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Mathematical Modeling using Rough Set and Random Forest Model to Predict Wind Speed 9

Mathematical Modeling using Rough Set and Random Forest Mode...

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9th International Conference on Computing for Sustainable Global Development, INDIACom 2022

作者： Das, Ratnakar Mishra, Jibitesh Mishra, Sujogya Pattnaik, P.K. Das, Subhalaxmi Odisha University of Technology and Research Dept. of Computer Science and Application Bhubaneswar India Utkal University Dept. of Computer Science and Application Bhubaneswar India

ISBN: (纸本)9789380544441

Prediction of meteorological phenomena using conventional techniques is always a challenge for meteorologists. We developed a novel method for predicting meteorological phenomena by using the Random Forest Model (RFM) and Rough Set Theory (RST). We have used RST to find the most significant meteorological phenomena, and then by using RFM, we have derived a set of predictive results. Using RST on vague meteorological data, we find that the significant meteorological phenomenon is wind speed. After using the RFM based on the outcome, we have predicted the wind speed. We used the Chi-square test to validate our claim. For our analysis, we collected various meteorological data from different parts of our Odisha state in India. © 2022 Bharati Vidyapeeth, New Delhi.

关键词： Rough set theory

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A Machine Learning Approach to Compare Causal Inference Modelling Strategies in the Digital Advertising Industry 2

A Machine Learning Approach to Compare Causal Inference Mode...

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2nd International Conference on Ambient Intelligence in Health Care, ICAIHC 2023

作者： Singh, Sanskriti Sanjay Kumar Kumar Sinha, Apoorv Pandey, Trilok Nath Acharya, Biswa Mohan School of Computer Science and Engineering Vellore Institute of Technology Chennai India SOA University ITER Dept. of Computer Application Bhubaneswar India

ISBN: (纸本)9798350344882

Cause and effect relationships are not extensively explored in machine learning but prior to creating a system that understands causal relationships, there needs to be a general ability to grasp and inculcate cause-and-effect statistically. The way of choice for the proposed model is causal inference where the causes are inferred from the data. The study of causality, unlike correlation, falls in the domain of prescriptive analytics, that is, the likelihood of an occurrence given that another occurrence has happened. As a result, the study of causality and predictions based on causal inference are highly important when it comes to the domain of marketing and sales, largely because many practices in the domain of advertising try to fundamentally mimic causal inference such as A/B testing, primarily used in e-commerce and the digital advertising industry. For the purposes of the study, the treatment will be exposure to multiple advertisements and the uplift modelling will be used to direct marketing efforts to the most agreeable customers. Uplift modelling is a causal learning approach that estimates the dataset's individual treatment effect and using the same, calculates the incremental impact of a direct treatment on the individual behavior of the customer, which is why the advertising use-case felt particularly suitable. The usual way causal inference is inculcated in machine learning models is that one attribute is taken as a treatment, that is, the intervention or policy that has been done, while the target label is the desired outcome while accounting for the confounders which are the rest of the attributes. However, for the crux of this study, the proposed model will be taking two treatment attributes so as to see how the causality of two outcomes improves or worsens the impact of a rudimentary machine learning model. At the same time, this comparative study will be in tandem with two other models featuring one causal relationship as well as no causal relations

关键词： Sales

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FedERA: Framework for Federated Learning with Diversified Edge Resource Allocation 2

FedERA: Framework for Federated Learning with Diversified Ed...

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2nd IEEE International Conference on Federated Learning Technologies and applications, FLTA 2024

作者： Borthakur, Anupam Kasliwal, Aditya Manna, Asim Dewan, Dipyan Sheet, Debdoot Centre of Excellence in Artificial Intelligence Indian Institute of Technology Kharagpur West Bengal India Dept. of Data Science and Computer Application Manipal Institute of Technology Karnataka Manipal India

ISBN: (纸本)9798350354812

Federated Learning (FL) is a distributed machine learning (ML) approach that allows multiple devices to train a model while keeping training data private on edge devices. However, existing FL libraries are incapable of: (i) supporting a wide range of existing FL algorithms, (ii) handling diverse public as well as custom datasets, (iii) discarding unreliable updates from malicious edge devices, (iv) facilitating edge-device training, and (v) implementing model compression to reduce communication overhead. With the rapid progression in AI, there is an increment in the computation power while training the models on edge devices which results in more carbon emission (CE). However, in most of the existing FL frameworks, there is no module for estimating CE. In this paper, we present FedERA, a modular and fully customizable open-source FL framework aiming to address these issues especially also by offering extensive support on heterogeneous edge devices and by incorporating both standalone and distributed training approaches. The integration of new software modules unforeseen in existing FL frameworks not only amplifies the scope of its usability but also fosters environment-friendly FL. We believe that FedERA will be a valuable tool for researchers and practitioners working in FL. ©2024 IEEE.

关键词： Federated learning

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An Efficient Approach to Deal with Cyber Bullying using Machine Learning: A Systematic Review 2

An Efficient Approach to Deal with Cyber Bullying using Mach...

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2nd International Conference on Emerging Trends in Information technology and Engineering, ic-ETITE 2024

作者： Naveen Kumar, M.R. Vishwachetan, D. Mushtaq Ahmed, D.M. Dayananda, K.J. Manasa, K.J. Nanda, K.V. Vidyavardhaka College of Engineering Information Science and Engineering Mysuru India Ramaiah Institute of Technology Information Science and Engineering Bengaluru India Gsss Ssfgc Dept. of Computer Application Mysuru India MUSoE Dept. of Aiml Manasagangothri Mysuru India Sri Siddhartha Institute of Technology Compter Application Tumkur India

ISBN: (纸本)9798350328202

The prominence of social media platforms like Facebook, WhatsApp, and Instagram have given rise to Cyber crime, notably in the form of Cyber bullying. This unique manifestation of harassment involves individuals exploiting social networks to engage in harmful behaviors such as posting toxic comments or sharing embarrassing content, often causing severe reputation damage to victims, particularly among teenagers. This Paper gives a comprehensive survey of technical approach to tackle this escalating issue, employing advanced machine learning algorithms such as Support Vector Machines (SVM), Convolution Neural Networks (CNN), and J48. The objective is to review models capable of accurately detecting Cyber bullying, thereby contributing to the creation of robust systems that promote a safer online environment, focusing on safeguarding vulnerable demographics like teenagers and also possible future direction. © 2024 IEEE.

关键词： Support vector machines

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A New Quantum Inspired Algorithmic Approach to Finding Minimum Spanning Tree 20

A New Quantum Inspired Algorithmic Approach to Finding Minim...

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20th IEEE India Council International Conference, INDICON 2023

作者： Kaur, Amrit Bansal, Sulabh Manipal University Jaipur Dept. of Computer Application Jaipur India Manipal University Jaipur Department of Information Technology Jaipur India

ISBN: (纸本)9798350305593

One of the most common and well-known problems in combinatorial optimization is the minimum spanning tree. With the emergence of complex data structures, new, more complex, but asymptotically efficient algorithms have been proposed. In this research, we present a new evolutionary algorithm influenced by quantum mechanics, known as quantum-inspired evolutionary algorithm (QIEA) to find the minimum spanning tree of a complete weighted undirected graph as input and computational results to demonstrate the effectiveness of proposed algorithm. The proposed algorithm is named QIEA-MST and is based on concept and principle such as qubits and the superposition, coherence and the entanglement of different qubits of quantum state. The algorithm is simple and easy to understand and easy to implement. Some types of scientific and engineering problems will benefit from the proposed method. © 2023 IEEE.

关键词： Evolutionary Algorithm Graph Theory Minimum Cost Spanning Tree Quantum Inspired Evolutionary Algorithm Qubits Spanning Tree

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IoT based Truck Wheel Temperature Monitoring System

IoT based Truck Wheel Temperature Monitoring System

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2024 Asian Conference on Intelligent Technologies, ACOIT 2024

作者： Zaid, Mohd Ahmad, Nadeem Aljamal, Mohammed Patel, Sarosh Khan, Asif Dept. of Computer Science and Engineering Integral University Lucknow India Dept. of Electronics and Communication Engg. Goel Institute of Technology and Managment Lucknow India School of Engineering University of Bridgeport United States Integral Robotics Lab Dept. of Computer Application Integral University Lucknow India

ISBN: (纸本)9798350374933

The main objective of this paper is to design an IoT based truck wheel temperature monitoring system using Arduino board with the aim to overcome endanger and raise the safety measures for truck and goods. By designing and implementing a temperature-detecting system, we can detect the temperature of the wheels trucks. By the use of such detecting device we can prevent the major problem associated with wheel’s temperature and may avoid the major accidents. This monitoring system senses the temperature data of the wheel and transmits through the Wi-Fi module. In addition, it upgrades Thingspeak channel that can collect the data and it can easily be accessed by the transport agency and the truck driver. This can further be analysed using any computer system or mobile with internet connectivity anywhere across the globe to take real-time decision. The core function of the proposed detecting system is to monitor the real- time value of truck wheel temperature and to inform the concerned people. © 2024 IEEE.

关键词： Wi-Fi

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User Interface and User Experience: A Review on Evaluation, Design and Research Methodology for Mobile applications 13

User Interface and User Experience: A Review on Evaluation, ...

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13th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2022

作者： Hosamani, Sanjana Dept. of Master of Computer Application KLS Gogte Institute of Technology Belagavi India

ISBN: (纸本)9781713857938

The usefulness of mobile phones has expanded significantly in the latest years permitting customers to carry out extra tasks in a mobile context. User Interface and User Experience play an essential position withinside the improvement of mobile applications nowadays. Specially to design the interface for aged people's usage. It allows to optimize the design and enhance it to be user-friendly. User Interface (UI) and User Experience (UX) elaborates a set of concepts, the workflow of design thinking and usability principles. The Graphical User Interface (GUI) of mobile phones are based on a certain set of principles, evaluation and research methodology. This research paper sums up various concepts of UI/UX such as evaluation, design, usability principles and also some common usability issues in the mobile applications of certain sectors. © Grenze Scientific Society, 2022.

关键词： Graphical user interfaces

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HCB Machine Learning Approach For Movie Recommendation System 6

HCB Machine Learning Approach For Movie Recommendation Syste...

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6th International Conference on Intelligent Computing and Control Systems, ICICCS 2022

作者： Gourammolla, Samheeta Gokila, S. Hindustan Insititute of Technology and Science Dept. of Computer Application Chennai603103 India

ISBN: (纸本)9781665410359

The Recommendation System (RS) is a very powerful technique which supports the user to derive decision quickly. The RS is essential in any business model like B2B, B2C and C2C. The user wants to get the quality and essential information suitable to perception in an entertainment which falls on C2C category. The recommendation system can achieve this by filtering the essential choices from the large amount of rating of given by other users. The Hybrid Collaborative-Based (HCB) recommendation system in proposed work is experimented. The proposed experimental results on movie rating and review rating with movie lens data set shows high result than SVD, KNN and Co-Clustering Machine Learning (ML) algorithms. © 2022 IEEE.

关键词： Collaborative filtering

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An Effective Prediction of Rainfall Using Machine Learning Technique 5

An Effective Prediction of Rainfall Using Machine Learning T...

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5th IEEE International Conference on Electrical, computer and Communication Technologies, ICECCT 2023

作者： Rana, Nisha Guru Prasad, M. Sharma, Ashutosh Pratap, M.S. Anand Kumar, M. Aditya Pai, H. Dept. of Computer Science and Engineering Rishikesh India Graphic Era Deemed University Dept. Computer Science and Engineering Dehradun India Rishikesh India School of Computing and Information Technology Reva University Bengaluru India Dept. of Computer Application Dehradun India Dept. of Computer Science and Engg. Dehradun India

ISBN: (纸本)9781665493604

Climatic information such as temperature, humidity, and precipitation are useful for agriculturists, businesses, researchers, and the government. Estimating precipitation is a major factor that affects the environment and is one of the most important aspects of meteorological science. In this study, factual approaches and machine learning methods are used to estimate and forecast meteorological parameters for the government. Estimating precipitation is a major factor that affects the environment and is one of the most important aspects of meteorological science. Approaches are used to forecast and estimate precipitation. Daily observations were used as part of the experiment. Validation of results using real-world data is used to check the accuracy of forecasting model experimentation. The experimental results show that distribution, correlation, line-plots, and neural networks perform well for forecasting meteorological characteristics and have the best classification accuracy when compared to other types of machine learning methods for precipitation forecasting. © 2023 IEEE.

关键词： Machine learning

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Development of Cloud Centric Healthcare Monitoring System for Cardiac Patients embedded in IoT Platform 11

Development of Cloud Centric Healthcare Monitoring System fo...

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11th International Conference on Emerging Trends in Engineering and technology - Signal and Information Processing, ICETET - SIP 2023

作者： Mishra, Adarsh Ravi Mishra, Ravi Shukla, Ragini Dr. C.V. Raman University Dept. of Computer Application and Information Technology Bilaspur India G H Raisoni Institute of Engineering and Technology Dept. of Electronics and Telecommunication Nagpur India

ISBN: (纸本)9798350348422

In terms of profit and employment, the Indian economy's healthcare sector has emerged as one of the most significant sectors. The Indian healthcare sector is experiencing rapid growth due to improved coverage, expanded functionalities and services and increased public and private spending. Due to which the life expectancy has increased dramatically. As the population of individuals rises in many societies, the number of people affected by chronic diseases, such as diabetes, cardiovascular disease, obesity, and so on, rises as well. As a result, Internet of Things (IoT)-based personalised healthcare is becoming a more significant idea.. This paper's main goal is to illustrate a cardiac patient e-health data acquisition, transfer, and monitoring system. The smart health monitoring system prototype uses a wireless sensor network to measure various health data, which are then sent to the concerned individual through GPRS. These parameters are also saved in Amazon cloud services for future use. © 2023 IEEE.

关键词： Internet of things

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