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Articles 481 - 510 of 37411

Full-Text Articles in Physical Sciences and Mathematics

Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment, Hui Wang, Le Peng Feb 2024

Improved Multi-Objective Swarm Algorithm To Optimize Wash-Out Motion And Its Simulation Experiment, Hui Wang, Le Peng

Journal of System Simulation

Abstract: Addressing the issues such as signal loss, distraction, and bad wash-out effect caused by improper parameter selection in classic wash-out algorithms, an improved multi-objective artificial bee colony algorithm is proposed to optimize the filter parameters of the classical wash-out algorithm to improve the effect. For the problems in the initialization and local optimization of traditional swarm algorithm, Circle mapping and Pareto local optimization algorithm are introduced. The human perception error model, acceleration difference model, and displacement model are established, and the model function is used as the objective function, the parameters of the classical wash-out algorithm is optimized by …

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Bus Traffic Strategy Based On Immune Theory In Network Environment, Cao Li, Rui Zheng, Xiaolu Ma, Ziqiong Ding, Junyi Zhong, Sheng Zhang, Jingjing Qi Feb 2024

Bus Traffic Strategy Based On Immune Theory In Network Environment, Cao Li, Rui Zheng, Xiaolu Ma, Ziqiong Ding, Junyi Zhong, Sheng Zhang, Jingjing Qi

Journal of System Simulation

Abstract: In V2X network environment, the bus system can obtain dynamic global information and the bus traffic strategy is carried out based on the road scene between adjacent bus stops. The mathematical model of bus rapid traffic is constructed with the difference of green time ratio as the main parameter. A hybrid genetic operator is proposed on the basis of the combination of genetic algorithm and immune theory, the design of affinity, the selection of excellent antibodies. A bus traffic strategy based on immune theory is proposed on the basis of the improvement of adaptive crossover and mutation probability. The …

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Fault Detection Based On Sliding Window And Multiblock Convolutional Autoencoders, Jianpeng Mou, Weili Xiong Feb 2024

Fault Detection Based On Sliding Window And Multiblock Convolutional Autoencoders, Jianpeng Mou, Weili Xiong

Journal of System Simulation

Abstract: In order to further improve the fault detection performance and fully mine the timing and hidden feature information, a fault detection method based on convolutional auto encoder is proposed. On the basis of modeling the original information set, the modeling of cumulative information and rate of change information is added to enhance the mining of implicit information; The three reconstructed information sets are sampled by sliding windows, and time series feature extraction and modeling are performed based on convolutional auto encoders. Bayesian fusion of the decision results of the convolutional auto encoder is performed to obtain the statistics, and …

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Short-Term Bus Passenger Flow Prediction Based On Convolutional Long-Short-Term Memory Network, Jing Chen, Zhaochong Zhang, Linkai Wang, Mai An, Wei Wang Feb 2024

Short-Term Bus Passenger Flow Prediction Based On Convolutional Long-Short-Term Memory Network, Jing Chen, Zhaochong Zhang, Linkai Wang, Mai An, Wei Wang

Journal of System Simulation

Abstract: To address the problem that the traditional short-time passenger flow prediction method does not consider the temporal characteristics similarity between the inter-temporal passenger flows, a shorttime passenger flow prediction model k-CNN-LSTM is proposed by combining the improved k-means clustering algorithm with the CNN and the LSTM. The k-means is used to cluster the intertemporal timeseries data, the k-value is determined by using the gap-statistic, and a traffic flow matrix model is constructed. A CNN-LSTM network is used to process the short-time passenger flows with spatial and temporal characteristics. The model is tested and parameter tuned by the real dataset. …

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Design And Application Of Hardware-In-The-Loop Simulation System For Infrared Imaging Guide Missile Test And Evaluation, Jianbin Dou, Xiaobing Wang, Hongjian Yang, Yulong Gao Feb 2024

Design And Application Of Hardware-In-The-Loop Simulation System For Infrared Imaging Guide Missile Test And Evaluation, Jianbin Dou, Xiaobing Wang, Hongjian Yang, Yulong Gao

Journal of System Simulation

Abstract: The characteristics of the army's conventional infrared imaging guide missile hardware-in-theloop simulation system used for test and evaluation is analyzed, and a system that can meet the test and evaluation requirement of infrared imaging guide missile is designed. The key technologies such as universal system design, rapid iterative development design of heterogeneous communication data, high radiation infrared interference dual channel coupling simulation, high-precision timing and synchronization, generation of complex battlefield environment are solved. The application of the system is verified on the typical anti-tank missile and helicopter borne missile tests. The system can be used for infrared imaging guide …

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Identification Of Strong Tremor Causes For Appropriate Rock Burst Prevention In A Hard Coal Mine, Rafał Pakosz, Łukasz Wojtecki, Maciej J. Mendecki, Agnieszka Krzyżanowska Feb 2024

Identification Of Strong Tremor Causes For Appropriate Rock Burst Prevention In A Hard Coal Mine, Rafał Pakosz, Łukasz Wojtecki, Maciej J. Mendecki, Agnieszka Krzyżanowska

Journal of Sustainable Mining

The exploitation carried out in the Bielszowice part of the Ruda Hard Coal Mine is mainly accompanied by seismic and rock burst hazards. The occurrence of high-energy tremors may be associated with many factors, e.g., fracturing of thick layers of high-strength rocks or destruction processes of a stressed and/or thick coal seam. These factors are often combined when excavating a single longwall panel. Determining the causes of strong tremors is of fundamental importance for mining and rock burst prevention. The extraction of the 004z longwall panel in the top layer of coal seam No. 504 was designed in complex geological …

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Pinpointing Dream Settings Onto Place Cookies Feb 2024

Pinpointing Dream Settings Onto Place Cookies

The International Journal of Ecopsychology (IJE)

Dream reports are short pieces of text, where a dreamer summarizes the remembered experience of nightly dreams. Dream cartography addresses especially the spatial information contained in dream reports. In this context, the current formalization of space in GIScience such as points, lines, polygons, or labels, including place names or addresses, is not sufficient for mapping dream settings. In the best case, dream reports mention place names or streets. However, usually, the perception of space in dreams is designated in terms of whether this is familiar or not, inside or outside, safe or threatening. Moreover, basic comparisons between dream settings are …

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A Quick And Cost-Effective Method For Monitoring Deforestation Of Oil Sands Mining Activities Using Synthetic Aperture Radar And Multispectral Real-Time Satellite Data From Sentinel-1 And Sentinel-2., J Garcia Del Real, M. Alcaraz Feb 2024

A Quick And Cost-Effective Method For Monitoring Deforestation Of Oil Sands Mining Activities Using Synthetic Aperture Radar And Multispectral Real-Time Satellite Data From Sentinel-1 And Sentinel-2., J Garcia Del Real, M. Alcaraz

Journal of Sustainable Mining

Alberta’s oil sands mining operations rank among the largest human-made structures globally. Monitoring through the use of Synthetic Aperture Radar (SAR) and Multispectral satellite imaging is an indispensable strategy in attaining sustainable development and mitigating deforestation in the third-largest verified oil reserves worldwide. This paper introduces a novel approach for cost-effective and reliable monitoring of deforestation caused by oil sands mining, avoiding cumbersome methods. It focuses on observing forest/non-forest areas affected by Suncor Energy Company’s mining assets in Alberta, using a combination of SAR and Multispectral satellite remote sensing. Radar images from Sentinel-1B and Multispectral images from Sentinel-2A were analyzed …

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Machine Learning Model And Molecular Docking For Screening Medicinal Plants As Hiv-1 Reverse Transcriptase Inhibitors, Muthia Rahayu Iresha, Firdayani Firdayani, Agam Wira Sani, Nihayatul Karimah, Shelvi Listiana, Irfansyah Yudhi Tanasa, Arief Sartono, Ayu Masyita Feb 2024

Machine Learning Model And Molecular Docking For Screening Medicinal Plants As Hiv-1 Reverse Transcriptase Inhibitors, Muthia Rahayu Iresha, Firdayani Firdayani, Agam Wira Sani, Nihayatul Karimah, Shelvi Listiana, Irfansyah Yudhi Tanasa, Arief Sartono, Ayu Masyita

Karbala International Journal of Modern Science

The human immunodeficiency virus type 1 reverse transcriptase (HIV-1 RT) plays a significant role in viral replication and is one of the targets for anti-HIV. However, a mutation in viral strains rapidly developed the resistance of the com-pounds to the protein, reducing the effectiveness of the inhibitors. This work seeks to utilize machine learning-based quantitative structure-activity relationship (QSAR) analysis in combination with molecular docking simulations to forecast the presence of active compounds derived from medicinal plants. Specifically, the objective is to identify com-pounds that have the potential to operate as inhibitors of HIV-1 reverse transcriptase (RT), encompassing both wild-type and …

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An Icosahedron For Two: A Many-Sided Look At Making A Duet, Colleen T. Wahl Feb 2024

An Icosahedron For Two: A Many-Sided Look At Making A Duet, Colleen T. Wahl

LASER Journal

The space around our bodies is not empty or neutral. In fact, the space around our bodies is loaded with meaning and important. When we move through it, whether it be in our daily lives or a choreographer making specific choices in order to convey a message, we activate new understandings in our lives. As a dancer and choreographer, I created a duet from improvisational climbs on an icosahedron. This article discusses choreographing from the form icosahedron and connects Laban's theories of space harmony with the activation of meaning in my life.

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Two Non–*–Isomorphic *–Lie Algebra Structures On Sl(2,R) And Their Physical Origins, Luigi Accardi, Irina Ya. ArefʹEva, Yungang Lu, Igorʹ VasilʹEvich Volovich Feb 2024

Two Non–*–Isomorphic *–Lie Algebra Structures On Sl(2,R) And Their Physical Origins, Luigi Accardi, Irina Ya. ArefʹEva, Yungang Lu, Igorʹ VasilʹEvich Volovich

Journal of Stochastic Analysis

No abstract provided.

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History Of Clover Leaf Syndrome, Isabella Perez Feb 2024

History Of Clover Leaf Syndrome, Isabella Perez

Mako: NSU Undergraduate Student Journal

The purpose of this paper is to summarize the history of clover leaf syndrome and describe the newest advancements made to treat it. Clover leaf syndrome is more formally referred to as Kleeblattschadel syndrome. Information was gathered from several scholarly, peer-reviewed articles, and was condensed down into the key takeaways. This syndrome impacts the formation of the skull due to premature fusion of its sutures, creating a tri-lobar skull that resembles a clover leaf. This premature fusion is referred to as a type of craniosynostosis and has been linked to causing several other health complications ranging in severity. This is …

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Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu Feb 2024

Motion Magnification-Inspired Feature Manipulation For Deepfake Detection, Aydamir Mirzayev, Hamdi Di̇bekli̇oğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Recent advances in deep learning, increased availability of large-scale datasets, and improvement of accelerated graphics processing units facilitated creation of an unprecedented amount of synthetically generated media content with impressive visual quality. Although such technology is used predominantly for entertainment, there is widespread practice of using deepfake technology for malevolent ends. This potential for malicious use necessitates the creation of detection methods capable of reliably distinguishing manipulated video content. In this work we aim to create a learning-based detection method for synthetically generated videos. To this end, we attempt to detect spatiotemporal inconsistencies by leveraging a learning-based magnification-inspired feature manipulation …

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On A Generator Of Copulas Method Based On A Duplication-Parameter Technique, Christophe Chesneau Feb 2024

On A Generator Of Copulas Method Based On A Duplication-Parameter Technique, Christophe Chesneau

International Journal of Emerging Multidisciplinaries: Mathematics

A two-dimensional copula is a function that accurately depicts the pattern of dependence between two quantitative variables. The demand for new two-dimensional copulas is as strong as ever, driven by the emergence of contemporary data from various sources. This paper makes a contribution to this area by presenting a novel modification of the well-known convex sums of copulas method. This modification is based on a thorough duplication-parameter technique: we transform one parameter into two, and we apply the classical convex sums method to only one of these parameters in the unit distribution setting. The main goals are (i) to solve …

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Privacy Principles And Harms: Balancing Protection And Innovation, Samuel Aiello Feb 2024

Privacy Principles And Harms: Balancing Protection And Innovation, Samuel Aiello

Journal of Cybersecurity Education, Research and Practice

In today's digitally connected world, privacy has transformed from a fundamental human right into a multifaceted challenge. As technology enables the seamless exchange of information, the need to protect personal data has grown exponentially. Privacy has emerged as a critical concern in the digital age, as technological advancements continue to reshape how personal information is collected, stored, and utilized. This paper delves into the fundamental principles of privacy and explores the potential harm that can arise from the mishandling of personal data. It emphasizes the delicate balance between safeguarding individuals' privacy rights and fostering innovation in a data-driven society. By …

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Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan Feb 2024

Error Performance Enhancement And Complexity Reduction In Ofdm Systems Via Coordinate Interleaving Under Practical Impairments, Mustafa Anıl Reşat, Armed Tusha, Seda Doğan Tusha, Serdar Özyurt, Hüseyin Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

In this work, subcarrier coordinate interleaving (CI) is implemented to orthogonal frequency division multiplexing (OFDM) systems with the aim of both enhancing the error performance and reducing the implementation complexity. To this end, the modulated symbols are independently chosen from a modified M-ary amplitude-shift keying signal constellation under a specific CI strategy. In addition to doubling the diversity level of the original OFDM scheme, the adopted CI approach also drastically reduces the inverse fast Fourier transform (IFFT) size at the transmit side by guaranteeing the first half of the input vector to be identical with the second half at the …

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Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy Feb 2024

Longitudinal Attacks Against Iterative Data Collection With Local Differential Privacy, Mehmet Emre Gürsoy

Turkish Journal of Electrical Engineering and Computer Sciences

Local differential privacy (LDP) has recently emerged as an accepted standard for privacy-preserving collection of users’ data from smartphones and IoT devices. In many practical scenarios, users’ data needs to be collected repeatedly across multiple iterations. In such cases, although each collection satisfies LDP individually by itself, a longitudinal collection of multiple responses from the same user degrades that user’s privacy. To demonstrate this claim, in this paper, we propose longitudinal attacks against iterative data collection with LDP. We formulate a general Bayesian adversary model, and then individually show the application of this adversary model on six popular LDP protocols: …

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A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran Feb 2024

A Novel Extended Reaction Force/Torque Observer With Impedance Control, İlkay Turaç Özçeli̇k, Abdurrahman Eray Baran

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a new extended version of the reaction force observer (RFOB) for high-precision motion control systems. The RFOB has been proven to be useful for many applications in the literature. However, because of the low-pass filter present inside of the RFOB, it has certain limitations. In this study, a new algorithm is proposed to compensate for filtering-based errors in the classical RFOB structure. The algorithm includes the differentiation of the observed force and scaling with a proper value. However, since the force has a noisy nature, differentiation also affects the signal’s stability and performance. To resolve this issue, …

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Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim Feb 2024

Differentially Private Online Bayesian Estimation With Adaptive Truncation, Sinan Yildirim

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a novel online and adaptive truncation method is proposed for differentially private Bayesian online estimation of a static parameter regarding a population. A local differential privacy setting is assumed where sensitive information from individuals is collected on an individual level and sequentially. The inferential aim is to estimate, on the fly, a static parameter regarding the population to which those individuals belong. We propose sequential Monte Carlo to perform online Bayesian estimation. When individuals provide sensitive information in response to a query, it is necessary to corrupt it with privacy-preserving noise to ensure the privacy of those …

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Board Of Directors Role In Data Privacy Governance: Making The Transition From Compliance Driven To Good Business Stewardship, David Warner, Lisa Mckee Feb 2024

Board Of Directors Role In Data Privacy Governance: Making The Transition From Compliance Driven To Good Business Stewardship, David Warner, Lisa Mckee

Journal of Cybersecurity Education, Research and Practice

Data collection, use, leveraging, and sharing as a business practice and advantage has proliferated over the past decade. Along with this proliferation of data collection is the increase in regulatory activity which continues to morph exponentially around the globe. Adding to this complexity are the increasing business disruptions, productivity and revenue losses, settlements, fines, and penalties which can amount to over $15 million, with many penalties now being ascribed to the organization’s leadership, to include the Board of Directors (BoD), the CEO and members of the senior leadership team (SLT). Thus, boards of directors can no longer ignore and in …

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Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu Feb 2024

Traffic Signal Optimization Using Multiobjective Linear Programming For Oversaturated Traffic Conditions, Mustafa Murat Coşkun, Cevat Şener, İsmail Hakkı Toroslu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we present a framework designed to optimize signals at intersections experiencing oversaturated traffic conditions, utilizing mixed-integer linear programming (MILP) techniques. The proposed MILP solutions were developed with different objective functions, namely a reduction in the total remaining queue and fair distribution of the remaining queue after each signal cycle. Our framework contains two distinct stages. The initial stage applies two distinct MILP methodologies, while the subsequent stage employs a neighborhood search method to further reduce the delays associated with the green signal timings derived from the first stage. Ultimately, to evaluate their effectiveness across various intersections, we …

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Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu Feb 2024

Artificial Intelligence-Based Evaluation Of The Factors Affecting The Sales Of An Iron And Steel Company, Mehmet Pekkaya, Zafer Uysal, Aytaç Altan, Seçkin Karasu

Turkish Journal of Electrical Engineering and Computer Sciences

It is important to predict the sales of an iron and steel company and to identify the variables that influence these sales for future planning. The aim in this study was to identify and model the key factors that influence the sales volume of an iron and steel company using artificial neural networks (ANNs). We attempted to obtain an integrated result from the performance/sales levels of 5 models, to use the ANN approach with hybrid algorithms, and also to present an exemplary application in the base metals industry, where there is a limited number of studies. This study contributes to …

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Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar Feb 2024

Fast Grid Search: A Grid Search-Inspired Algorithm For Optimizing Hyperparameters Of Support Vector Regression, Mustafa Açikkar

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents a fast hyperparameter optimization algorithm based on the benefits and shortcomings of the standard grid search (GS) algorithm for support vector regression (SVR). This presented GS-inspired algorithm, called fast grid search (FGS), was tested on benchmark datasets, and the impact of FGS on prediction accuracy was primarily compared with the GS algorithm on which it is based. To validate the efficacy of the proposed algorithm and conduct a comprehensive comparison, two additional hyperparameter optimization techniques, namely particle swarm optimization and Bayesian optimization, were also employed in the development of models on the given datasets. The evaluation of …

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Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai Feb 2024

Machine Learning Approaches In Comparative Studies For Alzheimer’S Diagnosis Using 2d Mri Slices, Zhen Zhao, Joon Huang Chuah, Chee-Onn Chow, Kaijian Xia, Yee Kai Tee, Yan Chai Hum, Khin Wee Lai

Turkish Journal of Electrical Engineering and Computer Sciences

Alzheimer’s disease (AD) is an illness that involves a gradual and irreversible degeneration of the brain. It is crucial to establish a precise diagnosis of AD early on in order to enable prompt therapies and prevent further deterioration. Researchers are currently focusing increasing attention on investigating the potential of machine learning techniques to simplify the automated diagnosis of AD using neuroimaging. The present study involved a comparison of models for the detection of AD through the utilization of 2D image slices obtained from magnetic resonance imaging brain scans. Five models, namely ResNet, ConvNeXt, CaiT, Swin Transformer, and CVT, were implemented …

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Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk Feb 2024

Fractional Delay-Dependent Load Frequency Controller Design For A Single-Area Power System With Communication Delay, Erhan Yumuk

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes a fractional delay-dependent load frequency control design approach for a single-area power system with communication delay based on gain and phase margin specifications. In this approach, the closed-loop reference transfer function relies on the delayed Bode’s transfer function. The gain and phase margin specifications are established in order to optimize the reference model based on three time-domain performance indices. Here, a category of fractional-order model is employed to describe the single-area power system incorporating communication delay. The controller parameters are determined using the fractional-order system model and optimal closed-loop reference model. Then, a delay-dependent control mechanism is …

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Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi Feb 2024

Grey Wolf Optimization Algorithm-Based Robust Neural Learning Control Of Passive Torque Simulators With Predetermined Performance, Seyyed Amirhossein Saadat, Mohammad Mehdi Fateh, Javad Keighobadi

Turkish Journal of Electrical Engineering and Computer Sciences

In flight control systems, the actuators need to tolerate aerodynamic torques and continue their operations without interruption. To this end, using the simulators to test the actuators in conditions close to the real flight is efficient. On the other hand, achieving the guaranteed performance encounters some challenges and practical limitations such as unknown dynamics, external disturbances, and state constraints in reality. Thus, this article attempts to present a robust adaptive neural network learning controller equipped with a disturbance observer for passive torque simulators (PTS) with load torque constraints. The radial basis function networks (RBFNs) are employed to identify the unknown …

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Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk Feb 2024

Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …

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Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu Feb 2024

Automated Identification Of Vehicles In Very High-Resolution Uav Orthomosaics Using Yolov7 Deep Learning Model, Esra Yildirim, Umut Güneş Seferci̇k, Taşkın Kavzoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

The utilization of remote sensing products for vehicle detection through deep learning has gained immense popularity, especially due to the advancement of unmanned aerial vehicles (UAVs). UAVs offer millimeter-level spatial resolution at low flight altitudes, which surpasses traditional airborne platforms. Detecting vehicles from very high-resolution UAV data is crucial in numerous applications, including parking lot and highway management, traffic monitoring, search and rescue missions, and military operations. Obtaining UAV data at desired periods allows the detection and tracking of target objects even several times during a day. Despite challenges such as diverse vehicle characteristics, traffic congestion, and hardware limitations, the …

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The Usage Of Band Ratios To Predict Lake Water Quality Parameters Using Sentinel-2 L1c Imagery, Austin Spoor, Ho-Seop Cha Feb 2024

The Usage Of Band Ratios To Predict Lake Water Quality Parameters Using Sentinel-2 L1c Imagery, Austin Spoor, Ho-Seop Cha

International Journal of Geospatial and Environmental Research

Band ratios using remote imagery can be useful for monitoring large bodies of water when high quality imagery is available. Sentinel-2 satellite imagery provides frequent, high-resolution coverage of the globe. This study set out to test the usefulness of existing band ratios for estimating chlorophyll a (CHL-a), dissolved organic carbon (DOC), and turbidity with Sentinel-2 imagery. USGS in-situ data was matched to Sentinel-2 imagery of Beaver Lake, Arkansas taken August 2015 to July 2019 and the dark spectrum fitting (DSF) atmospheric correction method in ACOLITE was applied to generate surface reflectance values. CHL-a was estimated using two …

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Multi-Agent System For Portfolio Profit Optimization For Future Stock Trading, Usha Devi, Mohan R Feb 2024

Multi-Agent System For Portfolio Profit Optimization For Future Stock Trading, Usha Devi, Mohan R

Karbala International Journal of Modern Science

Stock trading highly contributes to the economic growth of the country. The stock trading objective is to earn profits with buy/sell/hold decisions on the set of stocks in the portfolio. The portfolio optimization problem is finding the decision sequence that leads to higher profit and lower risk. Portfolio optimization is challenging due to complex price history patterns and an uncertain environment. Incorrect decisions in stock trading lead to massive losses. The proposed Multi-Agent System for Portfolio Profit Optimization (MASPPO) aims to optimize trading profit and reduce risk with accurate predictions. The proposed model integrates the Fuzzy c-means with the Deep …

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