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Classification of Mental Workload Using 1D-CNN with Transfer Learning 1

Classification of Mental Workload Using 1D-CNN with Transfer...

引用

1st International Conference on Pioneering Developments in computer science and Digital Technologies, IC2SDT 2024

作者： Chaturvedi, Sushil Ahirwal, Mitul Kumar Maulana Azad National Institute of Technology Dept. of Computer Science and Engineering Bhopal India

ISBN: (纸本)9798350365016

Mental workload (MWL) can be explained as the ratio of a participant's mental effort to their brain capability when performing activities. A significant challenge in the field of MWL classification for brain-computer interfaces (BCIs) based on electroencephalograms (EEGs) is the variability among individuals. It commonly takes unnecessary time to retrain the classification model from starting for a new subject. To address the individual variations among different subjects, a one-dimensional convolutional neural network along with transfer learning (1D CNN-TL) is proposed in this work. The end-to-end 1D-CNN learns the common features of EEG signals and, to tackle the problem of difference in EEG for individuals, a transfer learning technique is used that does fine-tuning on fully connected (FC) layers for a new participant having less training data. The average test accuracy (mean±stdv) of 65.18± 8.37 is achieved over the Cross-session mental workload dataset. The suggested method can achieve satisfying results for new unknown data with less time and fewer training data. © 2024 IEEE.

关键词： Convolutional neural networks

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AI Enhanced-Smart Genome Editing: Integration of CRISPR-Cas9 with Artificial Intelligence for Cancer Treatment 5

AI Enhanced-Smart Genome Editing: Integration of CRISPR-Cas9...

引用

5th IEEE International Conference for Emerging Technology, INCET 2024

作者： Kumar, D. Nitesh Chowdhary, D. Lavanya Pathuri, Trinadh Katta, Priyanka Arya, Leena Dept. of Computer Science & Engineering Koneru Lakshmaiah Education Foundation AP Guntur India

ISBN: (纸本)9798350361155

The CRISPR-Cas9 genome editing system is a new technology that allows the modification of secret vital material using disruptions insertions or amendments of DNA sequence. It is an easy, widely accepted, and correct representation of gene modification. The potential for treating different genetic diseases is enormous. This paper discusses the latest approach to CRISPR-Cas9 integration with AI, aimed at improving efficacy, as well as the safety of cancer treatment. This paper highlights the cutting-edge integration of CRISPRCas9 with Artificial Intelligence (AI) to enhance the efficacy and safety of cancer treatment. Artificial intelligence is a simulation of human intelligence for computers, indicates the latest developments in the field, and mentions clinical trials' ability to help further the treatment of cancer and overcome current and upcoming challenges. Finally, the application of (AI) in the modification of the CRISPR/Cas9 system is highlighted. Taking case scenarios and futuristic approaches, this paper reveals excellent implementation initiatives by learning from the Clinical revolution together with human technology and aimed at a future in which new technologies improve patient outcomes without sacrificing ethics or putting patients first. © 2024 IEEE.

关键词： Diseases

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Bidirectional Communication system for Deaf-Blind Individuals 8

Bidirectional Communication System for Deaf-Blind Individual...

引用

8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Saralaya, Sridevi Jijo, Jeevan V. Serrao, Lavisha Andri D'Souza, Flaivin Vaz, Jane Oveita St Joseph Engg. College Dept. of Computer Science & Engineering Mangalore India

ISBN: (纸本)9798350350593

In a world that thrives on connectivity and communication, we often take for granted the power of simple yet profound interactions. For individuals with sensory impairments, particularly the deaf-blind community, these fundamental human connections are often limited, making everyday life a challenge. In response to this challenge, we propose an innovative and transformative project that aims to bridge the communication gap for the deaf-blind community, enabling them to engage in text-based conversations with ease. While advancements in technology have greatly improved communication for many, those who are both deaf and blind remain largely excluded from the digital world. This exclusion hinders their ability to engage in meaningful conversations, access information, and connect with others, leading to social and informational isolation. While existing solutions often focused on either blindness or deafness, this project aimed to provide a holistic communication solution for individuals with both impairments. Through rigorous testing, the bidirectional communication system demonstrated its ability to accurately transcribe speech-to-text, translate text-to-braille, and facilitate seamless interaction between users and hardware peripherals. The project's novel solution for deaf-blind communication brings significant advantages namely cost saving, streamlined labor, efficient space utilization, and energy conservation. The integration of speech-to-text with real-time braille hardware interaction enhances user experience, reducing the need for extensive manual interpretation. © 2024 IEEE.

关键词： Ability testing

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From Ranch to Worldwide:Observing Soil Welbeing Patterns

From Ranch to Worldwide:Observing Soil Welbeing Patterns

引用

2024 International Conference on Knowledge engineering and Communication systems, ICKECS 2024

作者： Divakar, K.M. Ankith Gowrishankar Esturi, R. Anil, P.S. Namith, D. Chethan, A. S J C Institute of Technology Dept. of Computer Science Engineering Chikkaballapur India

ISBN: (纸本)9798350359688

Declining soil wellbeing represents a huge danger to worldwide food security and rural maintainability. Precisely checking soil wellbeing patterns and anticipating future land appropriateness at nearby and worldwide scales are essential for illuminating feasible administration practices and strategy intercessions. This paper proposes a clever structure that use the force of large information investigation to address this test. We expect to overcome any issues between ranch level checking and worldwide experiences, engaging partners at each level to come to informed conclusions about land use and management. Our structure depends on the mix of assorted information sources. High-goal remote detecting information, including satellite symbolism and aeronautical photography, will give basic experiences into soil properties, crop conditions, and land the board rehearses. We will additionally improve the examination by consolidating promptly accessible open-access datasets on environment, soil overviews, and financial data. This exhaustive information combination approach permits us to catch the diverse idea of soil wellbeing and land reasonableness dynamics. Extracting significant experiences from these tremendous datasets requires clever examination devices. We will use a setup of AI procedures, including regulated and solo learning calculations, to reveal stowed away examples and connections inside the information. Directed learning will empower us to foster prescient models for soil wellbeing appraisal and land appropriateness planning, while solo learning will assist with recognizing remarkable attributes and likely peculiarities in various farming *** system will create constant soil wellbeing maps, featuring areas of corruption, supplement lacks, and potential improvement open doors. This enables ranchers to come to informed conclusions about manure application, water the board, and harvest choice, advancing their activities for expanded yield and long ha

关键词： Fertilizers

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Epileptic Seizure Detection Using Quantum Support Vector Classifier

Epileptic Seizure Detection Using Quantum Support Vector Cla...

引用

2024 International Conference on Computational Intelligence for Green and Sustainable Technologies, ICCIGST 2024

作者： Meesala, Gopichand Soni, Barkha Pandey, Manish Khare, Nilay Maulana Azad National Institute of Technology Dept. of Computer Science and Engineering Bhopal India

ISBN: (纸本)9798350381887

Epilepsy is the second most prevalent neurological disorder. It poses significant challenges to both diagnosis and treatment. The information obtained from electroencephalography serves as crucial for understanding the dynamics of epileptic brain activity. It offers a non-invasive means for monitoring and detecting epileptic seizures. This paper explores the use of quantum machine learning algorithms to improve the precision and effectiveness of utilizing EEG data for epileptic seizure detection. Quantum machine learning, leveraging principles from quantum mechanics, holds promise for addressing these challenges by harnessing quantum computational power and exploiting quantum entanglement to process information more efficiently. Quantum features and quantum kernels are employed to capture intricate patterns within the EEG signals, allowing for improved discrimination between normal brain activity and seizure events. Results indicate that the Quantum Support Vector Classifier exhibit a satisfactory classification accuracy compared to traditional techniques despite having constraints with resources. The findings suggest that quantum computing holds great promise in revolutionizing the field of epilepsy diagnosis by providing more robust and accurate tools for distinguishing between epileptic and non-epileptic EEG patterns. © 2024 IEEE.

关键词： Quantum entanglement

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Using Blockchain for Incentive-Driven FHIR-based Health Record Exchange 24

Using Blockchain for Incentive-Driven FHIR-based Health Reco...

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39th Annual ACM Symposium on Applied Computing, SAC 2024

作者： Rosar, Moritz Chuang, Kun-Ta Dept. of Computer Science and Information Engineering National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9798400702433

Medical data is highly sensitive data, and patients are particularly concerned about the exposure of their identities [1]. A study found that 64% of participants were agreeable to sharing their health data when anonymized, highlighting the importance of privacy in medical data sharing [5]. © 2024 Copyright held by the owner/author(s).

关键词： Sensitive data

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Adaptive Forward Error Correction for Voice over IP with Random Linear Network Coding 2

Adaptive Forward Error Correction for Voice over IP with Ran...

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2nd IEEE Virtual Conference on Communications, VCC 2024

作者： Su, Yi-Chiuan Wu, Quincy National Chi Nan University Dept. of Computer Science and Information Engineering Nantou Taiwan

ISBN: (纸本)9798331530099

This paper proposes the use of Random Linear Network Coding (RLNC) as an erasure code in the forward error correction (FEC) mechanism for Internet telephony. It also designs and implements a forward error correction algorithm applied to the Real-time Transport Protocol (RTP), which we call Adaptive systematic RLNC (AS-RLNC). The algorithm learns the current packet loss rate of the network through the Real-time Transport Control Protocol (RTCP) and dynamically adjusts the number of redundant packets sent. Compared with traditional forward error correction methods based on block codes, this approach can enhance the reliability of data transmission and improve audio quality by 31%. © 2024 IEEE.

关键词： Internet telephony

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Almost Order Preserving Matching 16

Almost Order Preserving Matching

引用

16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024

作者： Liao, Wen-Wen Yang, Chang-Biau National Sun Yat-sen University Dept. Computer Science and Engineering Kaohsiung Taiwan

ISBN: (纸本)9798350377903

In this paper, we define a new problem, called the almost order-preserving matching (aOPM) problem, which is a combined variant of order-preserving matching (OPM) and the longest almost increasing subsequence (LaIS). Given a numeric pattern P, a numeric text string T, and a tolerance constant c) the aOPM problem seeks to find the substring of T that each element has the almost same rank as the corresponding element in P. In an almost increasing sequence, small drops within c are permitted while still maintaining a generally increasing trend. Our algorithm for solving the aOPM problem consists of three stages: fingerprint, almost rank, and bipartite matching. The time complexity of the proposed aOPM algorithm is O(n+k1m m+R+k2m3), where n= T, m= P, R is the number of separation rank combinations, k1 and k2 denote the number of candidate substrings identified in the fingerprint and almost rank stages, respectively. © 2024 IEEE.

关键词： almost increasing subsequence bipartite matching fingerprint order-preserving matching string matching

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Machine Learning based Real Estate Price Prediction 8

Machine Learning based Real Estate Price Prediction

引用

8th International Conference on Inventive systems and Control, ICISC 202

作者： Mukherjee, Anupam Nambiar, Rtwik Choudhury, Deepjyoti Manipal University Jaipur School of Computer Science and Engineering Dept. of Aiml Jaipur India

ISBN: (纸本)9798350386578

The dynamic nature of real estate markets gives rise to huge challenges for buyers and sellers in accurately predicting property prices. This paper presents a detailed study on real estate price predictions, focusing on using machine learning techniques to forecast property prices effectively. Using a dataset from Bengaluru, as a case study, it explored the intricacies of Real Estate markets and developed a predictive model to estimate the property prices. Our studies consist of data preprocessing, featuring engineering, model selection, and evaluations, giving insights into the factors that affect property prices and the performances of various regression algorithms. After performing multiple experiments, we showcase the efficiency of our approaches in predicting property prices. Existing techniques that have tried to predict house prices have often struggled to deal with nonlinear relationships present among the factors. Recent techniques such as Linear regression, Ridge and Lasso Regression and Support Vector Machines(SVM) have come up short of being perfect when it comes to dealing with computational intensity and these techniques require extensive hyperparameter tuning. However, our predictive model is able to deal with these challenges by leveraging the strengths of Random Forest regression. This is done with high accuracy and the implications for real estate stakeholders are discussed, subsequently. This paper also highlights the various avenues through which the performance of real estate estimation models can be improved in the future. © 2024 IEEE.

关键词： Support vector regression

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Integration of Q-Learning with Maximal Ratio Combining to Enhance IoT Communications in Dynamic Fading Environments 12

Integration of Q-Learning with Maximal Ratio Combining to En...

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12th International Conference on Internet of Everything, Microwave, Embedded, Communication and Networks, IEMECON 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Sharma, Rashmi Upadhyay, Abhay Dept. of Computer Science and Engineering Graphic Era Hill University Dehradun India Dept. of Computer Science and Engineering Graphic Era deemed to be University Dehradun India Dept. of Electronics and Communication Engineering Graphic Era deemed to be University Dehradun India Nagpur Campus Pune India

ISBN: (纸本)9798350387315

This paper serves to show how Q-learning can be used in complement with Maximal Ratio Combining to better IoT communication systems under dynamic fading, high-density networks, and severe interference sources. The ML-enhanced MRC demonstrated promising improvements in signal strength and quality, allowing for performance that was either above or at least equal to the regular MRC. The ML-enhanced presented the added benefit of dynamic adaptation, modifying its performance to meet real-life needs by adapting to issues such as increased density and interference. These results support that integrating Q-learning into MRC-based frameworks significantly increases the reliability and efficiency of IoT communication protocols. Future investigations will aim to improve ML algorithms more appropriate for devices with few resources and evaluate their potential with state-of-the-art technology to foster future applications across intelligent IoT networks. These approaches have the potential to support more efficient operations and increased connectivity in IoT systems. © 2024 IEEE.

关键词： Fading MRC Q-Learning Wireless

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