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Mechanism for Enhancement of Functionality in Deep Echo State Network by Optimizing Leaking Rate 3

Mechanism for Enhancement of Functionality in Deep Echo Stat...

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3rd International Conference on Emerging Techniques in Computational Intelligence, ICETCI 2023

作者： Inoue, Shuichi Nobukawa, Sou Nishimura, Haruhiko Watanabe, Eiji Isokawa, Teijiro Graduate School of Information and Computer Science Chiba Institute of Technology Narashino Japan Yamato University Faculty of Informatics Osaka Japan National Institute for Basic Biology Okazaki Japan Graduate School of Engineering University of Hyogo Himeji Japan

ISBN: (纸本)9798350300604

Deep echo state network (Deep-ESN) model consists of multiple reservoir layers, that can respond to layer-specific different time-scales. This dynamical characteristic leads to enhance performance of ESN. However, neither the design guidelines for the hyperparameters of the network and individual neurons nor the mechanism to produce the diverse dynamical response have been clarified. In this study, we proposed an approach to generate the dynamical responses with different time-scales in each layer by adjusting the leaking rate of neurons. Through the evaluations time-series prediction task for different leaking rates, multiscale entropy analysis for each reservoir layer, and cross-correlation between adjacent layers, we found that when the leaking rate is set to low, the layer-specific dynamics with different time-scales are generated, as well as a mechanism whereby the signal propagates to subsequent layers with a delay, i.e., queue characteristic. These characteristics produce a high memory capacity. Consequently, diverse responses with delay leads to an enhancement of Deep-ESN functionality. © 2023 IEEE.

关键词： Deep learning

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Using Machine Learning to Identify and Categorize Personally Identifiable Information and Payment Card Industry Data in Textual Content

Using Machine Learning to Identify and Categorize Personally...

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Advanced Research in Computing (ICARC), International Conference on

作者： Milinda Arambawela Achala Aponso Computer Science and Engineering University of Westminster London UK Department of Computing Informatics Institute of Technology Colombo Sri Lanka

The advent of the Internet has significantly stream-lined daily tasks through the rapid increase of online services. Everyday activities, such as purchasing goods and scheduling appointments with healthcare professionals, have become more speedy, efficient and user-friendly with the integration of the Internet. The continuous improvement of online services has led to many people moving towards digital activities. As a result, it has heightened the recording of personal and payment transaction data across various storage mediums, including databases and log files. The protection and regulation of this sensitive data are imperative, aligning with the guidelines outlined in GDPR and PCI-DSS compliances. Recognizing exposed personal data poses a considerable challenge. This research introduces a novel approach to identifying payment card industry data (PCI) and personally identifiable information (PII). The research project proposes a machine learning-based text classification model utilizing the Convolutional Neural Network (CNN) model to discern PII and PCI data within a given text. The CNN model has been constructed and compared against Naive Bayes, Gradient Boost, Random Forest, and Support Vector Machine (SVM) models. The CNN model achieved the highest accuracy at 0.96 (96%). Additionally, the F1 scores for each class were significant, with PII scoring 0.94, PCI scoring 0.95, and Normal scoring 0.99. Following the model's construction and training, it was employed with the saved tokenizer's word indexes and label encoders in the developed classification tool. This tool successfully delivered the promised results, identifying exposed PII and PCI data.

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Cross-Modality Perturbation Synergy Attack for Person Re-identification 38

Cross-Modality Perturbation Synergy Attack for Person Re-ide...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Gong, Yunpeng Zhong, Zhun Qu, Yansong Luo, Zhiming Ji, Rongrong Jiang, Min School of Informatics Xiamen University China School of Computer Science and Information Engineering Hefei University of Technology China The Department of Artificial Intelligence Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China School of Informatics Key Laboratory of Digital Protection and Intelligent Processing of Intangible CulturalHeritage of Fujian and Taiwan Ministry of Culture and Tourism Xiamen University Fujian Xiamen361005 China

In recent years, there has been significant research focusing on addressing security concerns in single-modal person re-identification (ReID) systems that are based on RGB images. However, the safety of cross-modality scenarios, which are more commonly encountered in practical applications involving images captured by infrared cameras, has not received adequate attention. The main challenge in cross-modality ReID lies in effectively dealing with visual differences between different modalities. For instance, infrared images are typically grayscale, unlike visible images that contain color information. Existing attack methods have primarily focused on the characteristics of the visible image modality, overlooking the features of other modalities and the variations in data distribution among different modalities. This oversight can potentially undermine the effectiveness of these methods in image retrieval across diverse modalities. This study represents the first exploration into the security of cross-modality ReID models and proposes a universal perturbation attack specifically designed for cross-modality ReID. This attack optimizes perturbations by leveraging gradients from diverse modality data, thereby disrupting the discriminator and reinforcing the differences between modalities. We conducted experiments on three widely used cross-modality datasets, namely RegDB, SYSU, and LLCM. The results not only demonstrate the effectiveness of our method but also provide insights for future improvements in the robustness of cross-modality ReID systems. © 2024 Neural information processing systems foundation. All rights reserved.

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Evaluating wall installation methods for cylindrical solar cells in urban areas by luminous flux simulation 13

Evaluating wall installation methods for cylindrical solar c...

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13th IEEE Power and Energy Society: Innovative Smart Grid Technologies - Asia, ISGT Asia 2024

作者： Tamura, Fumiki Yokogawa, Shinji Hayase, Shuzi Nakamura, Masaki Hirami, Tomoyuki Hirotani, Daisuke Sono, Yuya Takenoya, Toshihiro Nomura, Daishiro Nomura, Takatoshi Hayashi, Masahiro Honma, Kento The University of Electro-Communications Graduate School of Informatics and Engineering Department of Informatics Tokyo Japan The University of Electro-Communications Info-Power Energy System Research Center Tokyo Japan Ushio Inc Marketing Division Climate Solution Department Japan Marketing Division Ushio Inc Global Warming Solution Group Climate Solution Department Japan Fujico CO. Ltd Technology Development Center Japan Ckd Corporation New Business Development Office Japan The University of Electro-Communications Informatics and Computer Engineering Tokyo Japan

ISBN: (纸本)9798350373929

In urban areas of Japan, such as Tokyo, overcrowding in condominiums and office buildings leaves limited flat land for installing solar panels, resulting in inadequate installation of renewable energy. To advance photovoltaic power generation and support Japan's goal of achieving carbon neutrality by 2050, we are exploring the use of cylindrical solar cells in these dense urban settings. Cylindrical solar cells are ideal for metropolitan installations due to their lightweight design and wind resistance. However, it is crucial to consider how installation configurations influence electricity production, especially the need to minimize shadowing from nearby buildings and other urban elements. This study utilized lighting simulation software to model the light flux based on actual installation conditions of cylindrical solar cells to identify optimal placement strategies. Additionally, this configuration was compared with traditional flat-plate solar cells under similar conditions. Findings indicate that cylindrical solar cells offer flexible installation options. Notably, employing a horizontal grid layout for cylindrical cells addresses the challenges associated with wall-mounted flat-plate cells, which suffer reduced luminous flux at higher solar altitudes. These results demonstrate that cylindrical solar cells can effectively overcome the challenges of photovoltaic installation in densely populated urban areas. © 2024 IEEE.

关键词： Apartment houses

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Utilizing Fine-Tuning ResNet-18 for Acute Leukemia Diagnosis from Blood Smear Images

Utilizing Fine-Tuning ResNet-18 for Acute Leukemia Diagnosis...

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technology Innovation and Its Applications (ICTIIA), International Conference on

作者： Triandes Sinaga Ade Candra Bedy Purnama Master of Informatics Engineering Faculty of Computer and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Informatics School of Computing Telkom University Bandung Indonesia

ISBN: (数字)9798350351613

ISBN: (纸本)9798350351620

This study explores fine-tuning ResNet-18 to enhance the accuracy of acute leukemia diagnosis from blood smear images. Early detection is crucial for patient outcomes, but the application of ResNet-18 in this context has been underutilized. We propose fine-tuning ResNet-18 to increase diagnostic precision using datasets from RSUP Haji Adam Malik Medan and Università degli Studi di Milano Statale. The model achieved 99.12% accuracy on validation and test datasets, with excellent precision, recall, F1-score, and AUCROC. Comparative analysis with non-fine-tuned ResNet-18, VGG-16, and MobileNetV2 demonstrated the superiority and stability of fine-tuning, highlighting its importance in improving diagnostic model reliability.

关键词： Training Measurement Technological innovation Analytical models Accuracy Fluctuations Stability analysis Data models Blood Overfitting

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Observing Generator Performance by Finite Element Analysis Considering Coil Numbers 5

Observing Generator Performance by Finite Element Analysis C...

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5th International Conference on technology and Policy in Energy and Electric Power, ICT-PEP 2023

作者： Habibi, Muhammad Afnan Ali Irfani, Mochamad Farhan Gumilar, Langlang Kusumawardana, Arya Aripriharta Baskoro, Angger Universitas Negeri Malang Study Program of Power Plant Engineering Technology Malang Indonesia Universitas Negeri Malang Department of Electrical Engineering and Informatics Malang Indonesia National Yang Ming Chiao Tung University Dept. Electrical Engineering and Computer Sciences Hsinchu Taiwan

ISBN: (纸本)9798350369717

This paper conducts a comprehensive analysis of electrical generator performance using Finite Element Analysis (FEA), with a specific emphasis on the role of coil numbers in influencing generator efficiency and functionality. In the context of modern energy systems, where efficient power generation is paramount, this research aims to elucidate the relationship between the number of coils within a generator and its overall performance, including power output and electromagnetic behavior. Through systematic FEA simulations that vary coil numbers while keeping other parameters constant, this study provides valuable insights into the trade-offs associated with increased coil numbers and enhanced efficiency. These findings have significant implications for optimizing generator designs across various applications, from renewable energy systems to industrial power generation, ultimately advancing our understanding of generator dynamics and contributing to more sustainable and efficient power generation technologies. © 2023 IEEE.

关键词： Finite element method

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Feature Analysis and Selection for BGP Anomaly Detection

Feature Analysis and Selection for BGP Anomaly Detection

引用

International Conference on Intelligence in Next Generation Networks (ICIN)

作者： Rifqy Hakimi Martin J. Reed School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia

ISBN: (数字)9798331542399

ISBN: (纸本)9798331542405

Automated incidence reporting requires accurate and timely anomaly detection. This paper considers this in the context of the Border Gateway Protocol (BGP). BGP is crucial for Internet routing but is vulnerable to attacks due to a lack of widespread authentication. While rare, BGP disruptions can be highly detrimental to Internet performance and security. Detecting BGP anomalies helps network operators protect their networks and improve Internet reliability. In this work, we investigate and develop anomaly detection for BGP using Machine-Learning. We extract relevant features of BGP control plane messages from RIPE RIS and RouteViews public datasets. After extracting features, we employ various feature selection algorithms to extract the most relevant features and explore balancing the datasets. Finally, we explore detection latency, an important operating parameter for automated anomaly detection. The results show that BGP anomalies can be detected in the order of seven minutes when using real attack data and that the observation point for the BGP data has a significant effect on anomaly detection.

关键词： Technological innovation Soft sensors Machine learning Feature extraction Routing Border Gateway Protocol Security Reliability Anomaly detection Faces

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Multi Socket Network Transmission with Elliptic Curve Cryptography Encryption Algorithm 1

Multi Socket Network Transmission with Elliptic Curve Crypto...

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1st International Conference on technology, engineering, and Computing Applications, ICTECA 2023

作者： Kawet, Hetly Brinner Yusak Heikhmakhtiar, Aulia Rahardjo, Budi Mantoro, Teddy The Republic of Indonesia Defence University Sains and Defence Technology Faculty Bogor Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Sampoerna University Media-Tech Lab Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

Information systems play a crucial role in facilitating effective and efficient media sharing by enabling the exchange of information. However, the current technological landscape is plagued by numerous potential attacks that can compromise the security of exchanged information. Examples of such attacks include stealing user data through interception of user-server communication, spoofing, and sniffing. Robust security measures are essential to mitigate the risks of data leakage and ensure data confidentiality during network-based information exchange. This study proposes designing a communication system based on a multi-socket network, employing the elliptic curve cryptography (ECC) encryption algorithm. The system comprises a single server and multiple clients. This paper analyzes the security of ECC from the performance comparison of ECC and RSA when implemented in multi sochet server. This work uses cryptography library implementation using C programming language. The utilization of the ECC encryption algorithm in network transmission ensures a high level of security and data confidentiality during information exchange. Furthermore, the data transmission system implemented with the ECC algorithm exhibits a swift computation time, thereby expediting key processing and message transmission while maintaining a strong level of security. © 2023 IEEE.

关键词： Geometry

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Improving WiFi Fingerprint Database With Irregular Distribution of Reference Points Using Interpolation Methods

Improving WiFi Fingerprint Database With Irregular Distribut...

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2024 International Conference on Advanced Technologies for Communications, ATC 2024

作者： Vu-Thanh, Trung He, Jing Duong-Bao, Ninh Lee, Seon-Woo Thi, Luong Nguyen Nguyen-Huu, Khanh College of Computer Science and Electronic Engineering Hunan University Changsha China Dalat University Faculty of Mathematics and Informatics Dalat Viet Nam Hallym University Division of Software Chuncheon Korea Republic of Dalat University Faculty of Information Technology Dalat Viet Nam Dalat University Department of Electronics and Telecommunications Dalat Viet Nam

ISBN: (纸本)9798350353983

Using WiFi Fingerprinting for indoor positioning is becoming increasingly popular due to its cost-effectiveness. However, to ensure the system can operate with high accuracy and stability, this technique requires a burden of data collection tasks from a dense distribution of reference points (RPs). To decrease the cost of data collection, as well as to improve the WiFi fingerprint database with irregular distribution of RPs, this study applies and compares different interpolation methods. Evaluating these methods in a public dataset including multiple sub-datasets with irregular distributions of RPs, the results highlight the Linear Barycentric interpolation (LB) as the most favorable method due to its low complexity and stable performance. The LB-based fingerprint database achieves an average interpolation error of less than 3 dBm compared to the original one. When applying the interpolated database to positioning tasks, it can help reduce acquisition costs by up to 50% while improving positioning accuracy by up to 11%. The study reveals the feasibility of interpolation in optimizing WiFi fingerprint data collection, especially in large and complex environments where regular distribution of RPs cannot be deployed. © 2024 IEEE.

关键词： Interpolation

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Data Science System of Predicting and Detecting the Chikungunya Virus using Ensemble Techniques 4

Data Science System of Predicting and Detecting the Chikungu...

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4th International Conference on Inventive Research in Computing Applications, ICIRCA 2022

作者： Reddy, Bommireddy Vijay Kumar Patel, Shail Singh, Anayna Singh, Nishant Ranjit, Sasanapuri Dantkale, Shreyas National Institute of Technology Srinagar Department Computer Science and Engineering Jammu and Kashmir India Vellore Institute of Technology Department Computer Science and Engineering Vellore India Niit University Department Computer Science and Engineering Neemrana India University of Delhi Department of Institute of Informatics and Communication Delhi India Pes University Department of Electronics and Communication Engineering Bangalore India Vishwakarma Institute of Technology Department of Electronics and Communication Engineering Pune India

ISBN: (数字)9781665497077

ISBN: (纸本)9781665497077

The ailment known as chikungunya fever is brought on by a virus that mosquitoes disseminate. Due to the infection's excruciating joint and muscular discomfort, the term translates to 'bends you up' or 'stooped walk.' The abrupt onset of a high temperature, headache, exhaustion, rash, nausea, and red eyes are other symptoms. Chikungunya symptoms frequently show up 2 to 7 days after being bitten by an infected mosquito. There isn't a vaccination yet. Additionally, there is no cure for the illness. However, fatalities or major complications with chikungunya are uncommon. Many people recover in a matter of weeks. However, some people experience joint and muscular discomfort that can linger for months or even years after they have been exposed to the virus. After one to two weeks, a lot of people are free of further problems. Others, though, can experience joint and muscular discomfort for years. This kind of arthritis is known as chronic chikungunya. At least 40persons who contract the virus are affected. Chikungunya is seldom fatal. But for certain people, the infection can lead to serious issues. Older persons, those with chronic illnesses like diabetes or high blood pressure, small children, and pregnant women who could pass the virus to their unborn children are at increased risk. Serious issues with the eyes, heart, and nerves can be complications. Once-infected individuals are likely to be resistant to subsequent infections. The main aim of the authors is to use the ensemble technqiue to find a novel approach and to compare the ensemble techniques. © 2022 IEEE.

关键词： Viruses

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