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Nuances of Data Pre-Processing and its Impact on Business

Nuances of Data Pre-Processing and its Impact on Business

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International conference on ent Computing and Control Systems (ICICCS)

作者： M. Sumathi S.Ashika Parvin Sri Meenakshi Govt Arts College for women (A) Madurai India

Sentiment analysis (SA), is an open-ended field of research about computational remedy of classifying the human being's opinion about something. the data pre-processing plays a decisive position in SA which is obtained by accelerating the effectively classified instances through the selection of suitable preprocessing methods. When using both the Rule-based and Decision Tree algorithms separately, the missing of data happens that can cause the incorrect classifications of critiques and make the SA procedure not that effective. On the component of the above, this paper explains approximately the importance of pre- processing by introducing a novel approach of combining both the Rule-based and Decision Tree algorithms. the RBDT is a proposed approach which handles the lacking of information values effectively by making sure no word is missed during the classification process. the Experimental results classified the proposed technique to be more effective in achieving accuracy of 90% and time complexity of 0.079 seconds in predicting all the words in the dataset rather than using both the algorithms individually.

关键词： Sentiment analysis Prediction algorithms Approximation algorithms Control systems Classification algorithms Decision trees Time complexity

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A Succinct Summary of the Solar MPPT Utilizing a Diverse Optimizing Compiler

A Succinct Summary of the Solar MPPT Utilizing a Diverse Opt...

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International conference on Contemporary Computing and Informatics (IC3I)

作者： N. Pushpalatha S. Jabeera N. Hemalatha Vandana Sharma Balamurugan Balusamy R. Yuvaraj Department of Electrical and Electronics Engineering Sri Eshwar College of Engineering Coimbatore Tamilnadu India Department of Electrical and Electronics Engineering Pollachi Institute of Technology Pollachi Tamilnadu India Amity Institute of Information Technology India Shiv Nadar Institute of Eminence Delhi-NCR India Department of Electrical and Electronics Engineering Excel Engineering College Namakkal Tamilnadu India

AI approaches have been widely used for MPPT in solar power systems in the recent decade. Conventional MPPT can’t track GMPP under partial shade (PSC). A solar panel’s power-voltage output curve has one GMPP and several LMPPS (MPPs). AI must be integrated into MPPT to track GMPP and improve its efficiency and performance. Each AI-based MPPT approach has its own pros and cons. In general, AI-based MPPT approaches have quick convergence speeds, low steady-state oscillations, and high effectiveness. AI-based MPPT is computationally intensive and expensive. this research compares the categorization and performance of various AI-based MPPT approaches. In the proposed work it is found that ANN algorithm is less complex, more efficient in tracking ability, periodic tuning is available. FLC deserves the merit of efficient implementation with periodic tuning. PSO, ACO, DE, GA has a rapid convergence speed. GWO/FOAhas more system independency and Even though the tracking is not possible RMO/CSis one of the most efficient algorithms.

关键词： Optimizing compilers complexity theory Steady-state Power systems Artificial intelligence Informatics Tuning

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Lightweight Multilevel Feature Fusion Network for Hyperspectral Image Classification

Lightweight Multilevel Feature Fusion Network for Hyperspect...

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IEEE International conference on Information Communication and Signal Processing (ICICSP)

作者： Quanyu Huang Haojin Tang Weixin Xie Yanshan Li ATR National Key Laboratory of Defense Technology Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China

Hyperspectral image (HSI) classification is the key technology of remote sensing image processing. In recent years, convolutional neural network (CNN), which is a powerful feature extractor, has been introduced into the field of HSI classification. Since the features of HSI are the basis of HSI classification, how to effectively extract the spectral-spatial features from HSI with CNN has become a research hotspot. the HSI feature extraction network, based on two-dimensional (2D) and three-dimensional (3D) CNN which can extract both spectral and spatial information, may lead to the increase of parameters and computational cost. Compared with 2D CNN and 3D CNN, the number of parameters and computational cost of one-dimensional (1D) CNN will be greatly reduced. However, 1D CNN based algorithms can only extract the spectral information without considering the spatial information. therefore, in this paper, a lightweight multilevel feature fusion network (LMFFN) is proposed for HSI classification, which aims to achieve efficient extraction of spectral-spatial features and to minimize the number of parameters. the main contributions of this paper are divided into the following two points: First, we design a hybrid spectral-spatial feature extraction network (HSSFEN) to combine the advantages of 1D, 2D and 3D CNN. It introduces the idea of depthwise separable convolution method, which effectively reduces the complexity of the proposed HSSFEN. then, a multilevel spectral-spatial feature fusion network (MSSFFN) is proposed to further obtain more effective spectral-spatial features, which effectively fuses the bottom spectral-spatial features and the top spectral-spatial features. To demonstrate the performance of our proposed method, a series of experiments are conducted on three HSI datasets, including Indian Pine, University of Pavia, and Salinas Scene datasets. the experimental results indicate that our proposed LMFFN is able to achieve better performance than the manual f

关键词： three-dimensional displays Convolution Two dimensional displays Manuals Feature extraction Computational efficiency complexity theory

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An Effective Contrast Enhancement Approach for Wide Dynamic Range Image

An Effective Contrast Enhancement Approach for Wide Dynamic ...

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International conference on Vision, Image and Signal Processing (ICVISP)

作者： Xiongwei Sun Xiong Wei Qinshan Xu Cheng Zhang Chinese Academy of Sciences Laboratory of Photoelectric Detection Anhui Institute of Optics and Fine Mechanics Hefei China The 38th Research Institute China Electronics Technology Group Co. Ltd Hefei China

ISBN: (纸本)9781665408356

Wide dynamic range image enhancement plays an important role in image processing applications. this study presents a low-complexity automatic method for wide range image contrast enhancement. According to a large number of experimental results that a narrow range image enhancement problem can be described easily by Gaussian curve. In this paper, we divide wide dynamic range image into regular cells and then applying an optimized image remapping method based on contrast gain redistribution function groups. By improving the bilinear fusion method between cells and simplifying the mean and variance of the contrast gain redistribution function, the algorithm complexity is reduced significantly and the whole process is fully automatic. Experiments show that the presented method enhances the visual effect of the wide dynamic range image effectively and fast, making it suitable for real-time applications.

关键词： Shape Heuristic algorithms Signal processing algorithms Dynamic range Signal processing Visual effects Real-time systems

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Using Wearable IoT Devices to Analyze Healthcare Data for Human Activity Recognition

Using Wearable IoT Devices to Analyze Healthcare Data for Hu...

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International conference of Electronics, Communication and Aerospace Technology (ICECA)

作者： G. Sri Laxmi S. Pradeep Kumar Reddy VJIT ECE Hyderabad India

ISBN: (纸本)9781665435253

Now a day's wearable sensors have gained lots of importance in the field of healthcare researches. Utilizing wearable IoT (sensors) for analyzing health parameters has become more reliable. But in the present scenario the W-IoT which are used, needs to be improvised as there are few complexities in the design and the monitoring abilities. To overcome this, a system is designed which uses linear regression algorithms to analyze the wearable sensors data. All the information gathered from the wearable device applied to the liner regression algorithm where the analysis is made, and the outcome is displayed on the things board server and the update are sent to the mobile application. With this, the reduction of complexity can be achieved and also reduce the human effort by constant monitoring of the patient.

关键词： Wearable computers Linear regression Medical services complexity theory Mobile applications Servers Reliability

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Cloud Based Exon Prediction Using Maximum Error Normalized Logarithmic algorithms 5th

Cloud Based Exon Prediction Using Maximum Error Normalized L...

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5th International conference on Advances in Computing and Data Sciences (ICACDS)

作者： Rahman, Md Zia Ur Haneesh, Annabathuni Chandra Reddy, Bhimireddy Shanmukha Sai Surekha, Sala Srinivasareddy, Putluri KL Univ Koneru Lakshmaiah Educ Fdn Dept ECE Guntur 522002 Andhra Pradesh India

ISBN: (纸本)9783030814625;9783030814618

Distributed computing gives medical services organizations significant examination and monetary advantages. Cloud administrations guarantee that enormous amounts of such delicate information will be put away and overseen safely. the quality succession labs send crude or gathered data through the Internet to a few arrangement libraries under conventional progression of quality data. Cloud service use will reduce DNA sequencing storage costs to a minimum. In this work, we demonstrated a new genomic bioinformatic system, using Amazon Cloud Services, that stores and processes genomic sequence information. A critical assignment in bio-informatics, which helps in the recognizable proof and plan of sickness drug, is the genuine ID of exon locales in deoxyribonucleic corrosive (DNA) arrangement. All exon recognizable proof procedures depend on three fundamental periodicity (TBP) properties of exons. In contrast with a few different strategies, versatile sign preparing procedures have been promising. this paper utilizes the most extreme blunder standardized least logarithmic outright distinction (MENLLAD) calculation likewise its marked variations to build up various Adaptive Exon Predictors (AEPs) with less computational multifaceted nature. At last, a presentation assessment is performed for various AEPs utilizing different standard quality information successions got from National Biotechnology Information Center (NBI) genomic grouping data set, for example, Sensitivity (Sn), Specificity (Sp) and Precision (Pr) estimations.

关键词： Bioinformatics Cloud computing Computational complexity Exon predictor three base periodicity

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Time complexity Analysis of Optimal Firefly Vector Quantization algorithms for Image Compression 5

Time Complexity Analysis of Optimal Firefly Vector Quantizat...

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5th International conference on Inventive Computation Technologies (ICICT)

作者： Preethi, D. Loganathan, D. Pondicherry Engn Coll Dept Comp Sci & Engn Pondicherry India

ISBN: (纸本)9781728146850

Vector quantization is a lossy compression method utilized in communication as well as image coding. In scalar quantized, a scalar values are chosen from a restricted list of probable values to signify a model. In vector quantized, vectors are choosing from a limited record of probable vectors to signify an input vector of models. the key function in a vector quantized is the quantized of an arbitrary vector with encoder it as a binary key. VQ became an amazing method in the usage of digital image compression. the usual and extensively utilized manner consisting of the Linde-Buzo-Gray (LBG) technique created local best codebook. In this paper, a comparative analysis is made among the firefly by Tumbling effect (FF-T) and firefly with teaching and learning based optimization (FF-TLBO) techniques to VQ. Experimental outcomes illustrate that the presented FF-LBG techniques are earlier than the alternative 4 methods. Additionally, the recreated images obtain higher quality than that constructed shape the LBG, PSO and QPSO, but it's far no massive superiority to the HBMO set of technique. On the applied set of images, the FF-TLBO-LBG algorithm requires an average CT of 794.213ms whereas the FF-T-LBG model needs a minimum CT of 777.548ms.

关键词： Linde-Buzo-Gray (LBG) DCT vector quantization (VQ) FF-LBG algorithm

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Functional Modification of Advanced Encryption Standard Algorithm by Perturbing the Diffusion and Confusion Properties

Functional Modification of Advanced Encryption Standard Algo...

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International conference on Electrical Engineering and Information & Communication Technology (ICEEICT)

作者： Sharmin Sultana Sharmee Sadia Nowshiny Md. Mahbubur Rahmanz Musfiqur Sazal Military Institute of Science and Technology Dhaka Bangladesh Microsoft Corporation Atlanta Georgia USA

ISBN: (纸本)9781665495233

Advanced Encryption Standard is the most acceptable and widely used symmetric algorithm. However, cyber attacks and security breaches are becoming very common day by day. Cyber attacks hit businesses all over the world, not only financially but also in the terms of reputation. that is why more robust security measures are needed to protect privacy and prevent data breaches. In this paper, we analyzed the traditional AES algorithm and proposed some enhancements. We modified both the diffusion and confusion section by employing modified key scheduling and cipher rounds. While making the encryption stronger, we did not compromise with the complexity and user-friendliness. through simulation studies we showed that our modification increased the avalanche effect of the algorithm by 6%, and our proposed algorithm takes 35.23% less time than the original.

关键词： Ciphers Data privacy Data breach Prediction algorithms Communications technology Encryption complexity theory

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Combined attention mechanism and CenterNet pedestrian detection algorithm

Combined attention mechanism and CenterNet pedestrian detect...

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IEEE Advanced Information Technology, Electronic and Automation Control conference (IAEAC)

作者： Shuangcai Liu Hui Ma College of Electronic Engineering Heilongjiang University Harbin China

ISBN: (数字)9781728180281

ISBN: (纸本)9781728180298

Traditional pedestrian detection methods can no longer be effective improvement of pedestrian detection, so this paper proposes a pedestrian detection method combined with the attention mechanism, SE-Net attention mechanism and ECA-Net attention mechanism for channel focusing on sex to suppress some not important information channel, which greatly improves the recognition accuracy. Algorithm in this paper, based on CenterNet experiment, by predicting the pedestrian center and return the size information, this kind of anchor-free algorithm greatly reduces the time complexity. By targeting some occlusion and small scale pedestrian attention, our results on the Eth dataset are a good improvement over the original network.

关键词： Visualization conferences Focusing Prediction algorithms Detection algorithms Time complexity Information technology

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An efficient and high-precision algorithm on parameters estimation of LFM signal 5

An efficient and high-precision algorithm on parameters esti...

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2020 5th International conference on Intelligent Computing and Signal Processing, ICSP 2020

作者： Ruan, Hang Zhang, Shuxian Beijing Institute of Track and Telecommunication Technology Beijing100094 China

At present, prevalent algorithms on parameters estimation of linear frequency modulation (LFM) signal include the fractional Fourier transform (FrFT) method, of which the crucial procedure is to estimate the optimal rotation angle. the estimated value of the optimal rotation angle has a great influence on the estimation accuracy of LFM parameters, and it also affects the computational complexity of the algorithm. this paper proposes an algorithm on parameters estimation of LFM signal with high efficiency and precision. Based on the mathematical relationship between the optimal and any two rotation angles of FrFT, the optimal rotation angle is calculated through three FrFT transforms and interpolation, and the LFM signal parameters are estimated with high efficiency and precision. Simulation results verify the effectiveness of the proposed algorithm. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Computational complexity

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