The aquaculture industry has witnessed a significant surge in technological integration over the past decade, leveraging advancements in the Internet of Things (IoT) and Artificial Intelligence (AI) to enhance product...
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ISBN:
(数字)9798350374407
ISBN:
(纸本)9798350374414
The aquaculture industry has witnessed a significant surge in technological integration over the past decade, leveraging advancements in the Internet of Things (IoT) and Artificial Intelligence (AI) to enhance production efficiency. Monitoring the growth of aquatic cultures, such as fishes and prawns, plays a pivotal role in optimizing production. However, traditional methods, notably in prawn aquaculture in Asia, still heavily rely on stress-inducing techniques like netting and manual measurements. This paper proposes a novel approach using YOLO-based detection algorithm with biocode reference point based on the ArUco design to predict prawn size based on the length and are dimension to analysed the improvement in predicting the size. The propose solution is compared extensively using statistical tests against segmentation model with and without fine-tuning. Initial results show that both YOLOv8 segmentation and YOLOv8 with Segment Anything Model (SAM) give similar results with the actual mean length of 15.7 cm and predicted mean lengths are 20.5 cm and 20.8 cm respectively. However, after fine-tuning the parameter, the accuracy of predicted results improved significantly with 15.8 cm for YOLOv8 segmentation and 16 cm for YOLOv8 with SAM. The mean absolute error of 0.93 cm for YOLOv8 segmentation and 1.10 cm for YOLOv8 with SAM, and the width of 0.48 cm and 0.78 cm respectively.
The Internet of Things (IoT) has revolutionized the way people interact, communicate, and perform daily activities in various domains ranging from households to industries and cities. MQTT is one of the commonly adopt...
The Internet of Things (IoT) has revolutionized the way people interact, communicate, and perform daily activities in various domains ranging from households to industries and cities. MQTT is one of the commonly adopted protocols for implementing IoT. However, IoT systems that are connected through MQTT are susceptible to security breaches as MQTT was not originally designed with security as a priority. The credentials and messages transmitted in plaintext by default, thereby compromising data confidentiality and integrity. This study presents a comprehensive analysis of the MQTT protocol, including experimentation on an MQTT system using various cryptographic implementations, such as AES-CBC, RSA, and ECC AES Hybrid Scheme, to assess the processing time and message size. The findings indicate that payload encryption increases processing time and message bytes. Among the cryptographic implementations, RSA incurs the highest processing time, followed by ECC AES Hybrid Scheme and AES- CBC. Furthermore, the study demonstrates the effectiveness of attack prevention between standard MQTT and secured MQTT implementations by simulating various IoT attacks, such as black-box penetration attack, identity spoofing, DoS attack, and MITM attack. The results and subsequent discussion provide insights that answer the research question, revealing the cryptographic algorithms that result in the most overhead on the standard MQTT implementation and their capacity to resist common attacks.
The growing number of connected Internet of Things (IoT) devices has led to the daily growth of network botnet attacks. The networks of compromised devices controlled by a single entity can be used for malicious purpo...
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The paper presents research on the fabrication and electrical characterization of transparent contacts based on ZnO. Contact layers were manufactured in the process of physical vapor deposition (PVD) by the codepositi...
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ISBN:
(数字)9798350377323
ISBN:
(纸本)9798350377330
The paper presents research on the fabrication and electrical characterization of transparent contacts based on ZnO. Contact layers were manufactured in the process of physical vapor deposition (PVD) by the codeposition method, which allowed to obtain thin layers with various compositions and parameters. The evaporation unit NANO36 (Kurt&Lesker) allows real-time control of such parameters as the rate of layer growth, the composition of the obtained structure and its resultant *** tests of the current-voltage characteristics were performed by typical source measure unit KEITHLEY 4200-scs system. Surface analysis was performed using an AFM microscope. The structures can be used in thin-film cells and are an alternative to ITO contacts.
We investigate automated in situ optimization of the potential landscape in a quantum point contact device, using a 3 × 3 gate array patterned atop the constriction. Optimization is performed using the covariance...
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Colossal magnetoresistive (CMR) materials have been widely studied because of their huge potential in spintronic technology. An introduction of secondary phase to the manganite matrix is able to improve the low field ...
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We present a novel solution procedure for initial boundary value problems. The procedure is based on an action principle, in which coordinate maps are included as dynamical degrees of freedom. This reparametrization i...
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The Cosmic Ray Extremely Distributed Observatory (CREDO) pursues a global research strategy dedicated to the search for correlated cosmic rays, so-called Cosmic Ray Ensembles (CRE). Its general approach to CRE detecti...
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Nonnegative matrix factorization seeks to find a basic matrix and a weight matrix to approximate the nonnegative matrix. It has proven to be a powerful low-rank decomposition technique for nonnegative multivariate dat...
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ISBN:
(纸本)9781665442084
Nonnegative matrix factorization seeks to find a basic matrix and a weight matrix to approximate the nonnegative matrix. It has proven to be a powerful low-rank decomposition technique for nonnegative multivariate data. However, its performance largely depends on the assumption of a fixed number of features. In this work, we propose a new probabilistic nonnegative matrix factorization which factorizes a nonnegative matrix into a low-rank factor matrix with {0,1} constraints and a nonnegative weight matrix. In order to automatically learn the potential binary features and feature number. A deterministic Indian buffet process variational inference is introduced to obtain the binary factor matrix. And the weight matrix is set to satisfy the exponential prior. In order to obtain the real posterior distribution of the two factor matrices, a variational Bayesian exponential Gaussian inference model is established. The comparative experiments on both the synthetic and real-world data sets show the efficacy of the proposed method.
Infinite-layer nickelates show high-temperature superconductivity, and the experimental phase diagram agrees well with the one simulated within the dynamical vertex approximation (DΓA). Here, we compare the spin-fluc...
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