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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Sadullaeva, Shakhlo Azimbaevna Anarova, Shahzoda Amanbayevna Khaydarov, Abdugaffor Fayzullayeva, Zarnigor Nazirova, Dilorom Mirkhodzhaeva, Nazhiba departament Intellegent systems Joint Belarusian-Uzbek Intersectoral Institute of Applied Technical Qualifications Tashkent Uzbekistan Department of Convergence of Digital Technologies Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis National University of Uzbekistan Tashkent Uzbekistan Department of Informatics Computer Engineering Faculty Tashkent University of Information Technologies Tashkent Uzbekistan Department of Applied Mathematics and Computer Analysis NUUz Tashkent Uzbekistan

ISBN: (纸本)9798400716928

Currently, studies of double nonlinear equations and systems of double nonlinear equations representing many processes found in nature are considered relevant and necessary. These equations and systems, as a rule, are nonlinear, degenerate, and have properties that are absent in linear theory and therefore make them quite difficult for both analytical and numerical analysis of the solution. For this reason, great attention is paid to the research of nonlinear mathematical models, the construction of efficient numerical solution schemes and algorithms, and the creation of software using the capabilities of computer technologies. In this article, the mathematical model of the diffusion process in a two-component nonlinear medium under the influence of time-dependent convective transfer and damping is studied. The calculation scheme, algorithm, and software for nonlinear problems were developed. Based on a study of the qualitative properties of a nonlinear mathematical model of a reaction-diffusion system, computer modeling of reaction-diffusion processes was carried out. The developed computational schemes, algorithms, and software packages for solving systems of parabolic equations with double nonlinearity provide high productivity in studying the theory and processes of numerical solutions of such problems. © 2024 ACM.

关键词： Nonlinear equations

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Liver Ailment Prediction Using Random Forest Model

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computers, Materials & Continua 2023年第1期74卷 1049-1067页

作者： Fazal Muhammad Bilal Khan Rashid Naseem Abdullah A Asiri Hassan A Alshamrani Khalaf A Alshamrani Samar M Alqhtani Muhammad Irfan Khlood M Mehdar Hanan Talal Halawani Department of Electrical Engineering University of Engineering and TechnologyMardan23200Pakistan City University of Science and Information Technology PeshawarPakistan Department of IT and Computer Science Pak-Austria Fachhochschule Institute of Applied Sciences and TechnologyHaripurPakistan Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajranSaudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Electrical Engineering Department College of EngineeringNajran University Saudi ArabiaNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia Computer Science Department College of Computer Science and Information SystemsNajran UniversityNajranSaudi Arabia

Today,liver disease,or any deterioration in one’s ability to survive,is extremely common all around the *** research has indicated that liver disease is more frequent in younger people than in older *** the liver’s capability begins to deteriorate,life can be shortened to one or two days,and early prediction of such diseases is *** several machine learning(ML)approaches,researchers analyzed a variety of models for predicting liver disorders in their early *** a result,this research looks at using the Random Forest(RF)classifier to diagnose the liver disease early *** dataset was picked from the University of California,Irvine ***’s accomplishments are contrasted to those of Multi-Layer Perceptron(MLP),Average One Dependency Estimator(A1DE),Support Vector Machine(SVM),Credal Decision Tree(CDT),Composite Hypercube on Iterated Random Projection(CHIRP),K-nearest neighbor(KNN),Naïve Bayes(NB),J48-Decision Tree(J48),and Forest by Penalizing Attributes(Forest-PA).Some of the assessment measures used to evaluate each classifier include Root Relative Squared Error(RRSE),Root Mean Squared Error(RMSE),accuracy,recall,precision,specificity,Matthew’s Correlation Coefficient(MCC),F-measure,and *** has an RRSE performance of 87.6766 and an RMSE performance of 0.4328,however,its percentage accuracy is *** widely acknowledged result of this work can be used as a starting point for subsequent *** a result,every claim that a new model,framework,or method enhances forecastingmay be benchmarked and demonstrated.

关键词： Liver ailment random forest machine learning

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Integrated electro-optic isolator on thin-film lithium niobate (Jun, 10.1038/s41566-023-01227-8, 2023)

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NATURE PHOTONICS 2023年第8期17卷 732-732页

作者： Yu, Mengjie Cheng, Rebecca Reimer, Christian He, Lingyan Luke, Kevin Puma, Eric Shao, Linbo Shams-Ansari, Amirhassan Ren, Xinyi Grant, Hannah R. R. Johansson, Leif Zhang, Mian Loncar, Marko John A. Paulson School of Engineering and Applied Sciences Harvard University Cambridge MA USA Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles CA USA HyperLight Cambridge MA USA Draper Scholar The Charles Stark Draper Laboratory Cambridge MA USA Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA Freedom Photonics Goleta CA USA

Optical isolators are indispensable components of almost any optical system and are used to protect a laser from unwanted reflections for phase-stable coherent operation. The emergence of chip-scale optical systems, powered by semiconductor lasers that are integrated on the same chip, has generated a demand for a fully integrated optical isolator. Conventional approaches, which rely on the use of magneto-optic materials to break Lorentz reciprocity, present substantial challenges in terms of material integration. Although alternative magnetic-free approaches have been explored, an integrated isolator with a low insertion loss, high isolation ratio, broad bandwidth and low power consumption on a monolithic material platform is yet to be achieved. Here we realize a non-reciprocal travelling-wave-based electro-optic isolator on thin-film lithium niobate. The isolator enables a maximum optical isolation of 48.0 dB with an on-chip insertion loss of 0.5 dB and uses a single-frequency microwave drive power of 21 dBm. The isolation ratio remains larger than 37 dB across a tunable optical wavelength range from 1,510 to 1,630 nm. We realize a hybrid distributed feedback laser–lithium niobate isolator module that successfully protects the single-mode operation and linewidth of the laser from reflection. Our result represents an important step towards a practical high-performance optical isolator on chip.

关键词： Integrated optics Nanophotonics and plasmonics Nonlinear optics

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Prescribing Decision Conservativeness in Two-Stage Power Markets: A Distributionally Robust End-to-End Approach 59

Prescribing Decision Conservativeness in Two-Stage Power Mar...

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59th Annual Conference on Information Sciences and Systems, CISS 2025

作者： Liang, Zhirui Li, Qi Liu, Anqi Dvorkin, Yury Johns Hopkins University Department of Applied Mathematics and Statistics BaltimoreMD United States Johns Hopkins University Department of Computer Science BaltimoreMD United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD United States Johns Hopkins University Department of Civil and System Engineering BaltimoreMD United States

ISBN: (纸本)9798331513269

This paper presents an end-to-end framework for calibrating wind power forecast models to minimize operational costs in two-stage power markets, where the first stage involves a distributionally robust optimal power flow (DR-OPF) model. Unlike traditional methods that adjust forecast parameters and uncertainty quantification (UQ) separately, this framework jointly optimizes both the forecast model parameters and the decision conservativeness, which determines the size of the ambiguity set in the DR-OPF model. The framework aligns UQ with actual uncertainty realizations by directly optimizing downstream operational costs, a process referred to as cost-oriented calibration. The calibration is achieved using a gradient descent approach. To enable efficient differentiation, the DR-OPF problem is reformulated into a convex form, and the Envelope Theorem is leveraged to simplify gradient derivation in the two-stage setting. Additionally, the framework supports distributed implementation, effectively reducing computational overhead and enhancing efficiency. By proactively calibrating forecast parameters and prescribing optimal decision conservativeness, the framework significantly enhances cost efficiency and reliability in power system operations. Numerical experiments on an IEEE 5-bus system demonstrate the effectiveness and efficiency of the proposed approach. © 2025 IEEE.

关键词： Wind forecasting

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A System for Monitoring Hydroponic Plants in Greenhouse Using WSN, IoT and RnE 7th

A System for Monitoring Hydroponic Plants in Greenhouse Usin...

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7th International Conference on Artificial Intelligence in Renewable Energetic Systems, IC-AIRES 2023

作者： Touhami, Achouak Bourouis, Amina Touhami, Nawal Touhami, Sana Benahmed, Tariq Benahmed, Khelifa Department of Mathematics and Computer Science Ali Kafi University Center Tindouf Algeria Department of Mathematics and Computer Science Tahri Mohammed University Bechar Algeria Department of Electrical Engineering Ahmed Draia University Adrar Algeria Department of Mathematics and Computer Science Tamaghasset University Tamaghasset Algeria

ISBN: (纸本)9783031606281

Hydroponic cultivation offers a promising solution to address environmental and food-related challenges by minimizing the use of fertilizers and water. Our research presents a greenhouse-based design for monitoring hydroponic plants, using wireless sensor networks (WSN), hydroponic irrigation system, Internet of Things (IoT) technologies and renewable energy system (RnE). The WSN consists of diverse sensors, including those for water level, water temperature, and pH levels. The sensors are connected to a cluster head, which is linked to a microcontroller. Through the Internet, the microcontroller transmits the collected data to the farmer. The farmer evaluates the data by comparing it to predetermined thresholds and, using a laptop or smartphone, sends commands to the associated actuator. The cloud serves as the storage system for the collected data. The system features automated control capabilities, allowing for adjustments in temperature, pH levels, and water levels. Furthermore, the proposed design can be easily customized to accommodate different hydroponic conditions and systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Hydroponics

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New Results on Interval Type-3 Fuzzy Control for Nonlinear Time-Delay Systems Using Convex Relaxation Technique

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3630-3641页

作者： Harikaran, B. Harshavarthini, S. Lee, Sangmoon Sakthivel, R. Sathiyaraj, T. School of Advanced Sciences Department of Mathematics Chennai600127 India Kyungpook National University School of Electronic and Electrical Engineering Daegu41566 Korea Republic of Bharathiar University Department of Applied Mathematics Coimbatore641046 India Institute of Actuarial Science and Data Analytics UCSI University Kuala Lumpur56000 Malaysia

In this article, the interval type-3 fuzzy-based state feedback control is proposed for the stabilization problem of interval type-3 fuzzy systems (IT3FSs) subject to time-varying delay. Specifically, to improve the model accuracy and control capabilities, we proposed a nonparallel distributed compensation-based controller approach, be precise, the system and controller adopts the distinct membership functions. Moreover, the stability analysis of IT3FSs in the state space form is studied newly in this article. Besides the primary membership function that exists for interval type-2 fuzzy systems (IT2FSs), the IT3FSs possess the secondary membership function to handle the overall uncertainty which enacts the superiority of the proposed work. Notably, the adequate stability criteria are derived in the form of linear matrix inequality (LMI) using the Lyapunov stability theorem. Additionally, the convex relaxation technique is used to strengthen the design flexibility and achieve the faster convergence rate, which converts an optimization problem with a vector variable to a convex program with a matrix variable, via a lifting technique. A noteworthy aspect is that the application of the convex relaxation technique in the context of IT3FSs is proposed for the first time in literature. Finally, the comparative results between IT2FSs and IT3FSs are shown via two illustrative examples, including the inverted-pendulum model, to underscore the efficacy and practical implementations of the developed control methodology. © 2013 IEEE.

关键词： Membership functions

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Consensus MPC-Based hierarchical control of Islanded AC Microgrid 3

Consensus MPC-Based hierarchical control of Islanded AC Micr...

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3rd International Conference on Communication, Computing and Digital Systems, C-CODE 2023

作者： Khan, Zawar Aamir, Muhammad Pak-Austria Fachhochschule: Institute of Applied Sciences and Technology Electrical & Computer Engineering Department Haripur Pakistan

ISBN: (纸本)9798350332391

In this paper, the consensus model predictive control (MPC)-based hierarchical control scheme is presented for the primary and secondary layers of an islanded AC microgrid (MG). The secondary control is designed on the tracker consensus method, in this way a distributed controller in collaboration with the finite time observer will set the referenced values of voltage magnitude and frequency by significantly speeding up the method of synchronous convergence. Furthermore, the primary control has been implemented for each DG separately and comprises Finite Control Set-Model Predictive control (FCS-MPC), and droops control. FCS-MPC regulates PCC reference voltages for each DG unit. Droop Control regulates power exchange within and among DG units. In the proposed hierarchical control approach, information sharing is accomplished by a neighbouring node creating a sparse communication network while fully eliminating the requirement for a centralized controller. The controller effectiveness have been validated against unbalanced load, transients, and load plug-and-play capabilities. The simulation result shows that MG operates effectively using FCS-MPC for parallel inverters of DG units, and the consensus algorithm based distributed secondary controller in MG effectively delivers the anticipated power, voltage, and frequency. © 2023 IEEE.

关键词： Model predictive control

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Power Control for Collaborative Sensors in Internet of Things Environments Using K-means Approach 1

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International Conference on applied Soft Computing and Communication Networks, ACN 2023

作者： Hasan, Mohammed Zaki Alabady, Salah Abdulghani Salleh, Mohd Fadzli Mohd Computer Networks Department College of Computer Science and Mathematics University of Mosul Mosul Iraq Computer Engineering Department College of Engineering University of Mosul Mosul Iraq School of Electrical and Electronic Engineering Universiti Sains Malaysia Seri Ampangan Pulau Pinang Nibong Tebal14300 Malaysia

ISBN: (数字)9789819720040

ISBN: (纸本)9789819720033

Energy efficiency in sensor networks is a critical concern, as sensors are often resource-constrained devices with limited battery power. Maximizing energy efficiency is essential to prolonging the network’s lifetime, reducing maintenance costs, and enabling long-term monitoring and data collection in various Internet of Things (IoT) applications. Collaborative beamforming involves multiple sensors that coordinate their signal transmission to be focused on a specific direction. However, sensors may have various energy budget limitations to achieve beamformed signal transmission in a specific direction of the sink. In this paper, we developed a power control approach of beamforming transmission to prolong the lifetime of sensors by organizing the collaborative sensors into clusters. The proposed algorithm is based on the K-means clustering algorithm, which groups these collaborative sensors into clusters based on their residual energy information (REI). REI is changed among collaborative sensors to communicate with each other within a cluster. Therefore, each of these collaborative sensors adjusts its transmission power level to achieve balance in making decisions and facilitate collaboration between sensors in the inner cluster. Simulation results demonstrate that the proposed algorithm requires significantly low overhead and computational complexity in terms of prolonging the lifetime of the collaborative sensor cluster as compared to alternative power control algorithm that balances the energy consumption of the entire network. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Wireless sensor networks

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GENERALIZED BAYES SURE FOR MULTIVARIATE NORMAL DISTRIBUTION UNDER BALANCED-QUADRATIC LOSS

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Journal of Mathematical Sciences (United States) 2024年第2期280卷 262-274页

作者： Karamikabir, Hamid Afshari, Mahmoud Karamikabir, Nasrin Kiaei, Seyed Faridoddin Department of Statistics Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran Department of Mathematics Hamedan Branch Islamic Azad University Hamedan Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

One of the most important subjects in statistics is the theory of estimation. In this paper, we consider the generalized Bayes shrinkage estimator of the mean vector for multivariate normal distribution with the unknown covariance matrix under balanced quadratic loss. Also, we find the minimax and admissible estimator of the mean vector based on the generalized Bayes estimator. We obtain Stein’s unbiased risk estimator (SURE) threshold with a generalized Bayes shrinkage estimator and we find the wavelet shrinkage generalized Bayes SURE. Finally, we present a simulation study to test the validity of the generalized Bayes SURE and the concrete compressive strength dataset is given to test the efficiency of this estimator in denoising. © 2024, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Balanced-quadratic loss Generalized bayes estimator Shrinkage estimaton Shrinkage wavelet SURE threshold

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Lasso-Based Fast Residual Recovery For Modulo Sampling 48

Lasso-Based Fast Residual Recovery For Modulo Sampling

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48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Shah, Shaik Basheeruddin Mulleti, Satish Eldar, Yonina C. Weizmann Institute of Science Faculty of Mathematics and Computer Science Israel Bombay Department of Electrical Engineering India

ISBN: (纸本)9781728163277

In practice, Analog-to-Digital Converter (ADC) is used to perform sampling. A practical bottleneck of ADC is its lower dynamic range, leading to loss of information. To address this issue, researchers suggested folding operation on the signal using a modulo operator before passing it as an input to ADC. Though this process preserves the signal information, an unfolding algorithm is required to get the true samples from the folded samples. Noise robustness and computational time are two key parameters of an unfolding algorithm. In this paper, we propose a fast and robust algorithm for unfolding. Specifically, we first show that the first-order difference of the residual samples (the difference between the folded and true samples) is sparse by deriving an upper bound on its sparsity, and can be recovered from its partial Fourier measurements by formulating a sparse recovery problem. We demonstrate that the proposed algorithm is robust to noise and computationally efficient compared to the existing methods. © 2023 IEEE.

关键词： Recovery

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