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Prediction of Responsivity for Organic Tin-Based Perovskites

SN computer Science 2025年第5期6.0卷 1-9页

作者： Basak, Saurabh Roy, Tanmay Sinha Majumder, Bansari Deb Department of Electronics and Communication Engineering Budge Budge Institute of Technology Budge Budge West Bengal Kolkata India Department of Electrical and Electronics Engineering Institute of Engineering and Management Sector-V Salt Lake City West Bengal Kolkata India Department of Electrical Engineering Narula Institute of Technology West Bengal Kolkata India

Today, organic tin-based perovskite solar cell is a new emerging technology. Different experimental research has proven that the best-suited candidate for this group of perovskites is FASnI₃. The experimental data on external quantum efficiency integrated short circuit current density and photo responsivity are readily available in different research papers. This X-site anion, i.e., iodine (I), can also be replaced by bromine (Br) and chlorine (Cl). Still, no such experimental data of the above-mentioned parameters of FASnX₃, MASnX₃ (X = Cl, Br) is available in the literature. In this research, we have predicted the nature of the external quantum efficiency curve (EQE) and responsivity (R) with respect to the frequency of light by simulation, where MA and FA mean Methylammonium and Formamidinium, respectively. The knowledge of responsivity variation with respect to the input optical frequency of any organic tin-based perovskite is essential for photodetector application. From the responsivity variation curve, it can be easily observed which frequency of incident optical light the responsivity is maximum and minimum. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： External quantum efficiency Organic tin-based perovskite Responsivity Simulation

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Smart Assistance Device for the Visually Challenged: Integrating GPS Technology and Emergency Support Features with RTOS

Smart Assistance Device for the Visually Challenged: Integra...

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2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Kruthika, Y. Das, Anju Parvathy Thampi, M.S. CMR Institute of Technology Department of Electrical and Electronics Engineering Bangalore India CMR Institute of Technology Department of Electronics and Communication Engineering Bangalore India Global Academy of Technology Department of Electronics and Communication Engineering Bangalore India

ISBN: (纸本)9798331540685

There are many problems faced by visually impaired people. Blinds find it very difficult to walk and also do many other small things. Their grief is huge. In this paper a solution is proposed to one of their problems in form of an innovative blind stick. The proposed model of this blind stick contains the smart system that is designed to send an emergency message with the message and location of the user to the guardian. The system contains the GPS and GSM modules which together accomplish this task. Visually impaired are guided by the micro controller which receives the emergency signal through a button. The push button is also connected to a buzzer that is loud enough to catch the attention of people around. Apart from these, the smart stick also contains sensors that are used for object detection. Hence, this model is beneficiary not only to the users but also to the guardians, as can be relieved to some extent. Finally, this paper focuses on developing an assistive technology for individuals with visual impairments. Utilizing an ESP32 micro controller and the FreeRTOS Real Time Operating System, the device leverages GPS technology and integrates emergency support features. Even FreeRTOS supports efficient Inter Process communications like Mutex, Semaphores & message queues etc. This innovative tool aims to enhance user autonomy and security by providing essential navigation and safety functionalities. © 2024 IEEE.

关键词： Global positioning system

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Synergia: Device-Edge Server Association for ISAC-assisted Mobile Edge Computing Systems

Synergia: Device-Edge Server Association for ISAC-assisted M...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Charatsaris, Panagiotis Penafiel, Arianna Santamaria Diamanti, Maria Tsiropoulou, Eirini Eleni Papavassiliou, Symeon National Technical University of Athens Institute of Communication and Computer Systems School of Electrical and Computer Engineering Athens Greece University of New Mexico Dept. of Electrical and Computer Engineering AlbuquerqueNM United States

ISBN: (纸本)9798350351255

The efficient operation of the unified Integrated Sensing and communication (ISAC) - Mobile Edge Computing (MEC) systems is important for enhancing data sensing, communication, and computation processes in next-generation wireless systems. Despite prior research focusing on these systems, little attention has been given to optimizing the device-edge server associations. This paper addresses this gap by introducing the novel two-stage device-edge server association Synergia framework. Firstly, representative utility functions capture the characteristics of the devices and MEC servers by jointly considering their sensing, communication, and computation characteristics. Secondly, the Estimated Synergia framework leverages the Matching Theory to rapidly determine an initial device-server matching by disregarding the devices' externalities, i.e., the matching decisions of other devices. Thirdly, the Accurate Synergia model refines and improves this matching by using the coalition formation games, while considering the devices' externalities in optimizing the utilities of both the devices and the MEC servers. Extensive numerical evaluations demonstrate the Synergia's operational efficiency and scalability, outperforming reinforcement learningbased approaches. Also, a real-world application involving car accident detection validates its applicability. © 2024 IEEE.

关键词： Mobile edge computing

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Build to Win: electrical Hardware Opportunities for STEM Education 14

Build to Win: Electrical Hardware Opportunities for STEM Edu...

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14th IEEE Integrated STEM Education Conference, ISEC 2024

作者： Monagle, Daniel Ponce, Eric A. Leeb, Steven B. Saathoff, Erik K. Brooks, Dylan E. Krause, Thomas C. Green, Daisy H. Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science United States University of Hawai'i Department of Electrical and Computer Engineering Manoa United States

ISBN: (纸本)9798350352801

engineering outreach and introductory courses are essential for motivating and training the next generation of capable engineers. Accessibility and portability of the infrastructure for a STEM course is critical for spreading STEM education and motivation efforts. The ubiquity of student personal computers and laptops provides a convenient platform for introducing computer programming, but the relatively cumbersome equipment deemed necessary for a hands-on electronics learning environment contributes to the lack of electronic circuit hardware exposure for many K-12 students and university undergraduates. This paper presents the relatively low-cost, versatile, electronics platform we have developed at MIT upon which our new, hands-on introductory STEM electrical engineering course has been built and taught in recent years. This paper focuses its discussion on the power supply and measurement systems we have produced that allow students and instructors to engage in hands-on electric circuit exercises and projects without the requirement for expensive laboratory infrastructure. Example demonstrations of introductory laboratory exercises using our platform are shown. © 2024 IEEE.

关键词： Students

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TOPMG: Trust-Based Crowdsourcing through Multilateral Bargaining Game Theory

TOPMG: Trust-Based Crowdsourcing through Multilateral Bargai...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Charatsaris, Panagiotis Adesokan, Adedamola Rahman, Aisha B Tsiropoulou, Eirini Eleni Papavassiliou, Symeon National Technical University of Athens Institute of Communication and Computer Systems School of Electrical and Computer Engineering Athens Greece University of New Mexico Dept. of Electrical and Computer Engineering AlbuquerqueNM United States

ISBN: (纸本)9798350351255

Crowdsourcing plays a critical role in modern information gathering and task execution, yet it faces challenges regarding the task selection and equitable monetary incentives distribution. In this paper, we introduce the TOPMG framework, which addresses these challenges by enabling the workers to select tasks based on their historically experienced monetary incentives and the platforms' trustworthiness. Specifically, the TOPMG framework utilizes a reinforcement learning approach based on the principles of Optimistic Q-learning with Upper Confidence Bound (OQ-UCB) algorithm, guiding the platform selection process by considering the workers' monetary incentives, profit, and the platforms' trustworthiness. Also, the proposed framework introduces a multilateral bargaining game to allocate the platforms' monetary incentives to the workers by prioritizing their information contribution, fairness, and the platforms' reputation. Simulation results demonstrate TOPMG's operational dynamics, scalability, and efficacy, as well as its superiority over existing methodologies. © 2024 IEEE.

关键词： Reinforcement learning

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Optimization and Performance Evaluation of Distributed Multi-RIS-Enhanced Wireless communication System

Optimization and Performance Evaluation of Distributed Multi...

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2024 International Conference on Advances in Computing, communication, electrical, and Smart Systems, iCACCESS 2024

作者： Islam, Mohammad Shariful Mostafa, Md Golam Military Institute of Science and Technology Department of Electrical Electronic and Communication Engineering Dhaka Bangladesh

ISBN: (纸本)9798350350289

There are two parts to this study, and this is the second part. This paper assesses the performance of two distributed multi-reconfigurable intelligent surface (MRIS) assisted systems. Two MRIS-enhanced wireless communication methods are evaluated in terms of Energy Efficiency (EE) and Sum Rate (SR) using a mathematical framework that is provided for both schemes. Scheme One obtains a greater SR than Scheme Two, while Scheme Two performs better in terms of EE, according to the observations. Both methods' EE and SR results are shown, and it is clear that employing more antennas on the transmitting side greatly increases channel capacity. The significant effects of transmit power and element settings on system performance are highlighted in this study. © 2024 IEEE.

关键词： Energy efficiency

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A Deep Learning Approach for Detecting Malware Using Autoencoder

IAENG International Journal of Computer Science

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IAENG International Journal of computer Science 2024年第8期51卷 1051-1059页

作者： Panchagnula, Venu Madhav Satya Keerthi, N.V.L.Ch. Surekha, S. Sujatha, R. Veeraiah, Duggineni Ramesh, Eluri Lakshmi, B. Electronics and Communication Engineering Department Prasad V Potluri Siddhartha Institute of Technology Andhra Pradesh Vijayawada India Computer Science and Engineering Department Koneru Lakshmaiah Education Foundation Andhra Pradesh Guntur India AIML Department Vignana Bharathi Institute of Technology Ghatkesar Hyderabad India Information Technology Department M. Kumarasamy College of Engineering Karur India Computer Science and Engineering Department Lakireddy Bali Reddy College of Engineering Andhra Pradesh Mylavaram India Computer Science and Engineering Department R.V.R & J. C. College of Engineering Guntur India Electronics and Communication Engineering Department Rajiv Gandhi University of Knowledge Technologies Andhra Pradesh Nuzvid India

Research in the field of malware detection is currently leaning toward methods based on artificial intelligence algorithms due to the increasing limitations of traditional detection methods and the increasing accuracy of these methods. This study therefore introduces a novel approach to malware detection. This method integrates a deep learning model's autoencoder network with a grayscale graphic depiction of malware. By looking at the autoencoder's reconstruction error, we may assess if the grey-scale picture approach is feasible to use for malware detection. Additionally, it differentiates between malicious and safe software by utilizing the autoencoder's dimensionality reduction capabilities. Using the Android dataset, our newly introduced detection model attained a 95% accuracy and maintained a consistently high F-score of approximately 95%. This outperformed more conventional methods of machine learning detection. © (2024), (International Association of Engineers). All Rights Reserved.

关键词： Malware

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Optimization of Cooperative RelayingMolecular communications for Nanomedical Applications

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computer Modeling in engineering & Sciences 2024年第2期138卷 1259-1275页

作者： Eman S.Attia Ashraf A.M.Khalaf Fathi E.Abd El-Samie Saied M.Abd El-atty Konstantinos A.Lizos Osama Alfarraj Heba M.El-Hoseny Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61111Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Informatics Faculty of Mathematics and Natural SciencesUniversity of Oslo(UiO)OsloNorway Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Department of Computer science The Higher Future Institute for Specialized Technological StudiesEl ShoroukEgypt

Recently,nano-systems based on molecular communications via diffusion(MCvD)have been implemented in a variety of nanomedical applications,most notably in targeted drug delivery system(TDDS)***,because the MCvD is unreliable and there exists molecular noise and inter symbol interference(ISI),cooperative nano-relays can acquire the reliability for drug delivery to targeted diseased cells,especially if the separation distance between the nano transmitter and nano receiver is *** this work,we propose an approach for optimizing the performance of the nano system using cooperative molecular communications with a nano relay scheme,while accounting for blood flow effects in terms of drift *** fractions of the molecular drug that should be allocated to the nano transmitter and nano relay positioning are computed using a collaborative optimization problem solved by theModified Central Force Optimization(MCFO)*** the previous work,the probability of bit error is expressed in a closed-form *** is used as an objective function to determine the optimal velocity of the drug molecules and the detection threshold at the nano *** simulation results show that the probability of bit error can be dramatically reduced by optimizing the drift velocity,detection threshold,location of the nano-relay in the proposed nano system,and molecular drug budget.

关键词： Nanomedical system molecular communication cooperative relay optimization

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Efficient Classification of Rice Varieties Using Optimized Convolutional Neural Networks 8

Efficient Classification of Rice Varieties Using Optimized C...

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8th IEEE International Conference on Information and communication Technology, CICT 2024

作者： Pathak, Abhishek Kumar Singh, Ankit Kumar Bhatia, Vimal Singh, Puneet Indian Institute of Technology Department of Electrical Engineering Indore India Motihari College of Engineering Department of Computer Science and Engineering India

ISBN: (纸本)9798331531539

Rice type classification is a crucial task in agri-cultural automation, aimed at improving quality control and ensuring market standards. This study presents a deep learning-based approach using a optimized Convolutional Neural Network (CNN) model implemented with PyTorch to classify five rice varieties: Arborio, Basmati, Ipsala, Jasmine, and Karacadag. Our proposed model diverges from conventional methods that rely heavily on complex machine learning algorithms or pretrained CNN architectures like MobileNetV2, VGG16, EfficientNetB0 etc., which require a large number of parameters and layers, re-sulting in increased computational complexity. Through proposed approach, we achieved a remarkable 99.81% validation accuracy and a minimal validation loss of 0.01 % with a significantly reduced model size 30.76 MB. The simplicity of the proposed CNN architecture not only enhances computational efficiency but also maintains high accuracy, making it a viable solution for rice type classification in practical applications. This study demonstrates that a fine-tuned CNN model can outperform more complex models, providing an efficient and effective alternative for agricultural classification tasks. © 2024 IEEE.

关键词： Convolutional neural networks

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A New MRACS Approach for High-order System Following Low-order Model Using State Variables Taking from the Model

A New MRACS Approach for High-order System Following Low-ord...

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2024 International Conference on Advanced Control Systems and Automation Technologies, ACSAT 2024

作者： Wei, Yongdong Liu, Xiaojing Kong, Jiayi Cheng, Zixuan Fang, Wen Beijing Institute of Graphic Communication Department of Mechanical and Electrical Engineering Beijing102600 China

ISBN: (纸本)9798331541668

This paper proposes a model reference adaptive control system (MRACS) approach for high-order systems that are required to follow a low-order model, utilizing state variables derived from the model itself. Drawing from Popov hyperstability theory, the method addresses several critical challenges in control system design. The MRAC strategy is employed to tackle the issue of unmeasurable plant states, enabling the control system to adaptively adjust despite the lack of direct state measurement. This adaptation is crucial in maintaining system stability and performance in the presence of uncertainties. To enhance the robustness of the control system, an adjustable linear compensator is introduced. This compensator alleviates the need for the assumption of strictly positive real conditions, which is often a limitation in traditional control methods. By incorporating this flexible compensation mechanism, the proposed approach ensures better handling of various system dynamics and uncertainties, thereby increasing the overall reliability of the control system. The effectiveness of the proposed MRACS approach is substantiated through comprehensive digital simulation results. These results demonstrate that the controlled object is capable of closely following the output of the reference model, highlighting the robustness and adaptability of the method. This capability is particularly advantageous in practical engineering applications, where precision and reliability are paramount. © 2024 IEEE.

关键词： Model reference adaptive control

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