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Enhanced MADM Strategy with Heptapartitioned Neutrosophic Distance Metrics

Neutrosophic Sets and Systems 2025年 78卷 74-96页

作者： Eassa, Mohamed Myvizhi, M. Elkholy, Mohamed Abdelhafeez, Ahmed Elbehiery, Hussam Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Mathematics KPR Institute of Engineering and Technology Tamilnadu Coimbatore India Faculty of Computer Science& Engineering Alamein International University Egypt

In this work, a novel methodological approach to multi-attribute decision-making problems is developed and the notion of Heptapartitioned Neutrosophic Set Distance Measures (HNSDM) is introduced. By averaging the Penta-Partitioned Neutrosophic Distance Measures under particular conditional criteria, the suggested technique ranks the options. Additionally, we explore the fundamental characteristics of HNSDM and provide several illustrative theorems. The Heptapartitioned Neutrosophic Set Distance Measures are formulated based on the Hepta Neutrosophic Set. Lastly, a practical numerical example is provided to illustrate the efficacy of the suggested methodology. © 2025, University of New Mexico. All rights reserved.

关键词： Heptapartitioned Neutrosophic set Heptapartitioned Neutrosophic set and MADM strategy Heptapartitioned set Neutrosophic sine distance measure

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Breathers and Rogue Waves Derived from an Extended Multi-dimensional N-Coupled Higher-Order Nonlinear Schrdinger Equation in Optical Communication Systems

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Communications in Theoretical Physics 2018年第9期69卷 255-262页

作者： Cheng-Lin Bai Yue-Jin Cai Qing-Long Luo School of Physics Science and Information Engineering Liaocheng UniversityLiaocheng 252059China School of Computer and Information Anqing Normal UniversityAnqing 246133China Shandong Province Key Laboratory of Optical Communications Science＆ Technology Liaocheng 252059China

In this paper, an extended multi-dimensional N-coupled higher-order nonlinear Schr¨odinger equation (NCHNLSE), which can describe the propagation of the ultrashort pulses in wavelength division multiplexing (WDM)systems, is investigated. By the bilinear method, we construct the breather solutions for the extended (1+1),(2+1) and(3+1)-dimensional N-CHNLSE. The rogue waves are derived as a limiting form of breathers with the aid of symbolic computation. The effect of group velocity dispersion (GVD), third-order dispersion (TOD) and nonlinearity on breathers and rogue waves solutions are discussed in the optical communication systems.

关键词： N-coupled higher-order nonlinear SchrSdinger equations multi-dimensional rogue waves breathers bilinear transformation

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Improving the performance of aspect based sentiment analysis using fine-tuned Bert Base Uncased model

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International Journal of Intelligent Networks 2021年 2卷 64-69页

作者： Geetha, M.P. Karthika Renuka, D. Department of Computer Science& Engineering Sri Ramakrishna Institute of Technology Tamil Nadu India Department of Information Technology PSG College of Technology Tamil Nadu India

Nowadays, digital reviews and ratings of E-commerce platforms provide a better way for consumers to buy the products. E-commerce giants like Amazon, Flipkart, etc provide customers with a forum to share their experience and provide potential consumers with true evidence of the product's outcomes. To obtain useful insights from a broad collection of reviews, it is important to separate reviews into positive and negative feelings. In the proposed work, Sentiment Analysis is to be done on the consumer review data and categorize into positive and negative feelings. Naïve Bayes Classification, LSTM and Support Vector Machine (SVM) were employed for the classification of reviews from the various classification models. Many of the current SA techniques for these customer online product review text data have low accuracy and often takes longer time in the course of training. In this research work, BERT Base Uncased model which is a powerful Deep Learning Model is presented to elucidate the issue of Sentiment Analysis. The BERT model gave an improved performance with good prediction and high accuracy compared to the other methods of Machine Learning in the experimental evaluation. © 2021 The Author(s)

关键词： Sentiment analysis

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An Efficient Mouse Tracking System Using Facial Gestures 8

An Efficient Mouse Tracking System Using Facial Gestures

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8th International Conference on Advanced Computing and Communication Systems, ICACCS 2022

作者： Lakshmanarao, A. Lokesh, B. Sarita, Kilarapu Aditya Engineering College Department of Information Technology Surampalem India Raghu Engineering College Department of Cse Visakhapatnam India Aditya Engineering College Department of Computer Science& Engineering Surampalem India

ISBN: (纸本)9781665408165

A large number of human beings influenced with neuro-locomotor handicaps or those incapacitated by injury can't utilize computers/laptops for fundamental assignments like sending or getting messages, perusing the web, watching beloved Television shows or films. Through a past research study, it was presumed that eyes are a fantastic possibility for universal registering since they move in any case during cooperation with processing hardware. Utilizing this hidden data from eye developments could permit taking the utilization of computers back to these type patients. For this reason, we propose an mouse tracking framework which is totally worked by natural eyes as it were. The motivation behind this work is to develop an mouse tracking system that can viably follow eye-developments and empower the client to perform activities planned to explicit eye developments/signals through computer/laptop webcam. The proposed model controls mouse movements through facial gestures. © 2022 IEEE.

关键词： Eye movements

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Classification Models: Non Evolutionary vs. Evolutionary Approach

Classification Models: Non Evolutionary vs. Evolutionary App...

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International Conference on Advances in Computing, Control, & Telecommunication Technologies (ACT)

作者： Pardeep Kumar Saroj Rajesh Siddavatam Department of Computer Science& Engineering and Information Technology Jaypee University of Information Technology Waknaghat Himachal Pradesh India Department of Computer Science& Engineering Guru Jambheshwar University of Science and Technology Hisar Haryana India

Data mining has been the active area of research in the last decade. The classification is one of the important task of data mining. Different kind of classification algorithms have been suggested and tested to predict the future events based on unseen data. The objective of this paper is to compare various classification models that have been frequently used in data mining. Three decision trees; one neural network, one statistical and one clustering algorithm are compared on four datasets in terms of predictive accuracy, comprehensibility and training time. Further evolutionary approach based classification model is tested and compared with non evolutionary based approach. Experimental results demonstrate that overall decision tree algorithms are better in terms of accuracy, comprehensibility and training time. Out of the decision trees, QUEST generates trees with lesser levels and depth showing more comprehensibility. Finally GA based classification model shows better performance in context of some parameter including predictive accuracy and comprehensibility.

关键词： Decision trees Accuracy Clustering algorithms information technology Data mining Testing computer science Electronic mail Classification algorithms Neural networks

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Deep Learning Based Classification for Assessment of Emotion Recognition in Speech

SSRN

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SSRN 2019年

作者： Agrawal, Akshat Jain, Anurag Kumar, B. Suresh University School of Information Communication and Technology Computer Science& Engineering Amity University Rajasthan Jaipur India Department of Computer Science and Engineering

In recent events, expanding consideration has been coordinated to the investigation of the emotional material of Voice signals, and thus, numerous frameworks have been proposed to distinguish the emotional material of a verbally expressed articulation. This paper is an analysis of voice sentiments grouping tending to three critical parts of the structure for a Voice feeling acknowledgment framework. The first problem is the decision of reasonable features for voice signal portrayal. The second problem is the structure of a fitting grouping plan and the third problem is the best possible planning of a passionate voice signal database for assessing framework execution. In this paper we will try to recommend conceivable methods for enhancing voice signal acknowledgment frameworks. © 2019, The Authors. All rights reserved.

关键词： Speech recognition

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Congestion control for self similar traffic in wireless sensor network

Congestion control for self similar traffic in wireless sens...

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International Conference on Contemporary Computing (IC3)

作者： Arpan Kumar Dubey Adwitiya Sinha Department of Computer Science& Engineering Jaypee Institute of Information Technology Noida Uttar Pradesh India

Wireless sensor networks (WSNs) have inspired many research domains in recent years. Congestion is a major issue faced by such networks, which causes heavy loss in data transmissions. Congestion is caused due to several reasons, such as heavy traffic, link failure, node failure and many more. There are various techniques developed for combatting network congestion. In this paper, we have proposed a technique for prediction of the congestion before it happens and controlling the situation before it becomes worse. Congestion in the network is controlled by adjusting the traffic rate of sources. Source nodes change their transmission rate as soon as they receive the control signal. Our algorithm is developed especially for managing congestive situations created by self similar traffic. The self-similarty in network traffic is simulated Pareto distribution. Congestion in the network is detected by analyzing the buffer ratio of nodes. Further, the simulation results show that our algorithm outperforms other existing techniques in terms of packet delivery ratio and average number of packets dropped.

关键词： Prediction algorithms Wireless sensor networks Delays Propagation losses Data communication Telecommunication traffic Analytical models

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COVID-19 Detection on X-Ray Image Using Deep Learning 3

COVID-19 Detection on X-Ray Image Using Deep Learning

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3rd International Conference on Innovative Practices in Technology and Management, ICIPTM 2023

作者： Assudani, Manish K Sahu, Neeraj Arulmozhi Saravanan, A. Dhinakaran, K. Kumar, Ashok G H Raisoni University Department of Computer Science& Engineering Maharashtra Amravati India G H Raisoni University Department of Computer Science Maharashtra Amravati India Dhanalakshmi Srinivasan Engineering College Department of Information Technology Tamil Nadu Perambalur India Smk Fomra Institute of Technology Department of Electrical & Electronics Tamil Nadu Chennai India Misrimal Navajee Munoth Jain Engineering College Department of Computer Science Tamil Nadu Chennai India Banasthali Vidyapith Department of Computer Science Rajasthan India

ISBN: (纸本)9798350336238

COVID-19 is one of the threats that came out of nowhere and literally shook the entire world. Various prediction techniques have been invented in a very short time. This study also develops a Deep Learning (DL) model which can predict the presence of COVID-19 and pneumonia by analyzing the X-ray images of human lungs. From Kaggle, a collection of X-ray images of the lungs is collected. Then, this dataset is preprocessed using two alternative methods. Some of the techniques include image enhancement and picture resizing. The two deep-learning models are then trained using the preprocessed dataset. A few more examples of DL algorithms include MobileNet and Inception-V3. The best model is then selected by validating the learned deep-learning models. As the epochs count increases during training and validation, the accuracy value for both models increases. The value of the loss increases as the number of epochs decreases. During the fourteenth validation period, the model generates a loss value of 0.32 for the MobileNet technique. During the first few training epochs, accuracy is lower, and by the fifteenth, it is close to 0.9. The Inception-V3 method produces a loss value of 0.1452 at the eleventh validation epoch, which is the lowest value. The greatest accuracy value of 0.9697 is obtained after the twelfth cycle of validation. The model that performs better and has lower loss values is then put through one last test. Inception-V3 is therefore selected as the top method for COVID-19 detection. The Inception-V3 system properly predicted each of the normal images and the COVID-19 images in the final test. Regarding pneumonia, it correctly predicted just one image out of 20 that are so small as to be disregarded. When a patient cannot afford to find a doctor for consultation, the DL model created in this work can be utilized as a preliminary test for COVID-19. By including the model created in this study as a backend processor for a website or software application, the s

关键词： COVID-19

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A New Distributed Intrusion Detection Model Based on Immune Mobile Agent

A New Distributed Intrusion Detection Model Based on Immune ...

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Asia-Pacific Conference on information Processing, APCIP

作者： Jing Xu Yongzhong Li College of information engineering Yancheng Institute of Technology Yancheng China School of Computer Science& Engineering Jiangsu University of Science and Technology Zhenjiang China

The development direction of intrusion detection system is intelligent and distributed in future. However, current distributed intrusion detection system mostly uses distributed component to collect data then sent to processing center. Data is analyzed in the processing center. These models have the following problems: bad real time capability, bottleneck, and single point of failure. In order to overcome these shortcomings of current intrusion detection techniques, a new distributed intrusion detection model based on mobile agent is proposed in this paper. Intelligent and mobile characteristics of the agent are used to make computing move to data. As mobile agent can only improve the structure of system and can not supply fundamental new detecting techniques, improved dynamic clonal selection algorithm and collaborative signal mechanism are adopted for reducing false positive rate and increasing detection rate in this paper. Finally, the proposed model and algorithm were simulated by KDDpsila99 datasets. Comparing with winning entry of KDDpsila99 classifier learning contest, the proposed model has low false positive rate and higher detection rate in both Dos and Probing attacks, and greatly higher detection rate in U2R attack. Robustness and dynamic adaptability of the system are validated.

关键词： Intrusion detection Mobile agents Heuristic algorithms Collaboration computerized monitoring Intelligent agent Condition monitoring Autonomous agents Immune system Detectors

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A Framework to Improve Adaptability in Web Service Composition

A Framework to Improve Adaptability in Web Service Compositi...

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2010 2nd International Conference on computer engineering and Technology(2010年第二届计算机工程与技术国际会议 ICCET 2010)

作者： Wenjuan Lian Qingtian Zeng Yongquan Liang Jingjing Yan College of Network Eng.Shandong University of Science& Technology Qingdao Shandong266510China College of Information Science& Eng. Shandong University of Science& Technology Qingdao Shandong266 College of Information Science& Eng.Shandong University of Science& Technology Qingdao Shandong2665 Department of Computer Engineering TaiZhou Vocational & Technical College.Taizhou Zhejiang318000Ch

ISBN: (纸本)9781424463473;9781424463497;9781424463503

Web service combination,which integrates independent and modular distributed services,has loosely coupled,location transparent,protocol independent and other characteristics,but it is still lack of autonomic,self-adaptive and self-organized characteristics,and it’s difficult to deal with the complex,dynamic,open and uncertain Internet environment. A framework to improve composition adaptability of web services is proposed in the paper. This framework makes use of agents to supervise and manage service composition implementation. It can deal with various service failures,face different circumstances,and ultimately improve the adaptability of service composition in real-time context-aware style. To evaluate the proposed framework,the prototype implementation and data analysis are given at last.

关键词： web service:service composition:adaptability agent:context-aware

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