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12th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2023

作者： Guslendra Yuhandri Defit, Sarjon Universitas Putra Indonesia Yptk Computer Science Faculty Department of Information System Padang Indonesia Universitas Putra Indonesia Yptk Computer Science Faculty Department of Information Technology Padang Indonesia

ISBN: (纸本)9798350341102

CT-Scan is a computer-based imaging technology, but it presents certain weaknesses, including interpretation challenges, lengthy analysis times, and visualization limitations. The progress in digital image processing science empowers computers to identify objects through recognizing distinctive features. To facilitate further data processing, an image cropping method is essential to narrow down the area of interest, as not all parts of an object require processing. However, using a rectangular cropping method can lead to a reduction in image size, potentially compromising image quality and causing blurring when displayed on the same axes. To uphold image quality and avert blurring, maintaining the cropped image's size becomes crucial. The developed rectangular cropping method successfully preserves the cropped image's size by adjusting the intensity values of pixels surrounding the cutting point. Coordinate points within the cropping rectangle delineate the region where pixel intensity values are modified. In this study, input images were sourced from CT-scan images of M. Djamil Hospital, Padang, West Sumatra, in jpg format. The developed algorithm underwent testing using the Matlab program, employing the rectangle method for image cropping to ensure the image size remained constant. The study's outcomes reveal no disparity in the number of pixels obtained when employing the developed rectangular cropping method. Based on the experiments carried out in this study using 8 input images that were successfully maintained, the size of the image from the cropped image was 8 images and 0 images were unsuccessful, so the accuracy obtained in this study was 100%. © 2023 IEEE.

关键词： Image quality

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Research and Development of Enterprise Data Warehouse Based on SAP BW Modeling

Research and Development of Enterprise Data Warehouse Based ...

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

作者： Turken, Gulzat Naizabayeva, Lyazat Satymbekov, Maxatbek Abdiakhmetova, Zukhra Al-Farabi Kazakh National University Department of Computer Science Almaty Kazakhstan International Information Technology University Department of Information System Almaty Kazakhstan

ISBN: (纸本)9798350335040

The data warehouse is based on the development of relational databases, parallel processing and distributed processing technologies, as well as online analytical processing technologies. SAP BW is widely used in many enterprise data warehouses. It can issue reports of enterprises at the group level, manage the group's business operations, help find the laws and trends behind the performance of corporations and ultimately provide decision-making support for decision makers of enterprises. Therefore, how to use the SAP BW model architecture to better realize enterprise data warehouses is one of the hot topics in the data warehouse industry today. For a large corporation, its branches and subsidiaries have deployed multiple sets of enterprise data warehouses. At the same time, because there are multiple sets of data warehouse systems, when the data model needs to be modified at the group level, the data model of the branch also needs to be modified accordingly, and the flexibility of maintenance is poor. Finally, every time the corporation needs to upgrade the version of the data warehouse, it needs to maintain and upgrade the version of the data warehouse of each branch and the maintenance cost is high. Therefore, how to integrate multiple sets of data warehouses distributed in various subsidiaries into a corporation enterprise data warehouse by designing the model hierarchy, so as to ensure the reliability of data, enhance the flexibility of model modification and reduce the cost of data warehouse. This paper completes the design of an enterprise data warehouse of a large corporation, which can be used for the summary and collation of data from multiple branches such as finance and sales of a corporation, effectively improving the efficiency of data utilization and ensuring the authenticity of data. At the same time, through hierarchical design, the problems of poor flexibility in model modification and high system maintenance costs are solved. © 2023 IEEE.

关键词： Data warehouses

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Enhancing Internet of Vehicles Security: Advanced Intrusion Detection for Threat Detection and Mitigation 1st

Enhancing Internet of Vehicles Security: Advanced Intrusion ...

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1st International Conference on Intelligent systems, Blockchain, and Communication Technologies, ISBCom 2024

作者： Ali, Maged El-Badawy, Hesham Bahaa-Eldin, Ayman Sobh, Mohamed Giza12577 Egypt Cairo Egypt Elsewedy University of Technology Ain Shams University Cairo Egypt Department of Computer and System Engineering Ain Shams University Cairo Egypt

ISBN: (纸本)9783031823763

In this paper, a comprehensive approach to network intrusion detection data using Python is presented. Various techniques including XGB and DQN are discussed, necessitating a preprocessing phase at the beginning. This phase involves fixing data types, handling null and infinite values, dropping unnecessary columns, creating binary labels for threat detection, reducing memory usage, and balancing the dataset. Additionally, feature importance analysis and correlation visualization are explored to identify and drop highly correlated columns. Furthermore, machine learning processes, including data splitting, scaling, and computing class weights, are discussed, followed by the implementation of two machine learning methods: XGBoost and Deep Q-Network (DQN). For XGBoost, performance metrics such as F1-score, recall, precision and support are evaluated to assess model performance. For DQN, insights into its architecture, training objectives, and integration with Gym environment for reinforcement learning tasks are provided. The paper offers a comprehensive guide to preprocessing and machine learning approaches for network intrusion detection datasets, contributing to the advancement of cybersecurity research and applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Network intrusion

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A Hybrid WSVM-Levy Approach for Energy-Efficient Manufacturing Using Big Data and IoT

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computers, Materials & Continua 2024年第12期81卷 4895-4914页

作者： Surbhi Bhatia Khan Mohammad Alojail Mahesh Thyluru Ramakrishna Hemant Sharma School of Science Engineering and EnvironmentUniversity of SalfordManchesterM68HDUK University Centre for Research and Development Chandigarh UniversityMohali140307India Management Information System Department College of Business AdministrationKing Saud UniversityRiyadh11495Saudi Arabia Department of Computer Science and Engineering JAIN(Deemed-to-be University)Bangalore560030India Department of Computer Science and Engineering IES College of TechnologyBhopal462044India

In Intelligent Manufacturing,Big Data and industrial information enable enterprises to closely monitor and respond to precise changes in both internal processes and external environmental factors,ensuring more informed decision-making and adaptive system *** also promotes decision making and provides scientific analysis to enhance the efficiency of the operation,cost reduction,maximizing the process of production and so *** methods are employed to enhance productivity,yet achieving sustainable manufacturing remains a complex challenge that requires careful *** study aims to develop a methodology for effective manufacturing sustainability by proposing a novel Hybrid Weighted Support Vector-based Lévy flight(HWS-LF)*** objective of the HWS-LF method is to improve the environmental,economic,and social aspects of manufacturing *** this approach,Support Vector Machines(SVM)are used to classify data points by identifying the optimal hyperplane to separate different classes,thereby supporting predictive maintenance and quality control in *** Forest is applied to boost efficiency,resource allocation,and production optimization.A Weighted Average Ensemble technique is employed to combine predictions from multiple models,assigning different weights to ensure an accurate system for evaluating manufacturing ***,Lévy flight Optimization is incorporated to enhance the performance of the HWS-LF method *** method’s effectiveness is assessed using various evaluation metrics,including accuracy,precision,recall,F1-score,and *** show that the proposed HWS-LF method outperforms other state-of-the-art techniques,demonstrating superior productivity and system performance.

关键词： Sustainable manufacturing support vector machine random forest levy flight optimization weighted average ensemble

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Fine-Grained Software Vulnerability Detection via Neural Architecture Search 28th

Fine-Grained Software Vulnerability Detection via Neural Ar...

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28th International Conference on Database systems for Advanced Applications, DASFAA 2023

作者： Du, Qianjin Kuang, Xiaohui Li, Xiang Zhao, Gang The Department of Computer Science and Technology Tsinghua University Beijing100084 China National Key Laboratory of Science and Technology on Information System Security Beijing100084 China

ISBN: (纸本)9783031306778

Vulnerability detection methods based on the deep learning have achieved remarkable performance improvements compared to traditional methods. Current deep learning-based detectors mostly use a single RNN or its variants (i.e., LSTM or GRU) to detect vulnerabilities. However, vulnerability detection is a multi-domain problem. Different types of vulnerabilities have different characteristics. Using a single neural network cannot perform well in all types of vulnerability detection tasks. Manually designing a matching neural network for each type of vulnerability detection task not only requires a lot of trials and computational resources but also highly relies on the knowledge and design experience of experts. To address this issue, in this paper, we propose a novel fine-grained vulnerability detection framework named A-DARTS, which is capable of searching for well-performed neural network architectures for different vulnerability detection tasks by introducing neural network architecture search (NAS) techniques. Specifically, we design a more efficient search space to ensure superior neural network architectures can be found by the search algorithm. Besides, we propose an adaptive differentiable search algorithm to search for superior neural network architectures. Experimental results show that searched models consistently outperform all baseline models and achieve significant performance improvements. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Long short-term memory

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Cyclic Transfer Learning for Mandarin-English Code-Switching Speech Recognition

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IEEE Signal Processing Letters 2023年 30卷 1387-1391页

作者： Nga, Cao Hong Vu, Duc-Quang Luong, Huong Hoang Huang, Chien-Lin Wang, Jia-Ching National Central University Department of Computer Science and Information Engineering Taoyuan320 Taiwan Thai Nguyen University of Education Department of Computer Science and Information System Thai Nguyen7905218 Viet Nam Fpt University Department of Information Technology Can Tho900000 Viet Nam National Cheng Kung University Department of Computer Science and Information Engineering Tainan701 Taiwan

Transfer learning is a common method to improve the performance of the model on a target task via pre-training the model on pretext tasks. Different from the methods using monolingual corpora for pre-training, in this study, we propose a Cyclic Transfer Learning method (CTL) that utilizes both code-switching (CS) and monolingual speech resources as the pretext tasks. Moreover, the model in our approach is always alternately learned among these tasks. This helps our model can improve its performance via maintaining CS features during transferring knowledge. The experiment results on the standard SEAME Mandarin-English CS corpus have shown that our proposed CTL approach achieves the best performance with Mixed Error Rate (MER) of 16.3% on testman, 24.1% on testsge. In comparison to the baseline model that was pre-trained with monolingual data, our CTL method achieves 11.4% and 8.7% relative MER reduction on the testman and testsge sets, respectively. Besides, the CTL approach also outperforms compared to other state-of-the-art methods. © 1994-2012 IEEE.

关键词： Speech recognition

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Landscape Patterns in Mining Cities Influenced by Extraction and Terrain Features

Landscape Patterns in Mining Cities Influenced by Extraction...

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2023 International Conference on Data Science, Agents and Artificial Intelligence, ICDSAAI 2023

作者： Madhavan, K. Babu, J.Jai Jaganath Karthikeyan, P. Centre for System Design Chennai Institute of Technology Department of Computer Science & Engineering Tamil Nadu Chennai600 069 India Centre for System Design Chennai Institute of Technology Department of Biomedical Engineering Tamil Nadu Chennai600 069 India

ISBN: (纸本)9798350348910

The combined influence of mining activities and the underlying terrain gradient has caused significant transformations in the landscape patterns of mining cities. The natural topography being altered by mining operations can result in a distinct evolution in the spatial arrangement and ecological dynamics of these cities. Spatial heterogeneities are influenced by factors such as extraction techniques, waste disposal methods, and infrastructure development. The inherent terrain gradient heavily influences the distribution of mining sites and urban expansion patterns. This research underscores the intricate interplay between human-induced activities and natural topographical features in shaping the landscape of mining cities. The development of resilient communities in areas that are evolving due to mining requires a clear understanding of these dynamics for sustainable urban planning, environmental conservation, and community development. © 2023 IEEE.

关键词： Waste disposal

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Al-Biruni Based Optimization of Rainfall Forecasting in Ethiopia

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computer systems Science & Engineering 2023年第6期45卷 2885-2899页

作者： El-Sayed M.El-kenawy Abdelaziz A.Abdelhamid Fadwa Alrowais Mostafa Abotaleb Abdelhameed Ibrahim Doaa Sami Khafaga Department of Communications and Elecronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Department of Computer Science F aculty of Computer and Infomation SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of System Progamming South Ual State UniversityChelyabinsk454080Russia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Rainfall plays a significant role in managing the water level in the *** unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the *** individuals,especially those in the agricultural sector,rely on rain *** rainfall is challenging because of the changing nature of the *** area of Jimma in southwest Oromia,Ethiopia is the subject of this research,which aims to develop a rainfall forecasting *** estimate Jimma's daily rainfall,we propose a novel approach based on optimizing the parameters of long short-term memory(LSTM)using Al-Biruni earth radius(BER)optimization algorithm for boosting the fore-casting accuracy.N ash-Sutcliffe model eficiency(NSE),mean square error(MSE),root MSE(RMSE),mean absolute error(MAE),and R2 were all used in the conducted experiments to assess the proposed approach,with final scores of(0.61),(430.81),(19.12),and(11.09),***,we compared the proposed model to current machine-learning regression models;such as non-optimized LSTM,bidirectional LSTM(BiLSTM),gated recurrent unit(GRU),and convolutional LSTM(ConvLSTM).It was found that the proposed approach achieved the lowest RMSE of(19.12).In addition,the experimental results show that the proposed model has R-with a value outperforming the other models,which confirms the superiority of the proposed *** the other hand,a statistical analysis is performed to measure the significance and stability of the proposed approach and the recorded results proved the expected perfomance.

关键词： Rainfall prediction long short-term memory Al-Biruni earth radius algorithm meta-heuristic optimization

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Automated system for tracking the condition of a patient's feet and selecting specialized insoles 31

Automated system for tracking the condition of a patient's f...

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2023 31st National Conference with International Participation, TELECOM 2023

作者： Ralev, Ivan Georgieva, Despina Hristova, Irinka Koleva, Greta University of Ruse "Angel Kanchev" Department of Computer System and Technology Ruse Bulgaria University of Ruse "Angel Kanchev" Department of Health Care Ruse Bulgaria

ISBN: (纸本)9798350303292

The paper presents a description of a developed system, the purpose of which is to facilitate the work of a medical specialist in monitoring the condition of a person's feet and choosing suitable insoles for him. At the beginning, the problem is considered and an alternative solution is proposed. The developed system is described using UML diagrams, the system interface is also presented. © 2023 IEEE.

关键词： Automation

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A Comparative Analysis of Joomla, Drupal, Wordpress and ***: Exploring Features, Performance, and Suitability

A Comparative Analysis of Joomla, Drupal, Wordpress and ***:...

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2023 IEEE Asia-Pacific Conference on computer Science and Data Engineering, CSDE 2023

作者： Prasad, Ashwin Ashika Sharma, Neeraj Anand Kumar, Anal School of Science and Technology The University of Fiji Department of Computer Science and Mathematics Fiji College of Engineering Science and Technology Fiji National University Department of Computing Sciences and Information System Fiji

ISBN: (纸本)9798350341072

In the dynamic landscape of web development, the judicious choice of platform and structure plays a pivotal role. This comprehensive study conducts a thorough comparison of four prominent web development technologies: ***, Joomla, Drupal, and WordPress. With a primary focus on scrutinizing features, performance, and overall suitability, the research aims to provide valuable insights for developers, businesses, and decision-makers. By objectively evaluating the merits and limitations of each technology, this study seeks to empower stakeholders with essential knowledge, enabling them to make informed decisions at the onset of web development projects. © 2023 IEEE.

关键词： Decision making

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