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Breast Cancer Classification Using ANN and ML Techniques 7

Breast Cancer Classification Using ANN and ML Techniques

引用

2023 7th International Conference On Computing, Communication, control And Automation, ICCUBEA 2023

作者： Bhuta, Nishi Raut, Roshani Pimpri Chinchwad College of Engineering Dept. of Computer Engineering Pune India Pimpri Chinchwad College of Engineering Dept. of Information Technology Pune India

ISBN: (纸本)9798350304268

Millions of individuals throughout the world are impacted by the significant health issue known as breast cancer. To improve patient outcomes, breast cancer must be identified early and correctly diagnosed. In this study, we used TensorFlow to create an artificial neural network (ANN) model to categorise breast cancer. To compare with our ANN model, we also employed seven alternative ML classifiers as basis models, including Line SNM, LR, KNN, NB, DT, RF, and Gradient Booster. For each model, we determined the precision, accuracy, recall, and F1 score. To improve performance, we ensembled all the classifiers. Each classifier's accuracy was analysed and contrasted, and the classification performance was demonstrated via a confusion matrix. Our results show that the ANN have given an accuracy of 97% and the ML model achieved the highest accuracy of 98.8% using LR, followed by SVM with 97.7%, KNN with 96.7%, RF with 95.6%, DT with 95.4%, NB with 95.3% and Gradient Booster with 94.2% The ensemble model gave the overall accuracy to 97.7%. These findings indicate that our proposed ANN model and ensemble approach are effective but LR gave the highest accuracy in classifying breast cancer and can serve as a useful tool for clinicians and researchers in this field. © 2023 IEEE.

关键词： Artificial neural network (ANN) Breast cancer Ensemble Learning ML

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Application of Long Short Term Memory Network in Mine Leakage Protection Line Selection 6

Application of Long Short Term Memory Network in Mine Leakag...

引用

6th International Conference on Computer information Science and Application technology, CISAT 2023

作者： Guodong, Zhang Fuqiang, Yao Haitao, Pu Shuaishuai, Zhang Dept. of Electrical Engineering and Information Technology Shandong University of Science and Technology Jinan250031 China

ISBN: (纸本)9781510668546

The single-phase grounding of underground cables(feeder lines) in coal mines causes leakage, which poses great risks to safety production. A method for selecting faulty lines using long and short term memory neural network（LSTM） is proposed to address this issue. Firstly, a model of the coal mine underground power supply system is built, and a large number of simulation data are generated for training the neural network. Secondly, the LSTM neural network model is built and trained by using the keras platform. Finally, the trained LSTM neural network is tested using the new simulation data generated in various operating conditions. The results indicate that the LSTM neural network can quickly and effectively distinguish the faults of bus or line, and select the faulty line correctly. This method is not affected by voltage phase angle, grounding resistance value, voltage level, number of feeder lines, and intermittent arc, thus proving its effectiveness. © 2023 SPIE.

关键词： Coal mines

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Methods for Developing Effective Models of Biomedical Processes in MATLAB 17

Methods for Developing Effective Models of Biomedical Proces...

引用

17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer engineering, TCSET 2024

作者： Kolisnyk, Kostyantyn Kolisnyk, Viktoriia Wik, Torsten National Technical University 'Kharkiv Polytechnic Institute' Dept. Industrial and Biomedical Electronics Kharkov Ukraine Kharkiv National University of Radio Electronics Dept. Media Engineering and Information Radioelectronic Systems Kharkiv Ukraine Institutionen for elektroteknik Chalmers tekniska hogskola Dept. Systems and Control Technology Electrical Technology Gothenburg Sweden

ISBN: (纸本)9798331520564

Mathematical modeling in the study of dynamic processes in biomedicine is currently widely used. The use of mathematical statistics and formal logic methods in the analysis of complex biomedical processes is especially important for increasing the efficiency of biomedical research. Taking into account the established growth of the technical base of research, the development of new technologies and technical means for obtaining and processing statistical biomedical information, the use of mathematical modeling methods is a fairly promising direction in scientific and practical work. In this paper the authors studies the possibility of improving the quality of biomedical process modeling using the MATLAB software environment. The research was carried out on real statistical material obtained by the authors during a full-scale experiment to study the impact of a complex of external factors on patients. The results obtained in this work can be used in the implementation of scientific and applied research of biomedical processes. © 2024 IEEE.

关键词： MATLAB

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Note on 'RAKS: robust authentication and key agreement scheme for satellite infrastructure'

Note on 'RAKS: robust authentication and key agreement schem...

引用

2023 International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2023

作者： Tsai, Chun-Chieh Sun, Chin-Yu Yang, Shih-Hsuan National Taipei University of Technology Dept. of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350324174

Low Earth orbit (LEO) satellites play an important role in modern communication systems. Recently, Khan et al. [1] designed a robust authentication and key agreement scheme (RAKS) for LEO satellite communication. They also performed security analysis of RAKS to verify the declared safety. Upon careful examination, however, we discovered several security flaws in RAKS, including insufficient information for user identification, vulnerability to elaborate DoS attacks, and inaccurate estimation of computational costs. In this paper, we highlight these flaws and suggest potential modifications to improve the scheme. © 2023 IEEE.

关键词： Satellites

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A Blockchain Proposal - Proof of Synergy 10

A Blockchain Proposal - Proof of Synergy

引用

10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer engineering, UPCON 2023

作者： Ramesh, Dhanesh Kumar, Niharika Prasanna Srinivasan, Kishore Shashidhara, Pranav Belavadi Rv Institute of Technology & Management Dept. Information Science & Engineering Bengaluru India

ISBN: (纸本)9798350382471

In the realm of contemporary blockchain mechanisms, inherent flaws persist in bandwidth, security, speed, and reliability. Addressing these issues, the research introduces a pioneering approach that meticulously balances and enhances all the solutions to all these issues simultaneously. This solution is designed to accommodate computers of varying bandwidth capacities, fostering inclusivity and accessibility. Moreover, it empowers every computer to contribute resources, fostering a collaborative and community-driven ecosystem. Security, a paramount concern, is fortified through a novel Zero Knowledge Proof method, coupled with randomized key algorithms, ensuring robust protection against potential threats. Simultaneously, the system achieves remarkable speed improvements, promising seamless transactions and data processing. Furthermore, this research opens doors to an era of complete decentralization, where no single entity wields absolute control. Emphasizing transparency and fairness, with a methodology that redefines the landscape of blockchain technology. In addition, the blockchain technology revolutionizes certificate verification, ensuring authenticity and security. © 2023 IEEE.

关键词： Bandwidth Blockchain Reliability Security Speed

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Wireless Power Transfer system with Flying Capacitor Converter for Current Harmonics Reduction

Wireless Power Transfer system with Flying Capacitor Convert...

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2023 IEEE Energy Conversion Congress and Exposition, ECCE 2023

作者： Kusui, Rintaro Kusaka, Keisuke Itoh, Jun-Ichi Nagaoka University of Technology Dept. of Electrical Electronics and Information Engineering Nagaoka Japan

ISBN: (纸本)9798350316445

A wireless power transmission system using a flying capacitor converter (FCC) as a primary power source has been proposed to reduce current harmonics that cause low-order harmonic radiation noise. However, the diode rectifier on the secondary side applies a square wave voltage to the secondary transmit coil. Current harmonics are not sufficiently reduced due to the harmonic content of the square wave. This paper proposes a WPT system with FCC on both the primary and secondary sides in order to reduce voltage harmonics applied to both sides of the transmission coil. The proposed system reduces the odd-order harmonics of the primary and secondary currents by more than 25 dB compared to the conventional system, as confirmed by simulations. In particular, the 3rd harmonic is reduced by 37.2 dB, and the 5th harmonic is reduced by 35.1 dB. © 2023 IEEE.

关键词： Current harmonics Flying-capacitor converter Radiation noise Wireless power transfer system

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Explainability to Business: Demystify Transformer Models with Attention-based Explanations 2

Explainability to Business: Demystify Transformer Models wit...

引用

2nd International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2023

作者： Thiruthuvaraj, Rajasekhar Jo, Ashly Ann Raj, Ebin Deni Indian Institute of Information Technology Dept. of Computer Science & Engineering Kottayam India

ISBN: (纸本)9781665456302

Recently, many companies are relying on Natural Language Processing (NLP) techniques to understand the text data generated daily. It has become very critical to deal with this data because finding the sentiments of text and summarizing them will help the company understand the pain points of the customers posting reviews on social media or understand the experience of the customer. These requirements have increasingly demanded many advanced algorithms to deal the text data. The introduction of Transformers led to businesses adopting NLP methods more and more to keep up with their needs. Models like Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformers (GPT), state-of-the-art results were achieved with billions of parameters learned. Although these advancements improved the accuracy and expanded the use of algorithms to a wide range of NLP tasks like language translation, text summarization, and language modeling. Businesses are more interested in the Explainability of the model compared to its accuracy. Explainable Artificial Intelligence (XAI) plays an important role to comprehend the complexities of the model as well as the influence of weights on predictions. In this paper, the complexities of the transformer model are unraveled by presenting a straightforward method for computing explainable predictions. The DistilBERT model is chosen as an example to implement the explainable system due to its lighter nature. Combining the strengths of a Posthoc expla-nation with those of a self-learning neural network, the method makes it simple to scale it to other algorithms to implement. With technologies like python, PyTorch, and Hugging Face, a detailed step-by-step algorithmic computation is demonstrated to explain the predictions from the attention-based explanations. © 2023 IEEE.

关键词： Forecasting

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Rainfall Prediction using Artificial Neural Network with Forward Selection Method

Rainfall Prediction using Artificial Neural Network with For...

引用

2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications technology, IAICT 2023

作者： Najib, Faisal Yusriadi Mustika, I Wayan Sulistyo, Selo Universitas Gadjah Mada Dept. of Electrical Engineering and Information Technology Yogyakarta Indonesia

ISBN: (纸本)9798350313635

The weather has become an important part of people's daily activities;therefore, many people need faster, more complete, and more accurate information about its condition. Accurate weather predictions can be used to solve problems arising from weather effects. Compared to other methods, the Artificial Neural Network (ANN) method is deemed more efficient in fast computing and is able to handle unstable data in terms of weather forecast data. However, ANN has limitations in studying classification patterns if the dataset has large data and high dimensions. To manage this limitation, a feature selection method is needed to enable the ANN to produce accurate predictions. Several experiments were carried out to obtain the optimal architecture and produce accurate predictions. The proposed method only reduces the accuracy value to less than 1% and the loss value to less than 0.01 in both tested datasets. With these results, it can be said that the proposed method is feasible to be used as an improved method for the ANN algorithm. © 2023 IEEE.

关键词： Weather forecasting

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Transfer Matrix for Space-charge Analysis of Insulating Systems with Complex Geometries 4

Transfer Matrix for Space-charge Analysis of Insulating Syst...

引用

4th IEEE International Conference on Electrical Materials and Power Equipment, ICEMPE 2023

作者： Li, Xiaoxin An, Yeongguk Kawashima, Tomohiro Murakami, Yoshinobu Hozumi, Naohiro Toyohashi University of Technology Dept. Electrical and Electronic Information Engineering Toyohashi Japan

ISBN: (纸本)9798350334678

Time resolved space charge measurements by acoustic methods, such as the pulsed electroacoustic (PEA) method, have traditionally been performed on acoustically uniform plaque specimens. However, there is a growing demand to use this method for more complex insulating systems, such as laminated specimens. Since it is difficult to ensure acoustic matching in such specimens, artifacts due to multiple reflections are expected in addition to direct waves, which hinder the analysis. To solve the above problem, it is necessary to accurately define the transfer matrix, which is a sequence of transfer functions from different sources in the insulating system to the acoustic detection point. In the presentation, we will define a transfer matrix that takes into account multiple reflections in addition to sound velocity, acoustic impedance, and frequency-dependent attenuation of acoustic propagation. The signal component originating from a single source contains an infinite number of reflections in addition to the direct component, but the signal attenuates during repeated multiple reflections. For this reason, the width of the time window required for measurement should be set to a finite value. Based on this matrix, we will investigate how to calculate accurate charge distribution by means of the time-domain deconvolution. By defining a transfer matrix with multiple reflection components, space-charge analysis of insulating systems with acoustic mismatch can be performed more accurately. © 2023 IEEE.

关键词： Acoustic impedance

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From GPS to Maps: Path Reconstruction Techniques for Understanding People Mobility with Low-Sampling-Rate Data 3

From GPS to Maps: Path Reconstruction Techniques for Underst...

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3rd International Conference on Intelligent Cybernetics technology and Applications, ICICyTA 2023

作者： Rakhman, Arkham Zahri Nugroho, Lukito Edi Widyawan, Widyawan Utami, Nurul Khairiza Universitas Gadjah Mada Dept. of Electrical Engineering and Information Technology Yogyakarta Indonesia

ISBN: (纸本)9798350394559

Urban mobility is a critical aspect of city planning and transportation management, with the Global Positioning System (GPS) playing an essential role in analyzing and understanding patterns of human movement. Particularly using smartphones, GPS provides highly detailed digital trace data, enabling in-dept. analysis of human movement behavior. However, there are significant challenges when working with GPS datasets that have a low frequency, which often occurs due to storage capacity limitations or data transmission costs. This study explores methodologies for reconstructing movement paths from low-frequency GPS datasets. The process includes several key steps: data pre-processing involving cleaning and normalizing data;aligning GPS data with existing road networks using the nearest-neighbor KD-Tree algorithm;and accurate path reconstruction. In addition, the study develops a method for time interpolation estimation to determine movement times between the aligned coordinate points. The findings of this research indicate that with the proposed approach, movement paths can be reconstructed effectively and accurately, even from data with low sampling frequencies. This approach promises a wide potential application, ranging from transportation infrastructure planning to the development of more sophisticated navigation systems. With ongoing research, the integration of additional sensors and machine learning techniques is anticipated to further enhance the accuracy and utility of this methodology. © 2023 IEEE.

关键词： Global positioning system

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