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检索条件"任意字段=3rd International Conference on Computing and Data Science, CONF-CDS 2021"

共 909 条记录，以下是181-190 订阅

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A Survey on Privacy-Preserving data Publishing Methods and Models in Relational Electronic Health Records 1

引用

3rd international conference on Sustainable Advanced computing, ICSAC 2021

作者： Jayapradha, J. Prakash, M. Department of Computing Technologies SRM Institute of Science and Technology Tamil Nadu Kattankulathur Chengalpattu603203 India Department of Data Science and Business Systems SRM Institute of Science and Technology Tamil Nadu Kattankulathur Chengalpattu603203 India

ISBN: (数字)9789811690129

ISBN: (纸本)9789811690112

The collections of various digital information from corporations, public sectors, private sectors, and individuals have formed remarkable opportunities for analysis and decision-making. The electronic health record is highly constructive for various study purposes;however, it should be carried in a way that preserves the identity and privacy of the patients. Due to the digital transformation, the flow of data increases that lead to the need for big data. Protecting privacy cannot be straightforward as there are several privacy threats such as membership disclosure, identity disclosure, and attribute disclosure. The privacy methods such as generalization, suppression, pseudonymization, bucketization, slicing are illustrated with examples. The study focused on various privacy models such as k-anonymity, l-diversity, t-closeness, differential privacy, and cryptographic technique. The models are discussed with the sample dataset and workflow. The paper has discussed the security and privacy concerns on data publishing, the need for big data scope, an overview of threats, samples, privacy methods, models, and challenges in privacy-preserving data publishing. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Records management

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Ensemble of AES - RSA Cryptographic Model for Securing Sensitive Laptop data 3

Ensemble of AES - RSA Cryptographic Model for Securing Sensi...

引用

3rd international conference on Inventive Research in computing Applications, ICIRCA 2021

作者： Prakash, Sidharth S. Visakha, K. School of Engineering Cochin University of Science and Technology Division of Information Technology Kochi India

ISBN: (纸本)9780738146270

Laptops have become the workstation for a majority of people during the modern days. Many IT firms have migrated to laptops so that the employees have the necessary flexibility to work even from home due to unprecedented havocs like natural disasters and pandemics. Hence it is vital to safe guard the sensitive client related data present inside the laptop during theft. File system encryption is the widely adopted method to achieve the intended data security. But having the presence of decryption key within the stolen laptop is a loop hole for hardware experts to retrieve the sensitive contents. Hence our work proposes an ensemble of AES and RSA cryptographic model which ensures that the file encryption key is distributed to a remote server and is only accessible via an android phone request from an authorized user. © 2021 IEEE.

关键词： Cryptography

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Overview the Design Challenges of Phase-Frequency Detector for Clock and data Recovery Circuit 3rd

Overview the Design Challenges of Phase-Frequency Detector f...

引用

3rd international conference on Communication, Devices and computing, ICCDC 2021

作者： Maiti, Madhusudan Jana, Sayan Patra, Shuvoshree Saha, Subhas Chandra Department of Electronics and Communication Engineering C.V. Raman Global University Bidyanagar Odisha Mahura Janla Bhubaneswar752054 India Department of Pure and Applied Science Midnapore City College West Bengal Midnapore721129 India Departments of Electronics Vidyasagar University West Bengal Midnapore721102 India

ISBN: (纸本)9789811691539

In modern communication systems phase-frequency detector plays an important role. An overview of design challenges for clock and data recovery circuits of phase-frequency detectors is presented here. Investigations are made keeping our focus on critical design issues of different phase-frequency detectors with advantages and limitations. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Timing circuits

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An Incremental Load Balancing Algorithm in Federated Cloud Environment 3rd

An Incremental Load Balancing Algorithm in Federated Cloud E...

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3rd international conference on data, Engineering, and Applications, IDEA 2021

作者： Patrick, Nzanzu Vingi Misra, Sanjay Adetiba, Emmanuel Agrawal, Akshat Covenant Applied Informatics and Communication African Center of Excellence Covenant University Ogun State Ota Nigeria Department of Computer Science and Communication Østfold University College Halden Norway Amity University Haryana Gurgaon India

ISBN: (纸本)9789811946868

With the development of cloud computing, load balancing issues have substantially become prominent, which is of concern as well to the industry as to academia. Load balancing contributes to a high degree of customer satisfaction and the use of resources in the cloud by verifying an accurate, secure, and equitable allocation of all computing resources. In this paper, we review the research progress on load balancing issues from the perspective of several incremental and dynamic algorithms in federated cloud computing. First, we present some obstacles to load balancing algorithms in cloud computing and suggest a corresponding incremental algorithm for load balancing in a federated cloud. Last, we offer current challenges and highlight possible future directions for research in this field. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cloud computing

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Research on Parameter Verification of Power Grid Equipment Based on SOA and NPOI 3

Research on Parameter Verification of Power Grid Equipment B...

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3rd international conference on Smart Power and Internet Energy Systems (SPIES) - Towards A Sustainable and Affordable Energy Transition

作者： Wei, Hongbo He, Yini Liu, Xinran Bin, Can Gong, Shu Jiang, Xiongfeng Guangxi Power Grid Co Ltd Power Dispatch & Control Ctr Nanning Peoples R China

ISBN: (纸本)9780738146331

A service-oriented architecture (SOA) power grid equipment parameter verification system is proposed to solve the problem of long time consumption and low accuracy of parameter verification caused by the inconsistent naming format of equipment in different systems of the power grid. The system adopts the SOA architecture, decouples the parameter verification system into four parts: data import, analysis, check, and output, and separately encapsulates it as a Web service interface. The service function is obtained by calling the interface, which solves the problem of high system coupling and difficult maintenance. By loading lightweight NPOI components to improve the efficiency of data import and various report generation;the system is deployed on the cloud computing platform, and the efficient computing power and disaster recovery performance of the cloud platform is used to improve system computing efficiency and security. The test results show that the power grid equipment parameter verification system based on the method is safe and stable, fast in execution, accurate in results, provides reliable decision support for users, and has a wide range of application values.

关键词： parameter verification SOA cloud computing NPOI

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Detecting data Accuracy Issues in Textual Geographical data by a Clustering-based Approach 21

Detecting Data Accuracy Issues in Textual Geographical Data ...

引用

3rd ACM India Joint international conference on data science and Management of data (CODS-COMAD)

作者： Pellegrino, Maria Angela Postiglione, Luca Scarano, Vittorio Univ Salerno Dipartimento Informat Salerno Italy

ISBN: (纸本)9781450388177

data are published to encourage data exploitation. However, data quality issues threaten data consumption and require data consumers investing time and effort in data cleansing. By focusing on textual geographical data, we aim to detect inaccurate values, such as typos, truncated values, and propose corrections by a clusteringbased approach. Our method is mainly based on a dictionary of correct values, the Agglomerative clustering to group data in clusters, and Levenshtein and Fuzzy string searching for computing word similarity. We test our approach on real open datasets published by the Campania region, heterogeneous in the topic, size, and type of errors by showing the positive results of using Levenshtein and Fuzzy Matching and exploiting clustering methods in detecting and correcting quality issues in textual geographical data. The achieved results are useful for data producers and consumers, both for the academy and the industry, in any application domain.

关键词： data quality Clustering data cleaning Quality improvement

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Recognition of Traffic Police Gestures Based on Transfer Learning

Recognition of Traffic Police Gestures Based on Transfer Lea...

引用

Electronic Information Engineering and Computer science (EIECS), 2021 international conference on

作者： Li Lian Vladimir Y. Mariano College of Computing and Information Technologies National University Manila Philippines College of Big Data and Artificial Intelligence Anhui Xinhua University Hefei China

At present, the auto-driving technology is becoming more and more mature, but how the auto-driving car recognizes the traffic police gesture information under special road conditions has become an urgent problem to be solved. In this paper, based on transfer learning, eight kinds of gesture signals of Chinese traffic police are recognized. The dataset is "Chinese Traffic Police Gesture dataset"(CTPGD). The total loss value is 0.2174, and good results have been achieved.

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3rd international conference on Soft computing and its Engineering Applications, icSoftComp 2021

3rd International Conference on Soft Computing and its Engin...

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3rd international conference on Soft computing and its Engineering Applications, icSoftComp 2021

ISBN: (纸本)9783031057663

The proceedings contain 33 papers. The special focus in this conference is on Soft computing and its Engineering Applications. The topics include: Sentiment Analysis of Twitter data Using Machine Learning Approaches;mining Spatio-Temporal Sequential Patterns Using MapReduce Approach;a Split-Then-Join Lightweight Hybrid Majority Vote Classifier;identification of Barriers in Adoption of IoT: Commercial Complexes in India;a Dynamically Adapting Framework for Stock Price Prediction;evaluating Binary Classifiers with Word Embedding Techniques for Public Grievances;database Concentration Method for Efficient Image Retrieval Using Clustering and Image Tag Comparison;microstructure Image Classification of Metals Using Texture Features and Machine Learning;segregation of Areca Nuts Using Three Band Photometry and Deep Neural Network;Early Diagnosis of Alzheimer’s Disease from MRI Images Using Scattering Wavelet Transforms (SWT);constraint Pushing Multi-threshold Framework for High Utility Time Interval Sequential Pattern Mining;KTSVidRec: A Knowledge-Based Topic Centric Semantically Compliant Approach for Video Recommendation on the Web;intelligent Facial Expression Evaluation to Assess Mental Health Through Deep Learning;intelligent Mobility: A Proposal for Modeling Traffic Lights Using Fuzzy Logic and IoT for Smart Cities;crop Disease Prediction Using Multiple Linear Regression Modelling;radial Basis Function Network Based Intelligent Scheme for Software Quality Prediction;generating the Base Map of Regions Using an Efficient Object Segmentation Technique in Satellite Images;KCEPS: Knowledge Centric Entity Population Scheme for Research Document Recommendation;weighted Hybrid Recommendation System Using Singular Value Decomposition and Cosine Similarity;CT/MRI 3D Fusion for Cerebral System Analysis;text Analysis and Classification for Preprocessing Phase of Automatic Text Summarization Systems;arabic Cyberbullying Detection from Imbalanced dataset Using Machine Learning;in

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DEGAN: A Deep Learning Model for SAR Image Segmentation in Aquacultural Raft Monitoring 3

DEGAN: A Deep Learning Model for SAR Image Segmentation in A...

引用

3rd international conference on Neuromorphic computing, ICNC 2024

作者： Lian, Shuo Wang, Jun Han, Min Fan, Jianchao School of Computer Science and Engineering Chongqing Three Gorges University Chongqing Wanzhou China City Univ of Hong Kong Department of Computer Science and Department of Data Science Kowloon Hong Kong School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798331508661

Offshore aquacultural raft information extraction from synthetic aperture radar (SAR) images is crucial for large-scale marine resource exploitation and environmental protection. In this paper, a deep learning model named Detail-Enhancing Generative Adversarial Network (DEGAN) is proposed for SAR image segmentation to monitor aquacultural rafts. DEGAN incorporates several key modules to enhance segmentation performance, including f-divergence to improve the discrim-inator's ability to handle noisy data, and the Convolutional Block Attention Module (CBAM) for more effective spatial and channel attention. Within CBAM, multi-scale feature fusion is employed to capture both fine and coarse details across different resolutions. Additionally, the Simple, Parameter-Free Attention Module (SimAM) is introduced to enhance feature refinement by deriving neuron importance through an energy function. These modules, when integrated into the GAN framework, work together to improve noise suppression and detail preservation, critical for accurate segmentation in challenging SAR images. Experimental results demonstrate that DEGAN outperforms five baseline models in four performance metrics, making it highly effective for aquacultural raft monitoring in complex marine environments. © 2024 IEEE.

关键词： Image segmentation

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MSK: A Grade Mining Method for Second-Class Based on MeanShift and K-means 3

MSK: A Grade Mining Method for Second-Class Based on MeanShi...

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3rd IEEE international conference on Computer science and Educational Informatization, CSEI 2021

作者： Dong, Yao Dong, Yongfeng Shi, Jin Deng, Yahan Pang, Shaoyuan Hebei University of Technology Hebei Key Laboratory of Big Data Computing School of Artificial Intelligence Tianjin China

ISBN: (纸本)9781728184739

With the advent of the era of big data, more and more data are accumulated by the second class in colleges and universities, and how to effectively analyze and use them has become the research focus. A novel clustering algorithm named MeanShift-K-means (MSK) is proposed to assess the scores and get the relationship between scores and graduation. Firstly, the MeanShift vector is calculated by Gaussian kernel function, Then MeanShift algorithm is used to obtain the initial clustering center points in K-Means, instead of random selection. Secondly, the improved K-means algorithm was applied to assess the second class in a university. The results show that the MSK algorithm has better clustering effect than the traditional Kmeans algorithm and Canopy-K-means algorithm, which is more helpful to recommend activities for college students and to provide predictive guidance and decision-making basis for administrators. © 2021 IEEE.

关键词： data mining

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