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Disruptive Technologies (ICDT), International Conference on

作者： Geetha Ponnaian Jayanthi. N R. Sarasu Sajitha. L.P R. Ramalakshmi Manimegalai L Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Thandalam Chennai India School of Management Studies Vels Institute of Science Technology and Advanced Studies (VISTAS) Pallavaram Chennai Tamil Nadu India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and business system R. M. K Engineering College Kavaraipettai Tamilnadu India Department of Electronics and Communication Engineering Ramco Institute of Technology Rajapalayam Department of Electronics and Communication Engineering R.M.K. College of Engineering and Technology Chennai India

This research focuses on enhancing the spectral efficiency of 5G networks through the utilization of nonlinear stochastic precoding techniques. The proposed approach aims to mitigate the detrimental effects of channel impairments and noise by employing advanced precoding schemes that exploit the statistical properties of the wireless channel. By incorporating nonlinear precoding algorithms and stochastic optimization methods, the system can dynamically adapt to varying channel conditions, resulting in improved data transmission rates and overall spectral efficiency. Through extensive simulations and analysis, the effectiveness of the proposed method is demonstrated, showcasing its potential to significantly enhance the performance of 5G networks in real-world scenarios.

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IoT based Smart Cradle for Neonatal Monitoring 6

IoT based Smart Cradle for Neonatal Monitoring

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6th International Conference on Electronics, communication and Aerospace Technology, ICECA 2022

作者： Sonia, R. Jayadeva, Sujay Mugaloremutt Ragavendiran, S.D. Prabu Revathi, N. Arumugam, Jeevanantham Kumar, S Sandeep B.S. Abdur Rahman Crescent Institute of Science and Technology Department of Computer Applications Tamil Nadu Vandalur600048 India Jss Academy of Higher Education and Research Department of Health System Management Studies Karnataka Mysuru570004 India Rvs Technical Campus Department of Computer Science and Engineering Tamil Nadu Coimbatore641402 India Panimalar Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chennai600123 India Kongu Engineering College Department of Information Technology Tamil Nadu Perundurai638060 India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram522502 India

ISBN: (纸本)9781665482714

India has the highest percentage of working women and mothers. It also has a record for the highest number of babies being born every single day. These two statements highly contradict each other. When a woman gives birth to a baby, she needs to spend almost a year or two taking care of the necessities of the baby. But when a need to leave the baby for a certain time arises regularly, it becomes tougher for them to do so. This study provides a solution to this problem. This research aims at the construction of a smart cradle. This cradle is des igned using various input elements, output elements, a controller module, and a mobile application. The input elements consist of a temperature sensor, a sound sensor or a microphone,a moisture sensor, and a music player. The output elements include the motor and The controller used in this study is the NodeMCU module. Cloud storage is also used and it is provided by the Arduino loT software. The sensors in the smart cradle begin recording relevant parameters such as temperature, humidity, and sound as soon as it is turned on. The information is then uploaded to the cloud The data is then processed in the cloud for analysis. If indeed the child's temperatures is over the safe range, the user receives a warning. Moisture levels above normal suggest that the infant has urinated The sound of the baby crying will be recorded in the microphone. The output elements are energized as a result of the sensor's data. If the baby has a high fever or has to go to the bathroom, the app will notify the parent. © 2022 IEEE.

关键词： Microphones

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Optimal Resource Allocation for U-Shaped Parallel Split Learning

Optimal Resource Allocation for U-Shaped Parallel Split Lear...

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IEEE Globecom Workshops

作者： Song Lyu Zheng Lin Guanqiao Qu Xianhao Chen Xiaoxia Huang Pan Li The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong China School of Electronics and Communication Engineering Sun Yat-sen University Shenzhen China The Department of Electrical Computer and System Engineering Case Western Reserve University Cleveland OH USA

Split learning (SL) has emerged as a promising approach for model training without revealing the raw data samples from the data owners. However, traditional SL inevitably leaks label privacy as the tail model (with the last layers) should be placed on the server. To overcome this limitation, one promising solution is to utilize U-shaped architecture to leave both early layers and last layers on the user side. In this paper, we develop a novel parallel U-shaped split learning and devise the optimal resource optimization scheme to improve the performance of edge networks. In the proposed framework, multiple users communicate with an edge server for SL. We analyze the end-to-end delay of each client during the training process and design an efficient resource allocation algorithm, called LSCRA, which finds the optimal computing resource allocation and split layers. Our experimental results show the effectiveness of LSCRA and that U-shaped parallel split learning can achieve a similar performance with other SL baselines while preserving label privacy.

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The three dimensional dosimetry imaging for automated eye cancer classification using transfer learning model

The three dimensional dosimetry imaging for automated eye ca...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Murtuza Ali Mohammed Vazeer Ali Mohammed Rakesh Ramakrishnan Mehmood Ali Mohammed J. Logeshwaran Maheswaran S Department of Computer & Information System Lewis University Illinois USA Department of Information Technology University of The Cumberlands Union City CA USA Department of Information Technology University of The Cumberlands Williamsburg KY USA Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Department of Electronics and Communication Engineering Kongu Engineering College Erode Tamil Nadu India

computer vision methods utilizing transfer learning can offer a promising approach for automated eye cancer diagnosis with three-dimensional dosimetry imaging. The latest advances in AI have encouraged researchers to use deep learning models for automated cancer classification. This paper presents a novel approach using three-dimensional dosimetry imaging for automated ocular cancer classification using transfer learning. The approach uses a combination of dataset augmentation methods. The approach is adapted from the popular Inception V3 CNN architecture. Two different feature extraction approaches, namely mean and maximum pooling, are compared while extracting features from the output of the CNN layers. The extracted features are fed to the classifier which uses the SVM with a linear kernel as its decision system. The effectiveness of this method is evaluated on a set of 20 healthy ocular images and 26 suspicious ocular images. The overall classification accuracy achieved with this approach is 94.85%. The results obtained demonstrate that this approach has a promising potential for automated ocular cancer classification with an appropriate transfer learning model.

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An innovation prediction of DNA damage of melanoma skin cancer patients using deep learning

An innovation prediction of DNA damage of melanoma skin canc...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Rakesh Ramakrishnan Mehmood Ali Mohammed Murtuza Ali Mohammed Vazeer Ali Mohammed J. Logeshwaran Maheswaran S Department of Information Technology University of The Cumberlands Union City CA USA Department of Information Technology University of The Cumberlands Williamsburg KY USA Department of Computer & Information System Lewis University Illinois USA Department of Electronics and Communication Engineering Sri Eshwar College of Engineering Coimbatore Tamil Nadu India Department of Electronics and Communication Engineering Kongu Engineering College Erode Tamil Nadu India

There are now a variety of intriguing options for the study of genetic data thanks to recent developments in artificial neural networks and deep learning. In this study, we use a deep learning-based prediction model to find possible DNA damage in individuals with melanoma skin cancer. We create a convolutional neural network (CNN) model to forecast the DNA damage susceptibility of melanoma cancer cells using a publically available genome sequencing dataset. This model preprocesses the genomic data, extracts features, and categorises them. Comparing the results of our CNN model with those of a traditional logistic regression model, we find that our CNN reported superior performance in identifying differences between healthy and cancerous samples with an accuracy of nearly 96%. The model can be used to augment the standard clinical diagnosis of melanoma, which only uses visual assessment and histology. By intervening sooner, clinicians can put forward more personalized and informed plans of care and surveillance for each melanoma patient, reducing medical costs and improving the quality of patient diagnosis.

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Preliminary Exploration on Node-To-Node Fault Tolerance Coordination in Distributed system

Preliminary Exploration on Node-To-Node Fault Tolerance Coor...

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Computing (ICOCO), IEEE International Conference on

作者： Muntadher Saadoon Siti Hafizah Ab. Hamid Hazrina Sofian Hamza Altarturi Nur Nasuha Zati Hakim Azizul Haqi Khalid Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia Department of Artificial Intelligence Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia Department of Computer and Communication Faculty of Engineering Universiti Putra Malaysia Selangor Malaysia

Internet of Things, edge computing devices, the widespread use of artificial intelligence and machine learning applications, and the extensive adoption of cloud computing pose significant challenges to maintaining fault tolerance in distributed systems. As the volume and complexity of systems continue to grow, the probability of system failures also grows, leading to downtime and poor performance. Fault tolerance is pivotal in modern computing systems by preventing downtime and service disruptions, even during failures. However, adopting fault tolerance comes with additional resource consumption, such as memory, CPU, disk, and network bandwidth usage, impacting system performance. Balancing fault tolerance with system performance is crucial to optimize resource utilization while minimizing the costs associated with detecting and recovering from faults. This paper introduces a node-to-node fault tolerance coordination mechanism for distributed systems to facilitate the tradeoff between fault tolerance and the cost of performance penalties and resource consumption. The proposed mechanism is preliminarily implemented on HDFS cluster. Our proposal enables opportunities to minimize the cost of the fault tolerance impact on performance and resource usage compared to the existing fault tolerance coordination mechanism.

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Cooking With Agents: Designing Context-aware Voice Interaction 24

Cooking With Agents: Designing Context-aware Voice Interacti...

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Proceedings of the CHI Conference on Human Factors in Computing systems

作者： Razan Jaber Sabrina Zhong Sanna Kuoppamäki Aida Hosseini Iona Gessinger Duncan P Brumby Benjamin R. Cowan Donald Mcmillan Department of Computer and System Sciences Stockholm University Sweden and Department of Computer and System Sciences Stockholm University Sweden UCL Interaction Centre University College London United Kingdom and UCL Interaction Centre University College London United Kingdom Department of Biomedical Engineering and Health Systems KTH Royal Institute of Technology Sweden and Department of Biomedical Engineering and Health Systems KTH Royal Institute of Technology Sweden KTH Royal Institute of Technology Sweden and KTH Royal Institute of Technology Sweden School of Information and Communication Studies University College Dublin Ireland and School of Information and Communication Studies University College Dublin Ireland School of Information & Communication Studies University College Dublin Ireland and School of Information & Communication Studies University College Dublin Ireland Department of Computer and Systems Sciences Stockholm University Sweden and Department of Computer and Systems Sciences Stockholm University Sweden

ISBN: (纸本)9798400703300

Voice Agents (VAs) are touted as being able to help users in complex tasks such as cooking and interacting as a conversational partner to provide information and advice while the task is ongoing. Through conversation analysis of 7 cooking sessions with a commercial VA, we identify challenges caused by a lack of contextual awareness leading to irrelevant responses, misinterpretation of requests, and information overload. Informed by this, we evaluated 16 cooking sessions with a wizard-led context-aware VA. We observed more fluent interaction between humans and agents, including more complex requests, explicit grounding within utterances, and complex social responses. We discuss reasons for this, the potential for personalisation, and the division of labour in VA communication and proactivity. Then, we discuss the recent advances in generative models and the VAs interaction challenges. We propose limited context awareness in VAs as a step toward explainable, explorable conversational interfaces.

关键词： conversation analysis conversational user interfaces cooking voice interfaces

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An Haptic Display for Visually Impaired Pedestrian Navigation 1st

An Haptic Display for Visually Impaired Pedestrian Navigatio...

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1st International Conference of Advanced Computing and Informatics, ICACIN 2020

作者： Alzighaibi, Sara Bouaziz, Rahma Kammoun, Slim Information System Department College of Computer Science and Engineering Taibah University Medina Saudi Arabia Computer Science Department College of Computer Science and Engineering Taibah University Medina Saudi Arabia ReDCAD University of Sfax Sfax Tunisia Research Laboratory of Technologies of Information and Communication & Electrical Engineering University of Tunis Tunis Tunisia

ISBN: (纸本)9789811560477

Sight is one of the major senses that allows people to travel safely, freely, and independently of others. In their daily life, visually impaired people are confronting challenging tasks such as reading or writing. Navigation and direction finding, particularly in the unfamiliar environment, are remaining as one of the main issues for visually impaired (VI) individuals. Several ways have been emerged to help VI orientation and mobility such as electronic orientation aids which can be further studied and developed. This work aims to improve VI navigation by proposing a new tactile interface that will be designed and implemented with the use of vibrators and Arduino board. The proposed interface targets to increase the quality of life and independence for VI. Also, evaluation performed with VI pedestrian will give us further information and knowledge regarding haptic perceptions and effectiveness of such interface and interaction technique. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Navigation

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Wat Arun Metaverse: A Virtual Reality Based Approach for Digitization, Education, and Exploration of Cultural Heritage

Wat Arun Metaverse: A Virtual Reality Based Approach for Dig...

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International Conference on Electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： Avishi Waidyaratne Suebphong Noisri Kunanont Srisupakwong SK Wijayasekara Ratchaneekorn Ratchatakorntrakoon Bhadravarna Bongsasilp Pisit Vanichchanunt Lunchakorn Wuttisittikulkij Department of Electrical Engineering Wireless Communication Ecosystem Research Unit Chulalongkorn University Bangkok Thailand Dept. of Computer System Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Institute of Thai Studies Chulalongkorn University Bangkok Thailand Department of Fine Art Office of Archaeology Bangkok Thailand Department of Electrical and Computer Engineering King Monkuts University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

Wat Arun, or the ‘Temple of Dawn,’ is a well-known Buddhist temple and a significant tourist destination in Thailand. The temple serves as a hub for research on Buddhist studies and rich Thai culture. Overcoming the limitations in traditional cultural preservation, and educational methods, this paper describes a transformative Virtual Reality (VR) based metaverse design to attract users to explore this historical landmark. The methodology involves advanced Three-Dimensional (3D) digitization techniques for 3D model optimization, and customization, and a gamified educational framework. Results show the preliminary stage of the overall process of 3D implementation on Wat Arun metaverse. This study contributes as a vital platform for educators, researchers, and enthusiasts seeking an authentic and interactive exploration of rich cultural heritages. By setting a precedent for immersive and engaging experiences in heritage exploration, this research extends the boundaries of how cultural sites can be understood, appreciated, and preserved in the digital era.

关键词： Solid modeling Three-dimensional displays Satellites Metaverse Education Telecommunications Cultural differences

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A new design of a digital filter for an efficient field programmable gate array using quantum dot technology

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Materials Science and engineering: B 2024年 300卷

作者： Taghavirashidizadeh, Ali Ahmadpour, Seyed-Sajad Ahmed, Suhaib Jafari Navimipour, Nima Ramkrishna Kassa, Sankit Yalcin, Senay Tehran Iran Department of Computer Engineering Faculty of Engineering and Natural Sciences Kadir Has University Istanbul Turkey Chitkara University Institute of Engineering and Technology Punjab India Department of Electronics and Communication Engineering Model Institute of Engineering and Technology Jammu India Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou64002 Taiwan Pune India Department of Energy System Engineering School of Engineering and Natural Sciences Bahçeşehir University Istanbul Turkey

Digital filtering algorithms are most frequently used to implement generic-based Field-programmable gate arrays (FPGAs) chips, which are used for higher sampling rates. In the filtering structure, delay and occupied areas play a vital role. Since the existing structures suffered from shortcomings such as high delay and high occupied area, implementing a high-performance digital filter circuit with high speed and low occupied area based on unique technology can significantly improve the performance of whole FPGA structures. One of the best technologies to implement this vital structure to solve these shortcomings is quantum-dot cellular automata (QCA) technology. This paper presents several new efficient full adders for digital filter applications based on quantum technology, including a multiplier, AND gate, and accumulator. The QCADesigner 2.0.3 tool is used to create and validate the suggested designs. According to the results, all designed circuits have simple structures with few quantum cells, low area, and low latency. © 2023

关键词： Nanocrystals

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