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Power and Area Optimized Memristor-Based Majority Identifier for Digital Applications 3

Power and Area Optimized Memristor-Based Majority Identifier...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Raj, P. Michael Preetam Vittapu, Sravan K. Chinnasamy, P. Gupta, Manu Samatha, K. Sasivijaya, K. Mlr Institute of Technology Department of Computer Science and Engineering Hyderabad India Nalla Narasimha Reddy Education Society's Group of Institutions Department of Electronics and Communication Engineering Hyderabad India Kalasalingam Academy of Research and Education Dept. of Computer Science and Engineering Tamil Nadu India Sreenidhi Institute of Science and Technology Department of Electronics and Computer Engineering Hyderabad India

ISBN: (纸本)9798331518592

In earlier developments, CMOS technology played a great role in realizing majority identifiers. There are huge drawbacks that affect the circuit's performance. To overcome the drawbacks of CMOS-based majority Identifiers, novel memristor-based majority and minority Identifiers have been proposed in this work. The features offered by memristor have motivated us to use the component and achieve greatly improved results compared to CMOS-based majority identifier circuits. After observing the behavior of the basic memristor-based majority identifier circuit, we have decided to design and implement a memristor-based majority and minority identifier circuit which can be used in many automation systems to increase quality and productivity. © 2024 IEEE.

关键词： CMOS integrated circuits

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Performance Evaluation of CNN Models in Urban Acoustic Event Recognition Through MFCC Hyperparameter Search

Performance Evaluation of CNN Models in Urban Acoustic Event...

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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Tangarife, Ricardo Velásquez, Ricardo A. Rivera, Fredy University of Antioquia Dept. Electronics Engineering Medellín Colombia University of Antioquia Dept. Computer Science Medellín Colombia

ISBN: (纸本)9798350327595

This paper focuses on acoustic event recognition, a significant research area in various fields, including security, medicine, and entertainment. The study explores the design space of combining convolutional neural networks with Mel Frequency Cepstral Coefficients to extract audio features. This work explicitly investigates three acoustic events relevant to citizen security: gunshots, screams, and sirens. We aim to find the optimal combination of hyperparameters to train accurate models with low computational requirements. The proposed approach achieved impressive F1-Scores of 95% for sirens, 97.2% for gunshots, and 99% for screams. Furthermore, considering computational complexity, our results demonstrate that these sounds could be utilized in real-time acoustic event recognition systems for citizen security applications. © 2023 IEEE.

关键词： Acoustic Event Recognition Audio Feature Extraction Hyperparameter Search Machine Learning MFCC

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Steganographic Encryption and Decryption Using Duality Preserving GANs 22

Steganographic Encryption and Decryption Using Duality Prese...

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22nd IEEE International Conference on Industrial informatics, INDIN 2024

作者： Shah, Aaryak Kamal, Alok Kumar Neeraj Dept. of Information Technology ABV-IIITM Gwalior Gwalior India Dept. of Electrical/Electronics ABV-IIITM Gwalior Gwalior India Dept. of Computer Science and Engineering Mahindra University Hyderabad India

ISBN: (纸本)9798331527471

Image steganography has been a significant research area in the security sphere. The core idea revolves around embedding secret messages in existing images (covers) such that the resultant image displays no noticeable detectable artifacts of the secret while also being statistically similar to the original cover. Various steganographic techniques have been developed and tested. However, these traditional techniques often exploit some specific property of the image and are often easy to detect with the right tools. In recent times, generative adversarial networks, or GANs for short, have shown massive promise in their capability to modify and synthesize data. They are now ubiquitous in image synthesis and image translation tasks. With various recent advancements in this technology allowing these models to generate, in many cases, human-imperceptible data, GAN-based steganographic systems have become a significant focus of security research. This report analyzes and compares some existing models and attempts to provide a new solution that performs better on multiple well-defined metrics. A DualGAN-based architecture is proposed that trains both the encoder and decoder processes simultaneously while maintaining the underlying dual relationship of these tasks. The proposed scheme reports better results on the selected metrics (SBR, DER, PSNR) at three values of embedding capacity set at 0.3, 0.6, and 0.9. © 2024 IEEE.

关键词： Generative adversarial networks

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Generating Automated Assistance Mechanism in Android Programming Self-learning System Using Automatic Testing Tools

Generating Automated Assistance Mechanism in Android Program...

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2023 International Conference on Innovation and Intelligence for informatics, Computing, and Technologies, 3ICT 2023

作者： Syaifudin, Yan Watequlis Liliana, Dewi Yanti Kaswar, Andi Baso Fatmawati, Triana Funabiki, Nobuo Siradjuddin, Indrazno State Polytechnic of Malang Dept. of Information Technology Malang Indonesia State Polytechnic of Jakarta Dept. of Informatics Engineering Jakarta Indonesia State University of Makassar Dept. of Computer Engineering Makassar Indonesia Okayama University Dept. of Elec. and Comm. Engineering Okayama Japan State Polytechnic of Malang Dept. of Electrical Engineering Malang Indonesia

ISBN: (纸本)9798350307771

Nowadays, computer-assisted learning (CAL) has experienced a significant increase in demand for self-learning purposes with the mechanism of automated assistance to facilitate assessments and provide instant feedback to learners. Using automatic testing, test cases can be executed repeatedly, providing informative feedback to assist students in correcting the written code referring to the assignment specifications. This research experiences an automated testing mechanism in an Android programming self-learning system to serve several important functions for learning experience enhancement. By adopting the TDD method and utilizing automatic software testing tools, the testing process combines unit testing with JUnit and integration testing with Robolectric. It ensures the quality and functionality of the application under test based on learning assignment's specifications. Utilizing the assertion methods realizes the code verification referring to expected behavior and potentially produces informative feedback that can be captured to provide automated assistance. Evaluation through the test code implementation in the Basic Application learning topic shows that automatic testing tools cover the automated assistance feature in the validations of project configuration and UI components. © 2023 IEEE.

关键词： Specifications

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Privacy-Preserving Network Intrusion Detection using Federated Learning 14

Privacy-Preserving Network Intrusion Detection using Federat...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Abhijit, Chunduru Sri Himmatramka, Rishav Bishoyi, Aum Shiva Rama Prasath, Lallith Subbulakshmi, T. Vellore Institute of Technology Dept. of Computer Science Chennai India Vellore Institute of Technology Dept. of Electronics Engineering Chennai India

ISBN: (纸本)9798350335095

Internet of Things (IoT) devices are more vulnerable to viruses, assaults, and harmful activities as they are developed in tandem with the rise in cybercrime. Network Intrusion Detection Systems (NIDS) are generally used to detect attacks in the IoT devices. Machine learning (ML) techniques are being employed to improve these systems. This study compares various ML techniques to develop NIDS using UNSW-NB15 dataset and proposes a federated learning (FL) approach to overcome the limitations of classical ML approaches. Feature selection is done on the basis of correlation between them and five ML approaches are implemented: Logistic Regression, K-Nearest Neighbors, Random Forest (RF), Decision Tree and Artificial Neural Network. RF was found to be the best performing model for both binary and multi-class classification. However, there are certain limitations in this centralized approach which assumes the presence of a central organisation to store and execute analysis on data from all participant devices. FL is a decentralized approach where each IoT device is considered as a client and models are trained on these devices without transmitting data. This preserves privacy of data and also reduces data transfer costs as only model weights are shared instead of huge data. To assess the effectiveness of the proposed method, we conduct extensive experiments on the UNSW-NB15 dataset. The proposed FL detection model is shown to be both accurate and superior to the centralised model in experiments and empirical analyses, demonstrating its resilience and benefits. © 2023 IEEE.

关键词： Internet of things

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AI-Powered Advertisement Design: A PIL-Based Approach for Quality and Performance Analysis 3

AI-Powered Advertisement Design: A PIL-Based Approach for Qu...

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3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and electronics, IITCEE 2025

作者： Chilupuri, Harshitha Ramesh, G. Praveen, J. Gude, Venkataramaiah Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Artificial Intelligence and Machine Learning Hyderabad India Gokaraju Rangaraju Institute of Engineering and Technology Dept. of Computer Science and Engineering Hyderabad500090 India Gokaraju Rangaraju Institute of Engineering and Technology Department of Electrical and Electronics Engineering Telangana Hyderabad500 090 India Gp Technologies Llc United States

ISBN: (纸本)9798331515911

The paper presents the development of a Data Science solution that applies generative AI models in order to create high-quality images to be used in visual marketing and advertising. Using the Python library PIL (Pillow) along with machine learning frameworks, the solution combines predefined product images with the selected backgrounds, enhancing image synthesis techniques for more appealing and contextually relevant visuals. This leads to improved efficiency and effectiveness in the creation of content by automatically placing product images onto the background images used in marketing campaigns. The approach demonstrated a 98.06% SSIM (Structural similarity Index) score, indicating significant visual quality improvement. Initial results suggest a 15% enhancement in visual appeal compared to traditional image creation methods. © 2025 IEEE.

关键词： Data Science

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Offensive Message Spam Detection in Social Media Using Long Short-Term Memory 3

Offensive Message Spam Detection in Social Media Using Long ...

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3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Sivakumar, M. Abishek, S.A. Karthik, N. Vanitha, J. National Institute of Technology Dept. of Electrical and Electronics Engineering Puducherry India National Institute of Technology Dept. of Computer Science Engineering Puducherry India National Institute of Technology Puducherry India E.G.S.Pillay Engineering College Nagapattinam India

ISBN: (纸本)9798331518592

In this world, online communication has become an essential part in our daily lives. Almost everyone uses social media platforms to communicate with the whole world. But this also leads to a major problem: cyberbullying. This paper proposes a system to detect users who spam offensive messages repeatedly and ban them using natural language processing and machine learning. The system would be beneficial to service providers, social media platforms, and individuals, allowing us to strive for a world of harmony. The amalgamation of NLP, Big Data, and ML approaches presents a robust and efficient solution for offensive message spam detection. The findings of this project will shed light on the potential of these technologies to curb the proliferation of offensive content, thereby fostering a healthier and more respectful online communication ecosystem. This paper delves on offensive spam detection using the LSTM model, and the obtained MSE of this model is 12.58. © 2024 IEEE.

关键词： Social networking (online)

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Enhancement of Electronic Medical Record (EMR) Security in Private Networks with Blockchains 3

Enhancement of Electronic Medical Record (EMR) Security in P...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： El-Hamed, Osama M. Abd El-Samie, Fathi E. Abd El-Atty, Saied M. Abd El-Din Hemdan, Ezz Badawy, Wael Menoufia University Faculty of Electronic Engineering Dept. of Electronics and Electrical Communications Menouf Egypt Menoufia University Faculty of Electronic Engineering Dept. of Computer Ecience and Engineering Menouf Egypt University of Hertfordshire Hosted by Gaf School of Physics Engineering and Computer Science United Kingdom

ISBN: (纸本)9798350323511

In this paper, we propose a system for improving the security of Electronic Medical Records (EMRs) in private networks using Blockchain technology. There are currently problems with data integrity in database systems that contain health records. Application Programming Interfaces (APIs) are frequently used by amateur organizations to create internal frameworks, which might result in data manipulation in an improper way and unauthorized access. We put up a practical solution for this issue that makes use of Blockchain immutability. Our system depends on HTML forms and NodeJS to store patient-related records in a MySQL database. However, using the secure hashing SHA-256, we store the hash values of the records in blocks rather than the actual records themselves. This method ensures that any unauthorized alterations in the records may be quickly identified by comparing the stored hash value with the actual hash of the data that is obtained from the database. Our system performance analysis, which shows acceptable latency, was done. The Blockchain runs in the background without having a substantial influence on speed, thus the database continues to run quickly. Our system also saves money, because it is designed to be used with a user-programmed Blockchain within private networks. It is offered at no additional cost, and is primarily made to verify data accuracy. For private networks depending on EMR systems, our suggested solution provides improved security, effective performance, and affordability as compared to existing approaches and frameworks. © 2023 IEEE.

关键词： Blockchain

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Generalization Evaluation of Seq2seq based Fog Computing Application Placement Algorithm on Limited Dataset 3

Generalization Evaluation of Seq2seq based Fog Computing App...

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

作者： Pakpahan, Michael S. M. Nugroho, Lukito Edi Widyawan, Widyawan Wardhana, Ajie Kusuma Muhammad Ardian, R.A. Astagenta, Rangga Satria Universitas Gadjah Mada Dept. of Electrical and Information Engineering Yogyakarta Indonesia Universitas Amikom Yogyakarta Faculty of Computer Science Dept. Informatics Yogyakarta Indonesia

ISBN: (纸本)9798350394559

Addressing its growing number and vital role, decentralization of cloud computing becoming a necessity. Fog computing aims to bring application closer to the data source-typically at the network's edge by leveraging local resources to provide faster data processing and decision-making. Fog computing then has to place application strategically to use its limited fog resource to improve application performance metrics. This problem known as Fog Application Placement Problem (FAPP) has been approached using previous methods that rely on rules and prior knowledge that may not be adaptive, but rather being overly specialized to specific problems. Deep learning with its learning mechanism, can offer more adaptable and dynamic solutions for a wide range of scenarios, especially in fog network that continuously evolve. This research investigate Seq2seq placement model inherent limitations, notably the impracticality of generating every possible pattern from all potential request configurations. We aim to address and answer the following critical questions: 1) How does the model's performance vary when confronted with unseen requests or an augmented number of modules, especially considering the limitations in training data?;2) Can the seq2seq model, even with its training limitations, adhere to the heuristic rules of the dataset when dealing with unfamiliar problems? This research shows that in similar availability, there is a reduction of almost half of the response time with 183.03 ms, 2.93 number of hops, and 0.87 megabyte of transmitted messages against the hop3 algorithm. Moreover, we highlight the ability of seq2seq model to follow heuristic rules in unseen scenarios. © 2023 IEEE.

关键词： Fog computing

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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...

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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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