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A Novel Integration of Hierarchical Clustering and Ensemble Classification Algorithms for News Classification 1

A Novel Integration of Hierarchical Clustering and Ensemble ...

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1st ieee international conference on Cognitive Robotics and intelligent systems, ICC - ROBINS 2024

作者： Sreekala, Keshetti Sivajyothi, Modugula Chiranjevi, Dukuru Sunitha, Gadipe Swetha, Mucha Department of Cse Hyderabad India Cmr Technical Campus Medchal Department of It Telangana Hyderabad India Aditya Engineering College Department of It Surampalem India Sumathi Reddy Institute of Technology for Women Department of Cse Warangal India

ISBN: (纸本)9798350372748

This research work proposes a novel approach for news classification by integrating hierarchical clustering and ensemble algorithms. The proposed methodology began with the acquisition and preprocessing of the BBC News dataset taken from Kaggle. Text data underwent preprocessing by including tokenization, removal of stop words, and TF-IDF vectorization. Hierarchical clustering was then applied to group similar documents based on their content by using the Agglomerative Clustering algorithm. The number of clusters was adjustable for varying granularity. Subsequently, cluster labels obtained were assigned to corresponding documents, and additional features were extracted from the clustered data. These features, alongside the TF-IDF matrix, served as an input for training Gradient Boosting, Bagging Classifier and Random Forest classifiers. These classifiers were trained to predict document categories based on both text features and cluster assignments. The trained models were then tested on a separate test set to evaluate their generalization ability. Clustering and classification results were carefully evaluated to assess method efficacy, elucidating the relationship between document clustering and classification performance. © 2024 ieee.

关键词： Information retrieval systems

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Semantic Modelling of Multivariate Time-Series data in Cognitive IoT 9

Semantic Modelling of Multivariate Time-Series Data in Cogni...

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9th international conference on advanced computing and Communication systems, ICACCS 2023

作者： Jha, Vidyapati Tripathi, Priyanka NIT Raipur Department of Computer Application India

ISBN: (纸本)9798350397376

With the use of sensors and intelligent devices to assist interactions with the physical environment, we observe a significant rise in the amount of sensory input, which is continual, volatile, sometimes actual, and diverse in structure. The Internet of Things (IoT) encapsulates this phenomenon. In addition, when IoT integrates cognition into system design, it is called Cognitive IoT (CIoT). CIoT requires techniques to autonomously extract semantic patterns from plain sensory data for efficient service delivery. Only a little scientific attention has been paid to automatically identifying semantic patterns from a massive time-series data set. This research presents a scaffold for real-time automatic semantic pattern extraction in the Cognitive Internet of Things. It utilizes the Symbolic Aggregate Approximation (SAX) technique for sensory data with a multivariate time series. Further, the output of SAX is used to create a symbol table with their frequency. This frequency table is transformed into its corresponding probabilistic value. Finally, this value is used to generate the semantic pattern, which can be further processed using a rule-based method to create a machine-interpretable pattern. Experimental evaluation of this research study reveals that the proposed method can extract semantic patterns from heterogeneous multivariate sensory data. © 2023 ieee.

关键词： Internet of things

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Proceedings - 11th ieee international conference on intelligent computing and Information systems, ICICIS 2023

Proceedings - 11th IEEE International Conference on Intellig...

引用

11th ieee international conference on intelligent computing and Information systems, ICICIS 2023

ISBN: (纸本)9798350322101

The proceedings contain 85 papers. The topics discussed include: traditional and deep learning techniques in image steganography: recent advances;deep learning for extracting human movement patterns from spatio-temporal data;speech emotion recognition: enhancing human-computer interaction;a combined ELM and CNN model architecture for accurate viral family DNA classification;ML driven priority-based constrained routing for pollution management in ITS;on development of computer aided system for detecting brain neurological disorders;CalorieMe: an image-based calorie estimator system;deepfake detection using EfficientNet and XceptionNet;dental disease detection based on CNN for panoramic dental radiographs;and AI-based detection of myocardial infarction through electrocardiogram signals: a review.

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Design and Implementation of English intelligent Question Answering Based on Similarity Algorithm 5

Design and Implementation of English Intelligent Question An...

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5th international conference on Advances in Electrical Engineering and Computer Applications, AEECA 2024

作者： Jiang, Chunxia Sichuan University of Media and Communications Chengdu China

ISBN: (纸本)9798350355253

In recent years, with the rapid development of Internet technology and computer information technology, people's lives are closely connected with the network, and this emerging product has greatly changed the way of information acquisition and communication. In this context, in order to process and use massive network resources more efficiently, new types of Q&A systems have emerged, which rely on advanced similarity algorithms and optimised similarity metric search methods, and have rapidly gained widespread popularity. Given the unique advantages of such techniques such as real-time response and high scalability, they have become one of the hotspots in the current research field. The aim of this paper is to design and implement a simple, efficient and practical online English intelligent Q&A system to meet the increasing demand for information query and enhance user experience. In this paper, an online English intelligent Q&A system that can respond to user queries in real time is constructed by adopting the core technology based on similarity algorithm and combining the feedback law of iteration number calculation to optimise the Q&A matching process. In the process of system implementation, this paper focuses on optimising the similarity calculation module to ensure its efficiency and accuracy in handling large amounts of data. After rigorous performance testing, the online English intelligent Q&A system developed in this paper demonstrated excellent performance, with its reliability reaching more than 93%. This result indicates that the system is able to provide accurate and useful answers when processing user queries, effectively enhancing users' information acquisition efficiency and satisfaction. Through the advanced similarity algorithm and iterative feedback mechanism, the accuracy of information retrieval and user experience are significantly improved, providing new ideas and technical references for the development of future intelligent Q&A systems. © 20

关键词： Question answering

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Developing Coordinate Conversion Mobile Application for Geomatics Education 3

Developing Coordinate Conversion Mobile Application for Geom...

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3rd international conference on advanced Research in computing, ICARC 2023

作者： Hussaini, Alhaji Huang, Lei Tang, Kelvin Kang Wee Aminu Saleh College of Education Azare Department of Geography Bauchi State Nigeria Universiti Teknologi Malaysia School of Computing Faculty of Engineering Johor Bahru81310 Malaysia Universiti Teknologi Malaysia Faculty of Built Environment & Surveying Johor Bahru81310 Malaysia

ISBN: (纸本)9798350347371

Today, millions of mobile applications (apps) have been created and placed in Apple Store and Google Play Store. Users can easily download from the app stores and operate them using their handy gadgets. By merging information and communication technology (ICT) with geomatics, we are able to leverage smartphones and tablets for data acquisition and sensing, data processing and computation as well as distribution of geospatial information. Many sophisticated survey programs and tedious computations can be leveraged by using automated service-oriented programs, either in web-based apps or mobile apps. This study has created mCOORD mobile app for coordinate system conversion in Malaysia. The developed mobile app works in two ways: firstly, it transforms a pair of defined coordinates into their relevant coordinate reference systems;and secondly, it allows immediate viewing of the location in an interactive map. As for this study, we presented the performance and efficiency of the app by comparing the converted data with authorized GDTS conversion tools and several open-source GIS software. For instance, the differences of converted coordinates obtained from mCOORD and GDTS are relatively small and within the allowable tolerance. Hence, the successful development of this publicly accessible coordinate conversion app is beneficial to all GIS users in Malaysia. © 2023 ieee.

关键词： data acquisition

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Implementation of intelligent Farm Guards: Utilizing Bidirectional Monitoring for Motor Efficiency 8

Implementation of Intelligent Farm Guards: Utilizing Bidirec...

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8th international conference on Inventive systems and Control, ICISC 202

作者： Sujitha, S. Athrey, Amisha Jhansi Priya, K.N. Lavanya, N. Janhavi, G. New Horizon College of Engineering Department of Eee Bengaluru India

ISBN: (纸本)9798350386578

The agriculture sector faces significant challenges in ensuring the efficiency and reliability of farm equipment, particularly motor-driven systems. This research study proposed intelligent Farm Guards (IFGs), which represent a novel bidirectional monitoring approach to optimize motor efficiency and extend equipment lifespan. This study explores the integration of sensor networks, IoT technology, and advanced analytics to create a comprehensive monitoring system. By analyzing real-time data from motor operations and environmental conditions, IFGs provide actionable insights to farmers, enabling maintenance and efficient resource management. The results demonstrate substantial improvements in motor efficiency, reduced downtime, and lower operational costs, marking a significant advancement in smart farming technologies. This study utilizes the Internet of Things (IoT) to develop and deploy an intelligent Farm Guard utilizing bidirectional monitoring system for a single-phase DC motor to enable real-time remote monitoring and control using internet. The proposed system combines sensor technologies with IoT communication protocols to facilitate effective data collection and control. Here, the sensors are employed to monitor motor parameters such as voltage, current, speed, and direction. The microcontroller processes the data from sensors and transmits it wirelessly to a cloud-based platform using IoT protocols. © 2024 ieee.

关键词： advanced Analytics

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advanced Digital Platform for Agricultural Risk Management 16

Advanced Digital Platform for Agricultural Risk Management

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16th ieee international conference on Semantic computing (ICSC)

作者： Cruvinel, Paulo E. Embrapa Instrumentat Sao Carlos Brazil

ISBN: (纸本)9781665434188

This paper presents a robust system for agricultural risk management based on semantic knowledge and decision making processes at farm scale. Thus, in order to anticipate, avoid and react to shocks arising from negative externalities that may occur during a production process, the method has been structured using algorithms that enable not only an efficient agricultural management, but also a rational use of inputs in the crop management phase. The processing services have been implemented on a cloud computing infrastructure, being specific for geo-spatialized agricultural applications, i. e., involving large amounts of data and analytics. For the validation case studies were considered based on corn crop cycles (Zea Mays. L.) under rainfed conditions, two of them in the normal harvest period and the third in the off-season period, using the concept related to Research-on-Farm.

关键词： semantic computation agricultural risk intelligent systems big data

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Elevating Security in Wireless Sensor Networks using ECC and AES Cryptographic Techniques

Elevating Security in Wireless Sensor Networks using ECC and...

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2023 international conference on Innovative computing, intelligent Communication and Smart Electrical systems, ICSES 2023

作者： Dayana, D.S. Pandian, R. Babu, A. Ramesh Nirmalraj, S. Jebaseelan, S. D. Sundarsingh Mohan, V. SRM Institute of Science and Technology Dept. of Networking and Communications India Sathyabama Institute of Science and Technology Dept. of Electronics and Communication Engineering India Sathyabama Institute of Science and Technology Dept. of Electrical and Electronics Engineering India

ISBN: (纸本)9798350319200

This research article stands as a formidable response to the security vulnerabilities that loom over wireless sensor networks (WSNs). In a pioneering stride, the study introduces an advanced cryptographic framework designed to tackle these vulnerabilities head-on. The heart of this framework lies in the seamless integration of two potent cryptographic forces: Elliptic Curve Cryptography (ECC) and the advanced Encryption Standard (AES). The result is the ECC and AES cryptographic amalgamation, positioned as a robust solution to fortify the security of data transmission within WSNs. Engineered with a keen understanding of the challenges posed by resource-constrained environments - a hallmark of WSNs - the ECC and AES cryptographic system emerges as a beacon of security. This fusion optimizes security protocols while meticulously curtailing memory and energy consumption. The research outcomes hold promise for a transformative impact on WSNs, elevating the data protection landscape to unprecedented heights. This article transcends the boundaries of conventional security measures by presenting a cutting-edge framework that redefines security paradigms within WSNs. As modern applications continue to rely on the seamless and secure flow of data, the ECC and AES cryptographic solution emerges as an emblem of innovation, poised to elevate the potency of security protocols within the WSN domain. © 2023 ieee.

关键词： advanced Encryption Standard (AES) data protection Elliptic Curve Cryptography (ECC) security vulnerabilities Wireless Sensor Networks (WSNs)

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Angioplasty Virtual Reality Simulator: Modeling of Blood Flow in an Artery

Angioplasty Virtual Reality Simulator: Modeling of Blood Flo...

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ieee international Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Bakhyt Alipova Fatima Tokmukhamedova Zhiger Bolatov Yevgeniya Daineko Madina Ipalakova Dana Tsoy Mathematical and Computer Modeling International IT University Mechanical and Aerospace Engineering University of Kentucky Research Activities International IT University International Affairs International IT University Computer Engineering International IT University

Blood flow in human arteries considered as an important aspect of health care. Due to the large amount of difficulties conducting in-vivo experiments, the use of computational fluid dynamics (CFD) to simulate pulsatile flow in the blood artery has become a promising alternative approach. In this paper the 2-dimensional model of blood flow in the rectangular coordinates is formed by numerical approach and the simulation by Unity Engine is provided. The simulation showed that the blood flow was laminar within the artery. The velocity magnitude of blood was highest at the center of the artery and gradually decreased towards the walls due to the no-slip condition. These results are consistent with previous experimental and computational studies of blood flow in arteries.

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Metamorphosing Teaching and Learning with Python: A Practical Guide for Teachers Employing Text data Analysis Using the Bag of Words (BoW) Model

Metamorphosing Teaching and Learning with Python: A Practica...

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2023 ieee international conference on Quantum Technologies, Communications, computing, Hardware and Embedded systems Security, iQ-CCHESS 2023

作者： Rekhi, Ashraf Alam Indian Institute of Technology Rekhi Centre of Excellence for the Science of Happiness West Bengal Kharagpur India

ISBN: (纸本)9798350314946

This research explores the application of the Bag of Words (BoW) model for text data analysis with the goal of enhancing teaching-learning in the classroom. The BoW model expresses text as a 'bag' of its individual words while ignoring word order. The study covers the use of the BoW model toward the creation of intelligent teaching systems. These systems identify areas where students may be having difficulty and offer focused feedback and guidance by examining the language used by students as they work through an issue or subject. The paper uses snippets of Python code as examples and their outputs to demonstrate how the BoW model can be used to improve learning outcomes. The BoW model's importance in assessing educational resources, developing intelligent tutoring programmes, and analysing student writing is greatly emphasised in the paper. © 2023 ieee.

关键词： Sentiment analysis

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