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检索条件"任意字段=2023 International Conference on Algorithms, Computing and Data Processing, ACDP 2023"

共 6956 条记录，以下是921-930 订阅

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Geolocation Using Social Media data as Language Identification and data Mining Strategies

Geolocation Using Social Media Data as Language Identificati...

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2023 international conference on Applied Physics and computing, ICAPC 2023

作者： Su, Jian Dongying Vocational Institute Shandong Dongying China

ISBN: (纸本)9798350359244

An interdisciplinary inquiry into the complex dynamics of social media material is presented in this paper. Using modern data mining techniques, geolocation analysis, and Natural Language processing (NLP) tools, this work attempts to decipher the intricate interactions between linguistic and spatial dimensions in the digital realm. The all-inclusive methodology incorporates novel data mining techniques, advances in language identification using natural language processing, and improved geolocation accuracy. Combining explicit and implicit location clues, the geolocation analysis shows promising results in reliably detecting user locations. Benchmarking against ground truth data is incorporated into the study to demonstrate the accuracy and consistency of the geolocation algorithm on a variety of datasets. The proper use of geolocation data is emphasised by ethical issues, such as privacy protection, which guarantee openness and user confidence. Applications in public health, marketing, and cybersecurity are developing as a result of the research's insightful discoveries on user behaviour, preferences, and trends. Along with addressing present issues, the study paves the way for future developments in responsible data use, real-time application exploration, and algorithm refinement. To sum up, this study offers a nuanced viewpoint to the developing field of social media analytics, opening the door to more profound understanding and creative uses in the digital era. © 2023 IEEE.

关键词： data mining

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Hyper Lattice Structure for data Cube Computation

Hyper Lattice Structure for Data Cube Computation

引用

international conference on data Analytics and Management, ICDAM 2022

作者： Phogat, Ajay Kumar Mann, Suman Maharaja Surajmal Institute of Technology GGSIPU New Delhi110058 India

ISBN: (纸本)9789811976148

In the current business scenario, a quick and accurate response is required for business decisions. data warehouse consists of huge volumes of data repositories. This information is utilized to develop insights for decision-making queries on data, besides it takes a long time to process, resulting in longer response times. This response time must be lowered in order to make effective and efficient decisions. The computation of data cubes is a momentous task in data warehouse design. Pre-computation may significantly reduce the response time and also improve online analytical processing efficiency by computing partially or all or part of a data cube. However, such computing is difficult since it may need a substantial amount of time and storage space. Many authors have suggested algorithms for efficient data cube computation for reducing the time computation and storage cost. In this paper, we have proposed a framework that uses a heuristic approach for data cube computation in the hyper lattice structure. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： data warehouses

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international conference on Applied Intelligence and Sustainable computing, ICAISC 2023

International Conference on Applied Intelligence and Sustain...

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1st IEEE international conference on Applied Intelligence and Sustainable computing, ICAISC 2023

ISBN: (纸本)9798350323795

The proceedings contain 245 papers. The topics discussed include: a comprehensive analysis on deep learning based image retrieval;research on the influences of network characteristics of digital economy industry based on big data intelligent analysis algorithm;plant leaf disease classification using modified SVM with post processing techniques;a study of logistics teaching based on multimodal information input;feature extraction strategy of translated text based on neural network;localization recommendation algorithm of online translation course based on deep neural network;performance analysis of load balancing mechanism in cloud computing;pending interest table control management with optimal forwarder selection in named data network;big data analytics in small and medium enterprises;investigation and analyses of data processing through sports using scripting language: a novel paradigm;application of artificial neural network technology in electricity marketing;an accurate detection of drowsiness using a graph-based neural network;investigation on multi-objective optimization system of wastewater treatment process based on artificial intelligence;and ensemble machine learning techniques for pancreatic cancer detection.

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international conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings

International Conference on Sustainable Communication Networ...

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2023 international conference on Sustainable Communication Networks and Application, ICSCNA 2023

ISBN: (纸本)9798350313987

The proceedings contain 284 papers. The topics discussed include: a dynamic anomaly detection approach for fault detection on fire alarm system based on fuzzy-PSO-CNN approach;enhanced skin cancer prediction with analysis using machine learning algorithms;comparison study of different neural network models for assessing employability skills of IT graduates;performance evaluation of machine learning algorithms for prediction of cardiac failure;design of improvised DCM-based tunable true random number generator;design and implementation of piezoelectric shoe;prediction and processing of environment geography images using deep learning techniques;human activity recognition in video surveillance using long-term recurrent convolutional network;and energy-efficient task offloading for edge computing-based smart grid networks using human urbanization.

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Design of data Information processing System Based on Genetic Algorithm and BIM 2

Design of Data Information Processing System Based on Geneti...

引用

2nd international conference on 3D Immersion, Interaction and Multi-Sensory Experiences, ICDIIME 2023

作者： Pan, Juan Chongqing College of Architecture and Technology Chongqing China

ISBN: (纸本)9798350323818

In order to solve the current challenges of data collection, analysis and modelling in building construction, a set of data information processing system for building assembly construction based on BIM technology is established by combining BIM technology and genetic algorithm. Based on this, a multi-objective engineering scheduling optimization model with dual objectives of cost and resources is established, and genetic algorithm is used to solve the optimal engineering scheduling time and the start time of each process. Finally, the validity and correctness of the proposed theory and method will be verified by combining with engineering examples, so as to provide scientific and reasonable solutions for engineering construction, promote the application of BIM technology in engineering construction and enhance the benefits of engineering construction. © 2023 IEEE.

关键词： Genetic algorithms

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Using Edge-based Deep Learning Model for Early Detection of Cancer 31

Using Edge-based Deep Learning Model for Early Detection of ...

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31st Euromicro international conference on Parallel, Distributed and Network-Based processing, PDP 2023

作者： Barillaro, Luca Agapito, Giuseppe Cannataro, Mario University 'Magna Graecia' of Catanzaro Dept. of Surgical and Medical Sciences and Data Analytics Research Center Catanzaro88100 Italy University 'Magna Graecia' of Catanzaro Dept. of Law Economics and Social Sciences and Data Analytics Research Center Catanzaro88100 Italy

ISBN: (纸本)9798350337631

Cancer is one of the most frequent causes of death in the world. Usually, cancer can be easily diagnosed if characteristic symptoms occur. However, many people who are suffering from cancer have no symptoms. Early diagnosis of tumors is essential to contrast their progression, helping to define more effective treatments to provide long-term survival. Early cancer detection is effective if sensible data can be investigated through high-performance technologies like edge computing. Edge computing is a new paradigm for analyzing data as close to the source as possible, avoiding exporting them outside. Hence, edge-based deep learning models can be applied to improve early cancer detection. This paper provides an use case of a classification task on tumor-related data based on the famous UCI machine learning data sets repository using a deep learning approach based on edge computing. In addition, the manuscript provides an overview of the edge computing paradigm, highlighting its advantages and usability. We also described a small experiment with real tumor data to characterize performance considerations. Moreover, the presented model can be used with different data types, such as images, EGC, and ECC signals. © 2023 IEEE.

关键词： Tumors

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Certain Investigations on Cognitive based Movie Recommendation system using Pairwise Cosine Similarity 9

Certain Investigations on Cognitive based Movie Recommendati...

引用

9th international conference on Advanced computing and Communication Systems, ICACCS 2023

作者： Sumathi, S. Madhumitha, S. Sushma, R. Suriya, M. Subitsha, M. Swetha, S. Sri Eshwar College of Engineering Department of Artificial Intelligence and Data Science Coimbatore India Sri Eshwar College of Engineering Artificial Intelligence and Data Science Coimbatore India

ISBN: (纸本)9798350397376

The Internet serves as a major source in various sectors to communicate and share data. It is being used by every individual across the world for several purposes. The main objective of the recommender system is to provide users with suitable products and information. The movie recommendation system also helps in providing customized decisions to the user, thus improving the experience of customer or user. Content-based filtering manipulates item attributes to suggest other items that are relevant to user likes, this suggestion is made using past actions of customers or users. Cosine Similarity is an evaluation metric that helps in finding how similar the items are regardless of their dimensions. The proposed study, furnish users with suggestions that rest on the prevalence and category of a movie. Content based recommendation system is built using cosine similarity. The movie recommendation system has its separate algorithms for making suggestions by examining users' past data. Many attributes are considered like rating of each movie, name of the director and genre of the film. The system make recommendation by considering one attribute or mixture of attributes. For the proposed system, two different datasets used namely, the credits dataset and the movie dataset. The analysis of data is done with help of Python. © 2023 IEEE.

关键词： Python

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data Engineering Challenges in AI automation 6

Data Engineering Challenges in AI automation

引用

6th international conference on computing, Electronics and Communications Engineering, iCCECE 2023

作者： Reddy, Deexith Dallas TX United States

ISBN: (纸本)9798350340921

Artificial Intelligence (AI) systems have seen a meteoric rise in adoption, permeating across diverse sectors such as healthcare, finance, and e-commerce. The next step in the evolution of the practical use of AI is the automation of these systems. Since these systems hinge largely on the quality, volume, and careful management of data for training, optimization, and validation of data science models, the promise of AI automation hinges significantly on the ability to efficiently handle data ingestion, ensure real-Time processing, and respond swiftly to changes in *** is a requirement of a multi-faceted approach in terms of data engineering to help practitioners implement automated AI. The need for robust data engineering practices that ensure scalability, efficiency, and reliability in AI applications and their automation is evident. Comprehensive investigations of the impact of these practices on the automation of AI are required to create future-proof, reliable AI *** paper will highlight some areas of data engineering that are important for automation of AI, the challenges they pose and the impact they have on performance of AI systems. There is a solution section for each problem that gives the scope of automation and human involvement required along with the tools that are currently being used. © 2023 IEEE.

关键词： Automation

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Secure Auditing with Encrypted Trace Logs in Multi-Cloud Storage Management 1

Secure Auditing with Encrypted Trace Logs in Multi-Cloud Sto...

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1st IEEE international conference on Ambient Intelligence, Knowledge Informatics and Industrial Electronics, AIKIIE 2023

作者： Gnanasudharsan, A. Meena, P. Guru Raghavendra, S. Sreevarshan, S. Rithika, S.R. Sri Sairam Engineering College Department of Electronics and Communication Engineering Chennai India

ISBN: (纸本)9798350316469

Cloud computing revolutionizes the way resources are utilized, offering a platform where they can be dynamically allocated based on demand. This on-the-fly data processing and storage capability has led various providers to offer both free and premium storage solutions. However, with a multitude of providers in the market, accessing data scattered across them can be cumbersome. Hence, the emergence of multi-cloud storage management tools, which provide a unified interface for users to seamlessly access data without juggling between multiple providers. Though authenticated access safeguards data, maintaining its integrity requires oversight of user activities. This calls for the implementation of a Trace Log that meticulously records each action. Such logs, while crucial for auditing, are sensitive and can be vulnerable. To bolster their security, encryption techniques can be implemented, using unique user-specific keys. This not only enhances the log's security but also ensures controlled, authenticated access. A proposal for a robust, secure, and efficient system to manage and monitor data across multiple cloud platforms. © 2023 IEEE.

关键词： Authentication Cloud computing data processing Encryption Multi-Cloud Storage Management Streamline Trace Log

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Architecture design of energy Internet regulation system based on cloud-edge collaboration 6

Architecture design of energy Internet regulation system bas...

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6th international conference on Renewable Energy and Power Engineering (REPE)

作者： Xu, Lei Zhang, Kaiyue Han, Xuehua Huang, Huang Ren, Hehe Wang, Qiang Jiang, Ning Coal Ind Co Ltd Jinan Coal Technol Res Inst Jinan Peoples R China Beijing Inst Petrochem Technol Beijing Peoples R China Qingdao Inst Ind Software Qingdao Peoples R China

ISBN: (纸本)9798350306194;9798350306187

With the emergence of a large number of energy prosumer units, the edge side of the regulation system has become an intelligent computing unit, which has transformed the energy Internet control mode from centralized to decentralized centralized collaborative operation. Combined with the theory of cloud-edge collaborative computing, this paper analyzes the data transmission characteristics of the energy Internet regulation system, and designs the regulation architecture of cloud-edge collaboration, including information collection, edge computing, core computing, management control, business applications and security auxiliary layers. According to the real-time requirements of the regulation and control business, the energy Internet regulation business processing process is designed, and the typical business scenarios of the energy Internet are sorted out and analyzed. The simulation results show that the real-time data transmission of the energy Internet regulation system based on cloud-edge collaboration has been greatly improved, which can ensure the operation reliability of the new energy Internet service scenario.

关键词： dispatch and control cloud-edge collaboration business scenarios data transmission

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