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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5666-5675页

作者： Karim, Tasmin Shaon, Md. Shazzad Hossain Ali, Md. Mamun Ahmed, Kawsar Bui, Francis M. Chen, Li Department of Computer Science and Engineering Birulia Dhaka Savar1216 Bangladesh University of Saskatchewan Division of Biomedical Engineering SaskatoonSKS7N 5A9 Canada University of Saskatchewan Department of Electrical and Computer Engineering SaskatoonSKS7N 5A9 Canada Health Informatics Research Laboratory Department of Computer Science and Engineering Birulia Dhaka Savar1216 Bangladesh Mawlana Bhashani Science and Technology University Group of Bio-photomati Information and Communication Technology Tangail Santosh1902 Bangladesh

Antimicrobial peptides (AMPs) play a vital role in the immune defence systems of various organisms and have garnered significant attention for their potential applications in biotechnology and medicine. There are several approaches to identifying AMPs including clinical isolation and characterization, functional genomics, microbiology techniques, and others. However, these methods are mostly expensive, time-consuming, and require well-equipped labs. To overcome these challenges, machine learning models are a potential solution due to their robustness and high predictive capability with less time and cost. In this study, we explored the efficacy of stacking-based ensemble machine-learning techniques to identify AMPs with higher accuracy and precision. Five distinct feature extraction methods, namely amino acid composition, dipeptide composition, moran autocorrelation, geary autocorrelation, and pseudoamino acid composition, were employed to represent the sequence characteristics of peptides. To build robust predictive models, different traditional machine learning algorithms were applied. Additionally, we developed a novel stacking classifier, aptly named StackAMP, to harness the collective power of these algorithms. Our results demonstrated the exceptional performance of the proposed StackAMP ensemble method in AMP identification, achieving an accuracy of 99.97%, 99.93% specificity, and 100% sensitivity. This high accuracy underscores the effectiveness of our approach, which has promising outcomes for the rapid and accurate identification of AMPs in various biological contexts. This study not only contributes to the growing body of knowledge in the field of AMP recognition but also offers a practical tool with potential applications in drug discovery, biotechnology, and disease prevention. © 2024 IEEE.

关键词： Amino acids

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Automated Detection of Harmful Insects in Agriculture: A Smart Framework Leveraging IoT, Machine Learning, and Blockchain

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4787-4798页

作者： Rahman, Wahidur Hossain, Muhammad Minoar Hasan, Md. Mahedi Iqbal, Md. Sadiq Rahman, Mohammad Motiur Fida Hasan, Khondokar Moni, Mohammad Ali Mawlana Bhashani Science and Technology University Department of Computer Science and Engineering Tangail1902 Bangladesh Uttara University Department of Computer Science and Engineering Dhaka1230 Bangladesh Prime University Department of Management and Information System Mirpur Dhaka1216 Bangladesh Bangladesh University Department of Computer Science and Engineering Dhaka1207 Bangladesh School of Professional Studies CanberraNSW2052 Australia Artificial Intelligence and Cyber FuturesInstitute Charles Sturt University AI & Digital Health Technology BathurstNSW2795 Australia

Paddy cultivation is a significant global economic sector, with rice production playing a crucial role in influencing worldwide economies. However, insects in paddy farms predominantly impact the growth rate and ecological equilibrium of the agricultural field. Hence, the precise and timely identification of insects in agricultural settings presents a potential strategy for addressing this issue. This study aims to implement an automated system for paddy farming by employing a real-time framework that incorporates the Internet of Things (IoT), blockchain technology, and Deep Learning (DL) algorithms. The primary emphasis of the DL-based system is on the timely identification of pests. In contrast, integrating the IoT and blockchain technologies facilitates stablishing a fully automated system with security within the agricultural domain. The DL-based system includes a secondary dataset of paddy insects, and then preprocessing, feature extraction, and identification have been performed. Besides, an IoT-based system is embodied with a camera module and microprocessor, accompanied by some apparatus required to automate the whole system. In addition, the research also includes the blockchain to secure each individual data transmission among the several IoT components and the cloud server. While examining the proposed solution, various experimental data have been systematically documented and analyzed. The proposed framework attained a peak accuracy of 98.91% using the VGG19 model and ensemble classifiers to detect the pest with a specificity of 99.14% and a precision of 98.21%. The study additionally quantifies the mean duration of the cloud response when integrated with IoT, yielding an average time of 1.71 s after pest identification. Nevertheless, the system has exhibited a high level of efficacy in the context of real-time monitoring and automation of paddy farms. © 2020 IEEE.

关键词： Blockchain

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Cache Allocation in Multi-Tenant Edge Computing: An Online Model-Based Reinforcement Learning Approach

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IEEE Transactions on Cloud Computing 2025年第2期13卷 459-472页

作者： Ben-Ameur, Ayoub Araldo, Andrea Chahed, Tijani Dán, György Institut Polytechnique de Paris SAMOVAR Telecom SudParis Palaiseau91120 France KTH Royal Institute of Technology Division of Network and Systems Engineering School of Electrical Engineering and Computer Science Stockholm11428 Sweden

We consider a Network Operator (NO) that owns Edge Computing (EC) resources, virtualizes them and lets third party Service Providers (SPs) run their services, using the allocated slice of resources. We focus on one specific resource, i.e., cache space, and on the problem of how to allocate it among several SPs in order to minimize the backhaul traffic. Due to confidentiality guarantees, the NO cannot observe the nature of the traffic of SPs, which is encrypted. Allocation decisions are thus challenging, since they must be taken solely based on observed monitoring information. Another challenge is that not all the traffic is cacheable. We propose a data-driven cache allocation strategy, based on Reinforcement Learning (RL). Unlike most RL applications, in which the decision policy is learned offline on a simulator, we assume no previous knowledge is available to build such a simulator. We thus apply RL in an online fashion, i.e., the model and the policy are learned by directly perturbing and monitoring the actual system. Since perturbations generate spurious traffic, we thus need to limit perturbations. This requires learning to be extremely efficient. To this aim, we devise a strategy that learns an approximation of the cost function, while interacting with the system. We then use such an approximation in a Model-Based RL (MB-RL) to speed up convergence. We prove analytically that our strategy brings cache allocation boundedly close to the optimum and stably remains in such an allocation. We show in simulations that such convergence is obtained within few minutes. We also study its fairness, its sensitivity to several scenario characteristics and compare it with a method from the state-of-the-art. © 2013 IEEE.

关键词： Contrastive Learning

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Damman grating for array pumping of single-longitudinal-mode YVO4laser 14

Damman grating for array pumping of single-longitudinal-mode...

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Holography, Diffractive Optics, and Applications XIV 2024

作者： Cao, Weilin Xie, Bin Zhang, Dawei Li, Jianlang School of Optical-Electrical Information and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

ISBN: (纸本)9781510682085

The Dammann Grating (DG), a binary phase grating, efficiently divides incident light into equal-intensity sub-beams, making it ideal for beam splitting applications. In this research, an array-pumped, microchip Nd:YVO4 laser was explored by incorporating a DG into the collimation part of the pump optical path, to obtain single-longitudinal-mode (SLM) and multi-beam output at 1064 nm. As a result, 2×2 arrayed output of the laser was obtained with a total output power of 558.0 mW at 1.86-W pump power, exhibiting a slope efficiency of 36.3%, offering distinct advantages in SLM operation due to its thermal management capabilities in homogenizing thermal gradients and thus resulting in highpower operation with high beam quality. Except for the 2×2 array pumping, high-power SLM operation also can be expected by applying higher-order array pumping. © 2024 SPIE. All rights reserved.

关键词： Pumps

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Efficient conversion of acoustic vortex using extremely anisotropic metasurface

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Frontiers of physics 2024年第4期19卷 257-264页

作者： Zhanlei Hao Haojie Chen Yuhang Yin Cheng-Wei Qiu Shan Zhu Huanyang Chen Institute of Electromagnetics and Acoustics and Department of Physics College of Physical Science and TechnologyXiamen UniversityXiamen 361005China Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3117583Singapore Department of Mechanical and Electrical Engineering Xiamen UniversityXiamen 361005China Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen UniversityXiamen 361005China

Vortex wave and plane wave,as two most fundamental forms of wave propagation,are widely applied in various research ***,there is currently a lack of basic mechanism to enable arbitrary conversion between *** this paper,we propose a new paradigm of extremely anisotropic acoustic metasurface(AM)to achieve the efficient conversion from 2D vortex waves with arbitrary orbital angular momentum(OAM)to plane *** underlying physics of this conversion process is ensured by the symmetry shift of AM medium parameters and the directional compensation of ***,this novel phenomenon is further verified by analytical calculations,numerical demonstrations,and acoustic experiments,and the deflection angle and direction of the converted plane waves are qualitatively and quantitatively confirmed by a simple *** work provides new possibilities for arbitrary manipulation of acoustic vortex,and holds potential applications in acoustic communication and OAM-based devices.

关键词： efficient wave conversion vortex wave plane wave orbital angular momentum acoustic metasurface

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Enhancing sound pressure output in graphene-based hybrid bone conduction hearing aids through electromagnetic and electrostatic integration

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Nano Research 2025年第4期18卷 425-434页

作者： Dong-Kwan Lee Hyunwoo Baek Byung-Ho Kang § Jongchan Yoo Kun-Woo Nam Sang Hyun Lee Illsoo Sohn Eunjung Han June Choi Sung-Hoon Park Department of Mechanical Engineering Soongsil UniversitySeoul 06978Republic of Korea Department of Otorhinolaryngology-Head and Neck Surgery Korea University College of MedicineAnsan HospitalAnsan 15355Republic of Korea School of Electrical Engineering Korea UniversitySeoul 02841Republic of Korea Department of Computer Science and Engineering Seoul National University of Science and TechnologySeoul 01811Republic of Korea

Bone conduction hearing aids(BCHA)actively serve patients with conductive hearing loss or external auditory canal problems,including auditory canal atresia,ossicular dislocation,*** are typically categorized into surgically implanted devices,embedded directly into the skull,and adhesive devices,which transmit sound through the *** latter are advantageous for being noninvasive and suitable for children under ***,adhesive devices,due to their sound transmission method,require enhanced sound output performance compared to implanted ***,known for its low mass density yet excellent mechanical and electrical properties,finds application in various electronic ***,it serves as a diaphragm in electroacoustic transducers,enabling stable vibrations across broad frequency *** electroacoustic transducers of BCHA are typically driven by electromagnetic methods,which may be effective in low-frequency ranges but not in high-frequency *** study successfully introduced a hybrid approach that combines the complementary advantages of both electromagnetic and electrostatic modes by utilizing a graphene sheet as the diaphragm for a hybrid graphene *** electrostatic mode,which performs better in highfrequency ranges compared to the electromagnetic mode,was implemented in this hybrid *** to the measured frequency response data,the hybrid mode showed up to an 11 dB improvement compared to the electromagnetic mode and up to a 21 dB improvement compared to the electrostatic mode,exhibiting a relatively flat shape over a wide frequency ***,the device’s effectiveness as a BCHA is confirmed through experiments on rabbits,showcasing its potential in auditory aid advancement.

关键词： graphene bone conduction hearing aid loudspeaker frequency response

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Design of Intelligent Solar Cooling System with IoT Monitoring 3rd

Design of Intelligent Solar Cooling System with IoT Monitori...

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3rd International Conference on Emerging Electronics and Automation, E2A 2023

作者： Kushagra, C. Kirtimaan, S. Rushit, P. Jane Joshita, K. Divya Navamani, J. Lavanya, A. Department of Computer Science Engineering SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Electronics and Instrumentation Engineering SRM Institute of Science and Technology Tamil Nadu Kattankulathur India Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Tamil Nadu Kattankulathur India

ISBN: (纸本)9789819730896

Currently, IoT rules many unmanned applications to improve supervision and productivity. The proposed work concentrates on the need for a cooling system for solar Photovoltaic (PV) panels to enhance its efficiency. An increase in temperature will reduce the efficiency of the solar panel. The cooling system should be monitored, automated, and controlled without human intervention. This is achieved by developing a web App by which the cooling system can be controlled automatically. DHT11–Temperature and Humidity Sensor is used to monitor the temperature of the panel. If the module temperature increases more than 35 °C to 60 °C, the sensor sends the signal to the actuator to cool the PV panel, which will increase the output power. This technique is proposed for solar rooftop home applications where the grey water can be treated and used for cooling the solar panel rather than using fresh, clean water. Finally, a web-interface is done to cool the solar panel with water pumping through the tubes below the panel. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cooling IoT Solar Temperature Web interface

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Novel Darknet traffic data synthesis using Generative Adversarial Networks enhanced with oscillatory Growing Cosine Unit activated convolution layers

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International Journal of Cognitive Computing in engineering 2024年第1期5卷 58-65页

作者： Pradeep C, Antony Amali D, Geraldine Bessie Noel, Mathew Mithra Ghalib, Muhammad Rukunuddin Subramaniam, Prabhakar Rontala Venugopal, Chitra School of Computer Science and Engineering Vellore Institute of Technology Vellore India School of Electrical Engineering Vellore Institute of Technology Vellore India School of Computing De Montfort University Dubai United Arab Emirates Information Systems and Technology Westville South Africa Electrical Engineering & Renewable Energy Oregon Institute of Technology United States

The Darknet is an anonymous, encrypted collection of websites, with a passive listening nature - accepting incoming packets, while not supporting outgoing packets. Thus, it can potentially host criminal or malicious activity and software, becoming a cyber security threat. Network Detection Systems are effective in identifying dark net traffic and mitigating its ill effects. However, capturing and extracting data from raw network traffic for training these systems can be time-intensive and costly. Using the CIC-Darknet 2020 dataset, this paper proposes using a Novel Generative Adversarial Networks (GAN) Architecture generating the required training and testing data for these systems. This uses a combination of Growing Cosine Unit (GCU) activated convolution layers and Dense layers for the Generator. Feature selection with statistical correlation methods is used to select the most relevant features. An independently trained Evaluator network is used to evaluate the generated data. The proposed system is compared to other established Tabular data GANs like Conditional Tabular GAN (CTGAN) and Copula GAN with similar parameters and on the same data. The Proposed GAN architecture outperforms CTGAN and CopulaGAN by 20 % and 10 % in ters of accuracy while also taking 90 % and 30 % less time to train respectively. Results from measuring similarity of data using the Inverted Kolmogorov - Smirnov D statistic also show significantly better results for the Proposed GAN Architecture. This shows significant promise in using Generative models to reduce the time and effort costs associated with collecting and formatting data to use in research and for training detection systems. © 2024

关键词： Generative adversarial networks

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VeFog - Efficient Message Dissemination in VANETs based on Edge, Fog and Cloud Computing 47

VeFog - Efficient Message Dissemination in VANETs based on E...

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47th ICT and Electronics Convention, MIPRO 2024

作者： Jelić, Borna Gluhaković, Mario Mijić, David Ivešić, Toni Balen, Josip TTTech Auto Osijek Croatia Faculty Of Electrical Engineering Computer Science And Information Technology Osijek Croatia

ISBN: (纸本)9798350382495

Technological progress has had a dramatic impact on the automotive industry and the concept of intelligent and connected vehicles is developing rapidly. Vehicles are being equipped with various in-vehicle and environmental sensors that generate huge amounts of data, as well as onboard units that can calculate, store and communicate data with other vehicles, infrastructure and the environment. This has led to the development of Vehicular Ad-hoc Networks (VANETs), which face various challenges due to a heterogeneous and highly dynamic environment, where traditional solutions need to be improved and adapted to meet the networking and processing requirements. The integration of edge and fog computing in VANETs reduces the overhead by placing the necessary resources at the edge of the network closer to the information source. In this paper, we propose VeFog - the new architecture based on edge and fog computing for efficient data processing and dissemination in VANETs. The performance evaluation and simulation results show that the VeFog architecture is efficient, reduces processing time and saves resources with minimal infrastructure utilization. © 2024 IEEE.

关键词： Fog computing

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Enhanced Attitude Stabilization of Quadrotors Using a Single-Axis Constraint Moment Disturbance Obserner

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IEEJ Transactions on Industry Applications 2024年第4期144卷 257-264页

作者： Ichiryu, Atsuhiro Shimada, Akira Electrical Engineering and Computer Science Graduate School of Engineering and Science Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo135-8548 Japan Dept. of Engineering and Design Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo135-8548 Japan

This study proposes a maintaining a quadrotor’s attitude system using a ‘moment disturbance observer’ aimed at enhancing stability. In recent years, quadrotors have become increasingly prevalent in sectors such as agriculture, surveying, logistics, aerial photography, infrastructure inspection, and security. However, with their growing, there have been concerns about potential physical and human harm stemming from accidents. The Ministry of Land, Infrastructure, Transport, and Tourism has reported accidents attributed to challenging maneuvering conditions that have resulted in crashes. This study aims to develop a quadrotor that can maintain a stable attitude during sudden and significant alterations in its orientation. We suggest employing a moment disturbance observer to estimate the necessary moments for stable attitude maintenance. Numerical simulation results show that the proposed method surpasses traditional PID control in terms of attitude stabilization. Furthermore, this method resulted in superior attitude stability in single-axis experiments with a mechanically constrained quadrotor compared to conventional PID control methods. © 2024 The Institute of electrical Engineers of Japan.

关键词： Aerial photography

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