web 3.0 Affecting 7 Layers of Decen...

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7th international conference on Information Management and technology, ICIMTech 2022

作者： Vernando, Calvin Hitojo, Hendry Steven, Randy Meyliana Surjandy School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

the new web 3.0 or Web3 is a distributed web technology mainly operated by decentralized blockchain and Artificial Intelligence. the Web 3.0 technologies bring the changes in industry 4.0 especially the business sector. the contribution of this paper to discuss the new web 3.0 (not semantic web) and to explore the essential factors of the new Web 3.0 technologies in business or industry based on 7 layers of decentralized web. the Layers have users, interface, application, execution, settlement, data, and social as main components. the concept 7 layers of decentralized web was introduced by Polynya. this research was carried out using SLR (Systematic Literature Review) methodology to identify certain factors by analyzing high quality papers in the Scopus database. We found 21 essential factors that are Distributed, Real-time, Community, Culture, Productivity, Efficiency, Decentralized, Trust, Security, Performance, Reliability, Scalability, Transparency, Authenticity, Cost Effective, Communication, Telecommunication, Social Network, Use Case, and Business Simulation. We also present opportunities and challenges of the 21 factors in business and Industry. © 2022 IEEE.

关键词： Blockchain

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7th international conference on Science, technology and Innovation for Society, CITIS 2021

7th International Conference on Science, Technology and Inno...

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7th international conference on Science, technology and Innovation for Society, CITIS 2021

ISBN: (纸本)9789811641251

the proceedings contain 68 papers. the special focus in this conference is on Science, technology and Innovation for Society. the topics include: Combining Escape Rooms and Google Forms to Reinforce Python Programming Learning;model of State Spaces for Estimating the Dynamic Origin–Destination Matrix for a Public Transport Network by Applying the Kalman Filter;multi-objective Logistic Regression for Anomaly Detection in Water Distribution Systems;what Affects Household Electricity Demand in Ecuador: Using Analytical Hierarchy Process to Read Homeowners’ Perception;preliminary Studies of Performance and Lipid Profiles of Ecuadorian P. volubilis L. as Contribution to Agricultural Innovation;toxicological Evaluation of Essential Oil and Ethanolic Extracts of Ruta graveolens in Artemia salina;physicochemical Characteristics and Antioxidant Capacity of Yellow and Orange Andean Floral Species;dynamics of Nitrates and Phosphates in Chone Multipurpose Dam, Ecuador;the Effect of Ascorbic and Citric Acids in the in Vitro Establishment of Solanum betaceum to Prevent Phenolic Oxidation;data Augmentation Techniques Applied to Improve a Vitiligo database;the Technification of Irrigation as a Strategy of Community Resilience. Case Study: Pisque River Basin, Ecuador;limitations and Potentialities of Organic or Non-conventional Milk Production in Ecuador;I + PD Temperature Controller Tuned for Ant Colony Optimization (ACO) on an ARM Platform;analyzing Trends in Academic Papers about Sustainable Development and Smart Tourism using Text Mining;design and Evaluation of a Distributed Architecture for GeoSparkSim;toward a Social Media Emergency Events Detection Based on Supervised Learning;exploratory Study of Physic Informed Deep Learning Applied to a Step-Pool for Different Flow Magnitudes.

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Data Acquisition System for Web-based Multi-modal Data Repository 7

Data Acquisition System for Web-based Multi-modal Data Repos...

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7th IEEE international conference on Bio Signals, Images and Instrumentation, ICBSII 2021

作者： Rushambwa, Munyaradzi Charles Mukherjee, Anirban Maity, Maitreya Palaniappan, Rajkumar Vijean, Vikneswaran Ghulam Nabi, Fizza Harare Institute of Technology Electronic Engineering Harare Zimbabwe Indian Institute of Technology-KGP Electrical Engineering Kharagpur India Ama International University College of Engineering Department of Mechatronics Engineering Salmabad Bahrain University of Malaysia Perlis Mechatronic Engineering Perlis Malaysia Lahore Pakistan

ISBN: (纸本)9781665441261

the multimodal medical data with annotation helps to build different automated algorithms. Each reported work has used a specific disease database and developed a CAD based on the considered database. therefore, the availability and quality of medical database play the most crucial role in developing any CAD. However, it has been observed that most of the reported studies used public database (created by foreign universities/centers) or private database. Unfortunately, the availability of a national medical database in India is negligible. However, development of such medical database is possible. Such medical database can encourage new research activity and help a large research community. the proposed study focuses on developing an online public medical multimodal database platform. Here, the data acquisition software is build for collecting various information. © 2021 IEEE.

关键词： database systems

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Sentiment Analysis of Nationwide Lockdown amid COVID 19: Evidence from Pakistan 7

Sentiment Analysis of Nationwide Lockdown amid COVID 19: Evi...

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7th IEEE international conference on Information technology and Digital Applications, ICITDA 2022

作者： Qazi, Atika Qazi, Javaria Naseer, Khulla Zeeshan, Muhammad Khan, BaseerAhmed Dey, Samrat Kumar Universiti Brunei Darussalam Centre for Lifelong Learning Brunei Quaid-i-Azam University Faculty of Biological Sciences Islamabad Pakistan Maroof International Hospital Islamabad Pakistan Hbs Medical & Dental College Department of Medical Education & Research Islamabad Pakistan Gazipur Bangladesh

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

A growing number of people are using tweets about the recent coronavirus epidemic of COVID-19 as a dataset to determine how worried people are in different parts of the world. this study attempts to uncover the key sentiments expressed by Twitter users regarding the COVID-19 epidemic by categorizing the tweets into positive and negative sentiments utilizing several resources (such as the Twitter search application programming interface (API), the Tweepy Python library, and the CSV excel database), as well as some predefined search terms ('#LockdownPakistan.'). We extracted the text of English language tweets from 28th March-1st May 2020. We have performed the sentiment analysis and classified the tweets in a binary class of positive and negative. Further, we used the word frequencies of single (unigrams), double (bigrams), and three words to examine the gathered tweets (tri-grams). According to our data, the majority of tweets express a positive attitude, with the word for lockdown COVID-19 appearing frequently. When looking at frequency analysis, the word 'family and time' stood out among the other words, which suggests that tweets were mostly optimistic and sentiments of defeating SARS-COV-2 prevail. People are determined to spend the lockdown in a good way. However, a few of the negative tweets, nevertheless, should serve as a warning for healthcare officials to make appropriate arrangements. Public health crisis responses are today complicated and highly synchronized both offline and online. Social media is a significant medium that gives people the chance to communicate with healthcare authorities directly. © 2022 IEEE.

关键词： COVID-19

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Optimization Method of database Memory Sorting for Software and Hardware Application Integration 23

Optimization Method of Database Memory Sorting for Software ...

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Proceedings of the 2023 7th international conference on Electronic Information technology and Computer Engineering

作者： Yang Sun Cuiling Zheng College of Computer Engineering Jimei University China

ISBN: (纸本)9798400708305

In order to improve the memory capacity of the software and hardware application integration database, it is necessary to optimize the memory sorting. In this paper, database storage space is optimized by semantic ontology feature mapping method, so as to establish the database memory sorting control model; combined with fuzzy degree detection and resource information optimization scheduling method, the memory structure partition design of software and hardware application integration database is carried out, and through the grid partition block storage protocol is design to achieve the optimization of memory sorting of hardware and software application integrated database. the simulation results show that this method has better adaptability for the software and hardware application integration database memory sorting, improves the storage space of the database and reduces the storage cost.

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Research on the English teaching model of integrating corpus database and its application

Research on the English teaching model of integrating corpus...

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7th international conference on Vision, Image and Signal Processing (ICVISP 2023)

作者： Z. Yang Foundation Department Liaoning Vocational University of Technology Jinzhou Liaoning People's Republic of China

Vocabulary, as the foundation of the English learning process, plays an important role in listening, speaking and writing English. the study utilizes corpus retrieval, data-driven learning and statistical methods to design a corpus-based vocabulary teaching model and compare and test it with the traditional vocabulary teaching model, using two classes of students in a high school for the experimental design and test comparison. the experimental results yielded more obvious changes in the quantity and quality of vocabulary output in the experimental class, whose results on vocabulary density, complexity and variability were 1.27, 2.47 and 5.35, respectively, while the results on vocabulary density, complexity and variability in the control class were 0.95, 0.28 and 2.22, respectively, thus demonstrating the superiority of the corpus-based vocabulary teaching model, and providing a future technical references for the classroom approach to English language teaching.

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Performance Analysis of Scalable Transactions in Distributed Data Store 7th

Performance Analysis of Scalable Transactions in Distributed...

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7th international conference on Computing in Engineering and technology, ICCET 2022

作者： Bharati, R.D. Attar, V.Z. College of Engineering Pune Pune India

ISBN: (纸本)9789811927188

Data partitioning has become a practical method for scalable transaction selection due to the advent of numerous distributed system frameworks. We provide a scalable data partitioning technique that can recognize distributed transactions from empirical facts and use it as a crucial factor in data partitioning. On distributed database systems, we deal with the issue of developing scalable transaction management techniques for the web application. Using the standard benchmark, we evaluate various strategies for supporting scalability. the ideas discussed in this research can be used for web applications. We show that distributed transactions can be handled with the assurances of ACID properties in a scalable manner. © 2022, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Distributed database systems

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Development of Multilingual Speech database for Speaker Recognition in Indian Languages 7

Development of Multilingual Speech Database for Speaker Reco...

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7th international conference on Wireless Communications, Signal Processing and Networking, WiSPNET 2022

作者： Bharath, K.P. Rajesh Kumar, M. School of Electronics Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9781665496483

In this paper, we describe the collection of speech samples to develop a database for speaker recognition in the Indian scenario in the office environment and named VIT-Indian Language Speech Corpus (VIT-ILSC) speech database. Presently, we developed the Phase -1 database of speech samples from 50 speakers. the speech samples were collected in the office environment. Most of the speech samples collected are in English and other Indian languages in reading style, using two digital voice recorders. this work aims to develop a speech corpus database for a speaker recognition system in Indian languages, including English. Traditional Mel-frequency cepstral coefficients (MFCC) and Gaussian Mixture Model (GMM) was used to evaluate the collected phase-1 database. the phase-1 database has been evaluated on a speaker verification system. We considered both clean and noise backgrounds for initial studies and showed the impact of mismatch in training and testing samples. © 2022 IEEE.

关键词： database systems

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Scaling Machine Learning with a Ring-based Distributed Framework 7

Scaling Machine Learning with a Ring-based Distributed Frame...

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7th international conference on Computer Science and Artificial Intelligence, CSAI 2023

作者： Zhao, Kankan Leng, Youfang Zhang, Hui Shandong Inspur Database Technology Co. Ltd. Shandong Jinan China

ISBN: (纸本)9798400708688

In centralized distributed machine learning systems, communication overhead between servers and computing nodes has always been an important issue affecting the training efficiency. Although existing research has proposed various measures to reduce communication overhead between nodes in parameter server frameworks, the communication pressure and overhead inherited from centralized architectures are still significant. To address the above issue, this paper proposes a ring-based parameter server framework that is distinct from node division and model training mechanism in the standard p/s framework. the ring-based architecture cancels the global model stored on the server side, and each computing node stores a local copy of the model. During model training, computing nodes can asynchronously train local models based on local or remote training data. After all nodes finish learning, the ensemble learning method can predict test data based on all local models. To avoid the negative impact of remote data reading on model training efficiency, a producer-consumer data reading strategy is proposed. this strategy can reduce data reading overhead in a pipeline manner. To make rational use of the input and output bandwidths of all nodes, a circular data scheduling mechanism is proposed. At any given time, this mechanism ensures each node has at most one input stream and one output stream, thereby dispersing communication pressure. the experimental results show that the proposed distributed architecture achieves significantly better performance (1.7%-2.1% RMSE) than the state-of-the-art baselines and also achieves a 2.2x-3.4x speedup when reaching a comparable RMSE performance. © 2023 ACM.

关键词： Machine learning

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CSR+: A Scalable Efficient CoSimRank Search Algorithm with Multi-Source Queries on Massive Graphs 27

CSR+: A Scalable Efficient CoSimRank Search Algorithm with M...

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27th international conference on extending database technology, EDBT 2024

作者： Zhang, Maoyin Yu, Weiren Nanjing University of Sci. and Tech. Jiangsu Nanjing China Warwick University CoventryCV4 7AL United Kingdom

ISBN: (纸本)9783893180943

CoSimRank is a compelling model that iteratively follows the SimRank-like notion that "two items (nodes) are deemed similar if their in-neighbours are similar". However, the existing CoSimRank algorithm [6] is only efficient in single-source search, and is rather sluggish for multi-source queries due to repeated calculations across queries. Another algorithm [4] involves cost-inhibitive tensor products in preprocessing, rendering it unscalable on big graphs. In this paper, we propose CSR+, a fast efficient multi-source CoSimRank algorithm that scales well on billion-edge graphs. First, we analyse the pros and cons of [4] and propose a four-stage optimisation scheme to eliminate costly graph tensor products and numerous repetitive similarity calculations while addressing each of the deficiencies in [4]. Next, we present an efficient algorithm, CSR+, for multi-source CoSimRank search, which significantly reduces the computation time from O(r4n2) to O(r(m + n(r + |Q|))) and memory from O(r2n2) to O(rn) on a graph of n nodes and m edges, without compromising the accuracy of [4], where r ( n) is the low rank of singular value decomposition. Experiments on various real datasets validate that CSR+ is 1—4 orders of magnitude faster than its rivals for multi-source queries while scaling on large graphs. © 2024 Copyright held by the owner/author(s).

关键词： Singular value decomposition

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