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Spam Email Clustering by Ordered Pair of Modality: 2023 15th International Congress on Advanced Applied Informatics Winter (IIAI-AAI-Winter) 15

Spam Email Clustering by Ordered Pair of Modality: 2023 15th...

引用

15th International Congress on Advanced Applied Informatics Winter, IIAI-AAI-Winter 2023

作者： Matsuda, Takeshi Fujimaki, Takeshi Sonoda, Michio Hannan University Dept. Management and Information Technology Osaka Japan Chuo University Dept. Information and System Engineering Tokyo Japan National Cyber Training Center Nict Tokyo Japan

ISBN: (纸本)9798350383829

Cyber-attacks that deceive people in various ways, such as phishing scams that exploit personal information by pretending to be a real service, are gaining momentum. Scam email sometimes includes important keywords that are cleverly used to deceive people, but not always. This study focused on the modality representation contained in scam emails that make people uneasy and defined order pair of modality representation of 100 dimensions. Furthermore, we applied a dimensionality reduction algorithm to verify the accuracy of unsupervised learning of scam and normal em ails. © 2023 IEEE.

关键词： Electronic mail

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Methodology for Creating Annotated Datasets of Biological Objects in Microscopic Images 5

Methodology for Creating Annotated Datasets of Biological Ob...

引用

5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Kovalenko, Sergii Kovalenko, Svitlana Kutsenko, Alexander Godlevskyi, Mykhailo Severin, Valery Kovalenko, Anton Dept. of System Analysis and Information-Analytical Technologies National Technical University "KhPI" Kharkiv Ukraine Dept. of Software Engineering and Management Intelligent Technologies National Technical University "KhPI" Kharkiv Ukraine

ISBN: (纸本)9798350384499

The study presents a methodology for automatically creating an annotated dataset for further use in training neural networks. The method is based on the Crisp-DM framework and consists of 6 stages: business understanding, data understanding, data preparation, modeling, evaluation, deployment, which has been modified due to the specifics of computer vision tasks. As a modeling method, the k-means method is proposed, which is applied to the normalized area and average color data of a given object. The approach is tested for creating an annotated dataset for recognizing and localizing cells of different types in blood smear images. The output is a dataframe with the columns file_name, xmin, ymin, xmax, ymax, type, area, which represent the file name, the coordinates of the upper left and lower right points of the bounding boxes, the cell type, and its area. Using these parameters and image processing libraries it is easy to add bounding boxes to the original images. The resulting annotated dataset is analyzed. Metrics were calculated and a loss matrix was constructed. All calculations were performed using the Python programming language and the Pandas, numpy, openCV, and matplotlib libraries. ©2024 IEEE.

关键词： Image segmentation

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Sentiment Analysis for Curriculum of Independent Learning Based on Naïve Bayes with Laplace Estimator 2

Sentiment Analysis for Curriculum of Independent Learning Ba...

引用

2nd International Conference on information Technology Research and Innovation, ICITRI 2023

作者： Ariefah, Amelia Widodo Nugraheni, Murien State University of Jakarta Dept. of Informatics and Computer Engineering Education Jakarta Indonesia State University of Jakarta Dept. of Information System and Technology Jakarta Indonesia

ISBN: (纸本)9798350324945

Curriculum changes have a significant impact on the field of education in Indonesia, especially in universities. This is because the curriculum is used as a means to achieve the goals of educational success as well as guidelines in the implementation of teaching at every level of education. This study aims to determine public sentiment regarding the implementation curriculum of independent learning (MBKM) through Twitter based on Naïve Bayes with Laplace Estimator. Tweet search results use the keywords 'kurikulum mbkm' and 'mbkm'. The data used in this study amounted to 2500 tweet data which will be divided into 2000 data as training data with details of 1000 positive tweets and 1000 negative tweets and 500 data as testing data. The results showed the performance of Naïve Bayes using Laplace Estimator which resulted in an accuracy value of 80.20%, precision value of 82.00%, and recall value of 79.00%. Meanwhile, the performance of Naïve Bayes without Laplace Estimator resulted in an accuracy value of 77.00%, precision value of 80.00%, and recall value of 74.00%. Naive Bayes with Laplace Estimator reached the highest value in all metrics. © 2023 IEEE.

关键词： Curricula

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Comparative and Predictive Analysis of Kazakhstan's Sectoral International Trade 5

Comparative and Predictive Analysis of Kazakhstan's Sectoral...

引用

5th IEEE International Conference on Communications, information, Electronic and Energy systems, CIEES 2024

作者： Kuanyshbekov, Yermakhan Bissembayev, Alibek Iliev, Teodor Kang, Jeong Won Mukasheva, Assel Kazakh-British Technical University School of Information Technology and Engineering Almaty Kazakhstan University of Ruse Dept. of Telecommunications Ruse Bulgaria Korea National University of Transportation Dept. of Transportation System Engineering Uiwang-Si Korea Republic of

ISBN: (纸本)9798350352863

International trade is one of the main aspects of the global economy, which consists of imports and exports. The study presents sectoral analysis of Kazakhstan's trade for the 2011-2021 period, where provided comparative analysis to explore current dynamics, to reveal insights and predictive analysis to make forecasts and understand the future trend. Accordingly, these types of experiment give efforts aimed at analysis and statistics of our country, as well as at diversifying the current state. In the research comparative analysis provided with the help of visualization and statistical analysis, predictive analysis by means of following machine learning models, Linear Regression, Decision Trees, Random Forests, Gradient boosting, Support Vector Regression. In research estimated the use of production and import resources in 8 sectors, mainly in the manufacturing industry. The results show that the highest export requirements are imposed in certain sectors such as mineral products, fuel and energy products, metals and products made from them. Along with the result of the machine learning models' performance and prediction for the next three year. © 2024 IEEE.

关键词： analysis export import international trade machine learning

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Synthesis of Model Predictive control for an Electrohydraulic Servo system Using Orthonormal Functions 5

Synthesis of Model Predictive Control for an Electrohydrauli...

引用

5th IEEE International Conference on Communications, information, Electronic and Energy systems, CIEES 2024

作者： Mihalev, Georgi Yordanov, Stanimir Ormandzhiev, Krasimir Stoycheva, Hristina Todorov, Todor Technical University of Gabrovo Dept. of Automation Information and Control Systems Gabrovo Bulgaria Technical University of Gabrovo Dept. of Power Engineering Gabrovo Bulgaria Technical University of Gabrovo Dept. of Comunication Technique and Technologies Gabrovo Bulgaria

ISBN: (纸本)9798350352863

The paper presents the implementation of a Continuous-Time Model Predictive control (CMPC) regulator for controlling an electrohydraulic servo system. The control object is a test bench consisting of three modules and a PC-based data acquisition and control system. The system is modeled in state-space form, accounting for parametric uncertainties. The synthesis of the model predictive controller is performed by approximating the control signal using Laguerre orthonormal functions. The article includes mathematical formulas and relationships that illustrate the modeling approach. Simulations and robust analysis of the closed-loop system are conducted. Through a real-time control system, experimental data and graphs are obtained, demonstrating the performance and optimality of the synthesized control strategy. © 2024 IEEE.

关键词： Model predictive control

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An earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning model

An earlier serial lactate determination analysis of cardiac ...

引用

2023 International Conference on Intelligent systems for Communication, IoT and Security, ICISCoIS 2023

作者： Mohammed, Mehmood Ali Mohammed, Murtuza Ali Mohammed, Vazeer Ali Logeshwaran, J. Jiwani, Nasmin University of the Cumberlands Dept. of Information Technology WilliamsburgKY United States Lewis University Dept.of Computer Information System IL United States Sri Eshwar College of Engineering Dept. of Electronics and Communication Engineering Coimbatore India

ISBN: (纸本)9798350335835

In general, cardiac arrest results in an inability to pump enough blood for the body's needs. Through this, the organs and tissues get enough oxygen and nutrients for their metabolic needs, and excess fluid accumulates. This further increases the severity of the patient's problems. Cardiac arrest is the leading cause of hospitalization in people over 65 and is therefore considered a significant public health problem. It is a pathology linked to an increase in average life expectancy, and its incidence is increasing every year due to the general ageing of the population. In this paper, an earlier serial lactate determination analysis of cardiac arrest patients using a medical machine learning algorithm. It can occur following an episode of cardiac arrest or inadequate treatment of chronic diseases, including diabetes and hypertension. Adopting lifestyle habits that prevent the onset of these conditions is an essential strategy for preventing heart failure. The proposed approach has achieved 91.58% accuracy, 87.96% precision, 84.62% recall, and 85.23% F1-score results compared to other methods. © 2023 IEEE.

关键词： Tissue

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control of Deterministic Chaotic Modes in Power systems

Control of Deterministic Chaotic Modes in Power Systems

引用

2023 IEEE International Conference on Smart information systems and Technologies, SIST 2023

作者： Beisenbi, Mamyrbek Satpayeva, Ainur Mussabayeva, Shugla Mussina, Gulnara Tlegen, Meruert L.N. Gumilyov Eurasian National University Dept. of System Analysis and Control Astana Kazakhstan Astana It University Dept. of Computer Engineering Astana Kazakhstan

ISBN: (纸本)9798350335040

The paper examines a new approach to controlling deterministic dynamical chaotic mode of power system with two electric generate-sources. A control law is synthesized in the class of one-parameter structurally stable mappings from catastrophe theory. Analytical calculations and a numerical experiment in MatLab showed that the proposed system excludes the generation of a deterministic chaotic mode for any changes in the uncertain system parameters. The study of the control system is carried out by the gradient-velocity method Lyapunov vector functions © 2023 IEEE.

关键词： Uncertainty analysis

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Exploring User Experience and Challenges with Mobile Wallet Adoption in Emerging Markets 2

Exploring User Experience and Challenges with Mobile Wallet ...

引用

2nd International Conference on Technology Innovation and Its Applications, ICTIIA 2024

作者： Priandito Lutfiani, Ninda Yusuf, Natasya Aprila Goh, Thomas Sumarsan Madani, Muchlisina University of Raharja Dept. of Informatics Engineering Tangerang Indonesia University of Raharja Dept. of Digital Business Tangerang Indonesia University of Raharja Dept. of Information Systems Tangerang Indonesia Universitas Methodist Indonesia Dept. of Management Medan Indonesia University of Raharja Dept. of Computer System Tangerang Indonesia

ISBN: (纸本)9798350351613

This study explores user experiences and challenges in mobile wallet adoption in emerging markets using the UTAUT model. These markets face rapid technological growth alongside infrastructural and economic challenges. The research examines how factors like performance expectancy, effort expectancy, social influence, and facilitating conditions influence adoption. Data from 80 mobile wallet users was collected through an online survey and analyzed using SmartPLS 4.1.0.6. The results show that performance and effort expectancy predict behavioral intention, while facilitating conditions affect actual usage. The study highlights the role of infrastructure in supporting adoption and validates the UTAUT model's relevance in less developed regions. These findings provide insights into enhancing financial inclusion in emerging markets. © 2024 IEEE.

关键词： Emerging Markets Mobile Wallet Technology Adoption User Experience UTAUT

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The Comparison Study of Regression Models (Multiple Linear Regression, Ridge, Lasso, Random Forest, and Polynomial Regression) for House Price Prediction in West Nusa Tenggara 5

The Comparison Study of Regression Models (Multiple Linear R...

引用

5th International Conference on Advancement in Data Science, E-Learning and information systems, ICADEIS 2023

作者： Putri, Mindi Richia Wijaya, I Gede Pasek Suta Praja, Fritzie Primananda Adi Hadi, Abdul Hamami, Faqih University of Mataram Dept. Magister of Information Technology Mataram Indonesia Telkom University School of Industrial and System Engineering Indonesia

ISBN: (纸本)9798350303414

Predicting house prices is essential in the real estate industry as it enables stakeholders to make informed decisions. Accurately predicting house prices is paramount in facilitating buying and selling transactions, aiding property valuation, and providing valuable insights for investors and homeowners. This research compares five regression models, namely Multiple Linear Regression, Ridge, Lasso, Random Forest, and Polynomial Regression, to predict house prices in West Nusa Tenggara Province. These considered building area, land area, number of bedrooms, and bathrooms. The data was taken from the public website, namely Lamudi Website, and was collected using a web scraping method and then processed using Machine Learning. By considering factors such as building area, land area, number of bedrooms, and bathrooms, the study aimed to determine which model delivered the most accurate predictions and exhibited a low error rate. This research used various metrics such as R-Squared, Root Mean Square Error (RMSE), and Cross-Validation to measure the accuracy of these models. In this study, the R-Squared and RMSE methods showed that Multiple Linear Regression and Lasso Regression were the best models with the same R-Squared and RMSE values, namely R-Squared = 0.6947 (69.47%) and RMSE = 2863760831. Meanwhile, the RMSE (Cross-Validation) method shows that Random Forest Regression is the best model with a value of 3343572297. These research outcomes have the potential to provide valuable guidance to the local community in making informed decisions regarding property transactions in West Nusa Tenggara. © 2023 IEEE.

关键词： Multiple linear regression

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Classification of Skin Lesions using PyQt5 and Deep Learning Methods 5

Classification of Skin Lesions using PyQt5 and Deep Learning...

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5th IEEE International Conference on Communications, information, Electronic and Energy systems, CIEES 2024

作者： Koishiyeva, Dina Bissembayev, Alibek Iliev, Teodor Kang, Jeong Won Mukasheva, Assel Almaty University of Power Engineering and Telecommunications Dept. of Information Technology Almaty Kazakhstan Kazakh-British Technical University School of Information Technology and Engineering Almaty Kazakhstan University of Ruse Dept. of Telecommunications Ruse Bulgaria Korea National University of Transportation Department of Transportation System Engineering Uiwang-Si Korea Republic of

ISBN: (纸本)9798350352863

This study presents the OncoScan system designed to assist dermatologists in classifying skin diseases using an improved DenseNet121 model. The system was tested on the large HAM10000 dataset of over 10,000 images of skin lesions in seven categories. The DenseNet121 model, characterized by dense connectivity and transient layers, was compared with the InceptionV3 and EfficientNetB7 models. The results demonstrated the superiority of the DenseNet121 model, with an accuracy of 86.04% and an AUC of 96.32%. The OncoScan interface, developed using PyQt5, supports multilingual functionality including English, Russian, and Kazakh, and offers image processing tools. The system's ability to handle image processing and classification with ease makes it a valuable asset for dermatologic diagnostics. © 2024 IEEE.

关键词： denseNet121 pyqt5 skin disease transient layers

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