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Macroalgae as Blue Carbon Reservoirs and Bioindicators of Metal Pollution in the Saudi Arabian Red Sea: A Comparative Study of Coral Reef and Seagrass Meadow Habitats

SSRN

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SSRN 2024年

作者： Cai, Chunzhi Anton, Andrea Duarte, Carlos M. Agusti, Susana King Abdullah University of Science and Technology Marine Science Program The Biological and Environmental Sciences and Engineering Division Thuwal23955 Saudi Arabia Mediterranean Institute for Advanced Studies Esporles Illes Balears07190 Spain

Macroalgae are vital components of blue carbon ecosystems, yet their elemental compositions in the Red Sea are not well understood. This study analyzed 22 elements in 161 macroalgae blades from 13 species in the Saudi Arabian Red Sea. Macroalgae from coral reefs had higher K, As, and Sr but lower TN (Total nitrogen), Na, Mg, Al, P, S, Cr, Mn, Fe, and Zn compared to those from seagrass meadows, likely due to proximity to human activities. In the Southern Red Sea, macroalgae showed lower Sr but higher TOC (Total organic carbon), TN, P, and Cd compared to the North, suggesting nutrient inflows from the Indian Ocean. Macroalgae blades have lower carbon sequestration capacity than seagrass and mangrove leaves but are more effective bioindicators of metal pollution. Halymenia sp., Caulerpa taxifolia, and Dyctiota sp. showed the highest TOC, TN, and P contents among red, green, and brown macroalgae, highlighting their role in carbon sequestration and nutrient cycling. Amphiroa fragilissima, Udotea flabellum, and Padina sp. emerged as promising metal pollution bioindicators. Macroalgae from Al Birk, Al Lith, Thuwal, Yanbu, and Al Wajh exhibited alarming Cr (~10.9 mg kg−1) and Ni (~27.2 mg kg−1) levels, exceeding toxicity thresholds, urging stringent pollution control measures. © 2024, The Authors. All rights reserved.

关键词： Biomarkers

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A Novel Binary Emperor Penguin Optimizer for Feature Selection Tasks

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computers, Materials & Continua 2022年第3期70卷 6239-6255页

作者： Minakshi Kalra Vijay Kumar Manjit Kaur Sahar Ahmed Idris Saban Oturk Hammam Alshazly Computer Science Department Government College BahadurgarhBahadurgarh124507India CSE Department National Institute of Technology Hamirpur177005India School of Engineering and Applied Sciences Bennett UniversityGreater Noida201310India College of Industrial Engineering King Khalid UniversityAbhaSaudi Arabia Department of Electrical and Electronics Engineering Amasya UniversityAmasyaTurkey Faculty of Computers and Information South Valley UniversityQena83523Egypt

Nowadays,due to the increase in information resources,the number of parameters and complexity of feature vectors *** offermore practical solutions instead of exact solutions for the solution of this *** Emperor PenguinOptimizer(EPO)is one of the highest performing meta-heuristic algorithms of recent times that imposed the gathering behavior of emperor *** shows the superiority of its performance over a wide range of optimization problems thanks to its equal chance to each penguin and its fast convergence *** traditional EPO overcomes the optimization problems in continuous search space,many problems today shift to the binary search ***,in this study,using the power of traditional EPO,binary EPO(BEPO)is presented for the effective solution of binary-nature *** algorithm uses binary search space instead of searching solutions like conventional EPO algorithm in continuous search *** this purpose,the sigmoidal functions are preferred in determining the emperor *** addition,the boundaries of the search space remain constant by choosing binary ***’s performance is evaluated over twenty-nine benchmarking *** evaluations are made to reveal the superiority of the BEPO *** addition,the performance of the BEPO algorithm was evaluated for the binary feature selection *** experimental results reveal that the BEPO algorithm outperforms the existing binary meta-heuristic algorithms in both tasks.

关键词： Metaheuristics optimization algorithms emperor penguin optimizer intensification diversification feature selection

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Improved Hamiltonian Control Law with Load Current Sensorless of Multiphase Parallel Converter for Electric Vehicle Applications 49

Improved Hamiltonian Control Law with Load Current Sensorles...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Kamnarn, Uthen Yodwong, Burin Mungporn, Pongsiri Thounthong, Phatiphat Khomfoi, Surin Kumam, Poom Pierfederici, Serge Nahid-Mobarakeh, Babak Takorabet, Noureddine Rajamangala University of Technology Lanna Department of Electrical Engineering Chiang Mai Thailand King Mongkut's University of Technology North Bangkok Thai French Innovation Institute Bangkok Thailand King Mongkut's University of Technology North Bangkok Renewable Energy Research Centre Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Technical Education Department of Teacher Training in Electrical Engineering Bangkok Thailand School of Engineering King Mongkut's Institue of Technology Ladkrabang Department of Electrical Engineering Bangkok Thailand Faculty of Science Department of Mathematics Bangkok Thailand University of Lorraine Laboratoire d'Energetique et de Mecanique Theorique et Appliquee Umr 7563 Cnrs Vandœuvre-lès-Nancy54500 France McMaster University Electrical and Computer Engineering HamiltonONL8S 4L8 Canada Université de Lorraine ENSEM-GREEN Nancy54052 France

ISBN: (纸本)9798350331820

This article presents an improved Hamiltonian control law (HCL) with load current sensorless ability for multiphase parallel converters in electric vehicle applications. On one hand, the proposed control approach has a significant advantage in handling constant power load (CPL) that occurs in the situation of the vehicle, which is a dangerous situation that can cause oscillations and uncertainty. On the other hand, the load current observer is applied with HCL to improve the efficiency and reliability of the converter system. In addition, by eliminating the need for current sensors, the cost and size of the converter system are reduced, while maintaining accurate current control. Moreover, the difference flatness approach has been applied to generate the current reference resulting in regulating the DC bus voltage. Finally, the multiphase two-quadrant converter driving by the proposed control law has been evaluated through experimental tests. The obtained experimental results demonstrate the excellent performance of the multiphase two-quadrant converter with CPL thereby confirming the efficacy of the proposed approach. © 2023 IEEE.

关键词： Electric vehicles

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BeHAutH: A KNN-Based Classification Scheme for Behavior-Based Authentication in Web 3.0

BeHAutH: A KNN-Based Classification Scheme for Behavior-Base...

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2022 IEEE International Conference on Communications, Computing, Cybersecurity and Informatics, CCCI 2022

作者： Bhattacharya, Pronaya Trivedi, Chandan Obaidat, Mohammad S. Patel, Kartik Tanwar, Sudeep Hsiao, Kuei-Fang Department of Computer Science and Engineering Institute of Technology Nirma University Gujarat Ahmedabad India Department of Computer Science Cybersecurity Center University of Texas Permian Basin OdessaTX70762 United States King Abdullah II School of IT University of Jordan Jordan University of Science and Technology Beijing China Computer Science Department University of Texas-Permian Basin 4901 E. University Blvd. OdessaTX79762 United States

ISBN: (数字)9781665486170

ISBN: (纸本)9781665486170

Web 3.0 would allow users and processes to communicate and interpret data semantically. It is expected to employ web user (WU) behaviour data, which is sampled and collected at different time instants for verification. Recent approaches have suggested behaviour-based authentication (BBA), but most schemes suffer from a high rate of false positives. Motivated from the gap, the paper presents a scheme named BeHAutH, that constructs a two-factor authentication (2FA) scheme for WU, based on real-time keystroke dynamics. We employ the K-nearest neighbour classification (KNN) algorithm and compute the similarity across two vectors in K dimensions. The similarity is computed in terms of both Euclidean and Manhattan distance metrics. The scheme achieves an accuracy of 87% over 146 testing samples, and a recall value of 0.95, which address the false negative issues. © 2022 IEEE.

关键词： Machine learning

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Coordinating Storage and Demand Response to Increase Photovoltaic Hosting Capacity in Distribution Grid

Coordinating Storage and Demand Response to Increase Photovo...

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Innovative Sustainable Technologies for Energy, Mechatronics, and Smart Systems (ISTEMS), International Conference on

作者： Tanuj Rawat Ankit Garg Vipin Chandra Pandey Jyotsna Singh Sachin Sharma Shobhit Garg School of Engineering Newcastle University Newcastle Upon Tyne United Kingdom Department of Electrical Engineering Malaviya National Institute of Technology Jaipur India Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Department of Electrical Engineering School of Automation Tonk India Department of Electrical Engineering Graphic Era University Dehradun India Department of Management Studies Graphic Era University Dehradun India

ISBN: (数字)9798350384246

ISBN: (纸本)9798350384253

This work analyses capability of energy storage system (ESS) and demand response (DR) to maximize the hosting capacity (HC) of solar photovoltaic (PV) in distribution network. The optimization model aims to maximize total capacity of PV that can be installed in the distribution system. Three different cases are framed and impact of proposed approach on technical parameters of distribution system such as energy losses, voltage phenomenon and grid peak demand are discussed. In addition, a sensitivity analysis to investigate impact of changing DR participation rate, energy, and power rating of ESS on HC is presented. The effectiveness of ESS and DR in improving HC is simulated on IEEE-33 bus system. Results indicate that jointly coordinating ESS and DR gives higher HC as compared to scheduling ESS or DR alone.

关键词： Photovoltaic systems Renewable energy sources Energy loss Uncertainty Mechatronics Sensitivity analysis Simulation

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A new way of analyzing malaria data: A non-stationary geostatistical modeling approach

Research Square

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Research Square 2023年

作者： Ejigu, Bedilu Alamirie Moraga, Paula Department of Statistics CNCS Addis Ababa University Ethiopia Department of Statistics Addis Ababa University Ethiopia Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

Geostatistical models are widely used to analyze malaria data, and obtain spatial predictions at un-sampled locations based on the First Law of Geography (close things in space are more similar than distant things). When environmental covariates affect not only the mean of the underlying process under investigation but also its covariance structure, stationary models for spatial prediction are questionable. In this paper, we illustrate how to incorporate spatially referenced environmental risk-factors into the covariance function to model non-stationary patterns of malaria risk. Specifically, we demonstrate the suggested modelling framework with a case study of malaria prevalence in Mozambique where we compare a non-stationary model with dependence structure governed by precipitation to the standard stationary model. Results reveal that non-stationary geostatistical modeling approaches are more useful to model the non-stationary patterns of malaria. Further the predication malaria risk map based on the non-stationary modeling approach show that in many part of the country (especially in the eastern part) malaria prevalence is above 30%. The demonstrated non-stationary modeling approach will play a great role for malaria elimination. © 2023, CC BY.

关键词： Diseases

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Internet-of-Explainable-Digital-Twins: A Case Study of Versatile Corn Production Ecosystem

Internet-of-Explainable-Digital-Twins: A Case Study of Versa...

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2022 IEEE International Conference on Communications, Computing, Cybersecurity and Informatics, CCCI 2022

作者： Bhattacharya, Pronaya Obaidat, Mohammad S. Sanghavi, Sakshi Sakariya, Vatsal Tanwar, Sudeep Hsiao, Kuei-Fang Department of Computer Science and Engineering Institute of Technology Nirma University Gujarat Ahmedabad India Department of Computer Science Cybersecurity Center University of Texas-Permian Basin OdessaTX70762 United States King Abdullah II School of IT University of Jordan Jordan University of Science and Technology Beijing China Computer Science Department University of Texas-Permian Basin 4901 E. University Blvd. OdessaTX79762 United States

ISBN: (数字)9781665486170

ISBN: (纸本)9781665486170

In this paper, the authors present a new architectural concept named as Internet-of-Explainable-Digital-Twins (IoxDT), that holistically integrates explainable AI (xAI) and digital twin (DT) in Industry 5.0 production processes. The authors present the architecture over a versatile production system (VPS) corn production plant, where processes are sensor-driven and monitored to minimize bias. The collaboration of DT and xAI leverages the robustness, predictability, and maintainability of VPS processes. In the proposed architecture, the VPS sensor-controlled inputs are sent to the DT controller. The controller is supplied with virtual inputs, which are replicas of real inputs, and the controller behaviour is monitored. The outputs are connected to an xAI module designed with Shapley additive explanations (SHAP) model, which generates the output predictability and dependence on inputs. The unsafe outputs are rejected. A case-study evaluation is carried out in terms of the mean and standard deviation of DT module creation, and SHAP predictability outputs, which shows an accuracy of 96% of unsafe inputs. The proposed results indicate the viability of the framework in real Industry 5.0 VPS setups. © 2022 IEEE.

关键词： Ecosystems

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SMoA: Improving Multi-agent Large Language Models with Sparse Mixture-of-Agents

arXiv

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arXiv 2024年

作者： Li, Dawei Tan, Zhen Qian, Peijia Li, Yifan Chaudhary, Kumar Satvik Hu, Lijie Shen, Jiayi School of Computing and Augmented Intelligence Arizona State University United States Computer Science and Engineering Michigan State University United States King Abdullah University of Science and Technology Saudi Arabia University of Texas Austin United States

While multi-agent systems have been shown to significantly enhance the performance of Large Language Models (LLMs) across various tasks and applications, the dense interaction between scaling agents potentially hampers their efficiency and diversity. To address these challenges, we draw inspiration from the sparse mixture-of-agents (SMoE) and propose a sparse mixture-of-agents (SMoA) framework to improve the efficiency and diversity of multi-agent LLMs. Unlike completely connected structures, SMoA introduces novel Response Selection and Early Stopping mechanisms to sparsify information flows among individual LLM agents, striking a balance between performance and efficiency. Additionally, inspired by the expert diversity principle in SMoE frameworks for workload balance between experts, we assign distinct role descriptions to each LLM agent, fostering diverse and divergent thinking. Extensive experiments on reasoning, alignment, and fairness benchmarks demonstrate that SMoA achieves performance comparable to traditional mixture-of-agents approaches but with significantly lower computational costs. Further analysis reveals that SMoA is more stable, has a greater capacity to scale, and offers considerable potential through hyper-parameter optimization. Code and data will be available at: https://***/David-Li0406/SMoA. © 2024, CC BY.

关键词： Benchmarking

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Optimizing Propagation Predictions for Last-mile Connectivity in a CubeSat Perspective

Optimizing Propagation Predictions for Last-mile Connectivit...

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Computing and Information technology (ICCIT-1441), 2020 International Conference on

作者： Faris A. Almalki Haitham Aljahdalia Computer Engineering Department College of Computers and Information Technology Taif University Taif Saudi Arabia Core Labs King Abdullah University of Science and Technology Thuwal Saudi Arabia

CubeSats is seen as an innovative approach to provide many wireless communications services in a wide footprint coverage manner. However, this could lead to electromagnetic spectrum congestion, which requires larger bandwidths. Thus, optimization approaches and considering of high frequency bands are needed. This work aims to develop an optimized propagation model to enhance the last-mile connectivity of a CubeSat system using an enhanced version of the log-normal shadowing propagation model by considering elevation angle in its formulation. Then, a linear iterative feedback scheme is applied to produce an enhanced approximate solution of the propagation problem. Link budget parameters, Mean Absolute Percentage Error (MAPE), and Root Mean Squared Error (RMSE) have been used as performance indictors to validate the proposed scheme. Results show that the optimized model outperforms the non-optimized one from link budget and the two regression metric validation perspectives.

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Acoustic Beam Splitting and Cloaking Based on a Compressibility-Near-Zero Medium

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Physical Review Applied 2022年第5期17卷 054025-054025页

作者： Changqing Xu Sibo Huang Zhiwei Guo Haitao Jiang Yong Li Ying Wu Hong Chen Division of Computer Electrical and Mathematical Science and Engineering King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia Key Laboratory of Advanced Micro-Structured Materials MOE School of Physics Science and Engineering Tongji University Shanghai 200092 China

We report an artificial acoustic compressibility-near-zero medium made of a phononic crystal composed of epoxy blocks arranged in a square lattice. Its anisotropic effective density leads to a linear cross in its isofrequency contour in the vicinity of the Brillouin zone center, as its effective compressibility approaches zero. When a Gaussian beam is normally incident on the phononic crystal, a splitting effect is achieved at the frequency of the crossing point. Based on such a beam-splitting effect, an acoustic cloaking of an irregular-shaped object embedded in the phononic crystal is demonstrated both theoretically and experimentally. Such an anisotropic zero-index material offers a potential method to control acoustic waves.

关键词： Acoustic metamaterials Acoustics Cloaking Phononic crystals

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