We introduce a novel framework for acquisition of analog signals by combining compressive sensing (CS) and the shift-invariant (SI) reconstruction procedure. We reinterpret the random demodulator as a system that acqu...
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Rainfall plays a significant role in managing the water level in the *** unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the *** individuals,especially those in the agric...
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Rainfall plays a significant role in managing the water level in the *** unpredictable amount of rainfall due to the climate change can cause either overflow or dry in the *** individuals,especially those in the agricultural sector,rely on rain *** rainfall is challenging because of the changing nature of the *** area of Jimma in southwest Oromia,Ethiopia is the subject of this research,which aims to develop a rainfall forecasting *** estimate Jimma's daily rainfall,we propose a novel approach based on optimizing the parameters of long short-term memory(LSTM)using Al-Biruni earth radius(BER)optimization algorithm for boosting the fore-casting accuracy.N ash-Sutcliffe model eficiency(NSE),mean square error(MSE),root MSE(RMSE),mean absolute error(MAE),and R2 were all used in the conducted experiments to assess the proposed approach,with final scores of(0.61),(430.81),(19.12),and(11.09),***,we compared the proposed model to current machine-learning regression models;such as non-optimized LSTM,bidirectional LSTM(BiLSTM),gated recurrent unit(GRU),and convolutional LSTM(ConvLSTM).It was found that the proposed approach achieved the lowest RMSE of(19.12).In addition,the experimental results show that the proposed model has R-with a value outperforming the other models,which confirms the superiority of the proposed *** the other hand,a statistical analysis is performed to measure the significance and stability of the proposed approach and the recorded results proved the expected perfomance.
The scope of the Internet of Things(IoT)applications varies from strategic applications,such as smart grids,smart transportation,smart security,and smart healthcare,to industrial applications such as smart manufacturi...
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The scope of the Internet of Things(IoT)applications varies from strategic applications,such as smart grids,smart transportation,smart security,and smart healthcare,to industrial applications such as smart manufacturing,smart logistics,smart banking,and smart *** the advancement of the IoT,connected devices become smart and intelligent with the help of sensors and ***,issues and challenges need to be addressed regarding the data reliability and protection for signicant nextgeneration IoT applications like smart *** these next-generation applications,there is a requirement for far-reaching privacy and security in the ***,blockchain systems have emerged as a key technology that changes the way we exchange *** emerging technology has revealed encouraging implementation scenarios,such as secured digital *** a technical advancement,the blockchain network has the high possibility of transforming various industries,and the next-generation healthcare IoT(HIoT)can be one of those *** have been several studies on the integration of blockchain networks and ***,blockchain-as-autility(BaaU)for privacy and security in HIoT systems requires a systematic *** paper reviews blockchain networks and proposes BaaU as one of the *** proposed BaaU-based framework for trustworthiness in the next-generation HIoT systems is divided into two *** rst scenario suggests that a healthcare service provider integrates IoT sensors such as body sensors to receive and transmit information to a blockchain network on the IoT *** second proposed scenario recommends implementing smart contracts,such as Ethereum,to automate and control the trusted devices’subscription in the HIoT services.
Smart grids are popular areas of research as they are an essential component of smart cities, smart homes, IoT, and other popular research areas. Scientific experiments in smart grids may be conducted by researchers w...
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Detecting deepfake content presents a formidable challenge, necessitating advanced methodologies. This paper proposes a holistic strategy employing Facenet_pytorch, MTCNN, and InceptionResnetV1 for robust deepfake det...
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ISBN:
(数字)9798350365269
ISBN:
(纸本)9798350365276
Detecting deepfake content presents a formidable challenge, necessitating advanced methodologies. This paper proposes a holistic strategy employing Facenet_pytorch, MTCNN, and InceptionResnetV1 for robust deepfake detection. Facenet_pytorch serves as the cornerstone for facial feature recognition, while MTCNN efficiently identifies faces in images during preprocessing. InceptionResnetV1 scrutinizes visual details to detect subtle anomalies indicative of manipulation, such as unnatural facial expressions and incongruent lip synchronization. Our approach underscores the importance of maintaining a delicate balance between accurate detection and individual privacy rights. By leveraging these advanced models, we achieve significant strides in differentiating manipulated content from authentic media, contributing to the ethical deployment of deepfake detection technologies.
We consider the identifiability issue of maximum-likelihood based activity detection in massive MIMO-based grant-free random access. An intriguing observation by Chen et al. [1] indicates that the identifiability unde...
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Microcomputers and medical devices with signal transceivers that operate on a specific radio display constitute the backbone of wireless sensor networks (WS Ns) that monitor environmental conditions (temperature, pres...
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It is known that two-dimensional two-component fundamental solitons of the semivortex (SV) type, with vorticities (s+,s−)=(0,1) in their components, are stable ground states (GSs) in the spin-orbit-coupled (SOC) binar...
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It is known that two-dimensional two-component fundamental solitons of the semivortex (SV) type, with vorticities (s+,s−)=(0,1) in their components, are stable ground states (GSs) in the spin-orbit-coupled (SOC) binary Bose-Einstein condensate with the contact self-attraction acting in both components, in spite of the possibility of the critical collapse in the system. However, excited states (ESs) of the SV solitons, with the vorticity set (s+,s−)=(S+,S++1) and S+=1,2,3,..., are unstable in the same system. We construct ESs of SV solitons in the SOC system with opposite signs of the self-interaction in the two components. The main finding is stability of the ES-SV solitons, with the extra vorticity (at least) up to S+=6. The threshold value of the norm for the onset of the critical collapse, Nthr, in these excited states is higher than the commonly known critical value, Nc≈5.85, associated with the single-component Townes solitons, Nthr increasing with the growth of S+. A velocity interval for stable motion of the GS-SV solitons is found too. The results suggest a solution for the challenging problem of the creation of stable vortex solitons with high topological charges.
The Distributed Sensing and computing Over Sparse Environments (DISCOVER) testbed is a pioneering cyberinfrastructure initiative designed to advance research in distributed computing and networking tailored to rural, ...
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ISBN:
(数字)9798331538323
ISBN:
(纸本)9798331538330
The Distributed Sensing and computing Over Sparse Environments (DISCOVER) testbed is a pioneering cyberinfrastructure initiative designed to advance research in distributed computing and networking tailored to rural, remote, and sparsely populated regions. Supported by the National Science Foundation (NSF), DISCOVER integrates a network of configurable Internet-of-Things (IoT) nodes—including stationary sensors, drones, and terrestrial rovers—across three key sites: Northern Arizona University (NAU), Clemson University, and Navajo Technical University (NTU). This collaboration offers a unique platform to explore innovative algorithms and methodologies addressing the technical challenges of under-served areas, with an emphasis on environmental and civil disaster response. The testbed enables a wide range of experiments, such as regional-scale data collection, heterogeneous networked services, distributed artificial intelligence (AI), distributed multi-robot control, and communication-aware software for resource-constrained networks. An online portal enhances accessibility, allowing researchers to request resources, upload experimental code, and retrieve data, with pre-integrated deep learning models for applications like human posture detection, object detection, and wildfire detection. This paper outlines the testbed’s architecture, operational sites, supported experiment types, ongoing research efforts, and its educational and outreach impacts, highlighting its role in fostering scientific innovation.
Pursuing a target in the presence of obstacles requires that an autonomous mobile robot keeps sight of the target in a way robust to the target's unknown behavior. This paper presents visually safe pursuit control...
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Pursuing a target in the presence of obstacles requires that an autonomous mobile robot keeps sight of the target in a way robust to the target's unknown behavior. This paper presents visually safe pursuit control, which keeps a target with the unknown motion inside the camera's field of view while preventing occlusion caused by spherical obstacles. Framed as forward invariance of sets in the SE(3) state space, visual safety is ensured by the Control Barrier Functions (CBFs) approach. Concretely, by showing the Input-to-State stability of the vision-based observer that estimates the target's motion, we design safety certificates for visual safety that accommodate uncertainties in the target's motion. This enables us to synthesize a safe controller as a Quadratic Programming problem. Finally, the theoretical results are verified via a simulation of a visual pursuit scenario.
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