Franklin Open最新文献_第5页

Robust moving horizon planning for multi-vehicles area coverage in uncertain environment using mixed-integer-programming 基于混合整数规划的不确定环境下多车辆区域覆盖鲁棒移动地平线规划

Franklin Open Pub Date : 2025-03-31 DOI: 10.1016/j.fraope.2025.100249

Mohamed Ibrahim

引用次数: 0

Security control of Boolean control networks against periodic DoS attacks 布尔控制网络对周期性DoS攻击的安全控制

Franklin Open Pub Date : 2025-03-27 DOI: 10.1016/j.fraope.2025.100246

Bowen Bai , Jinhuan Wang , Linying Xiang

引用次数: 0

Exceedance probabilities using Nonparametric Predictive Inference 使用非参数预测推理的超越概率

Franklin Open Pub Date : 2025-03-27 DOI: 10.1016/j.fraope.2025.100241

Ali M.Y. Mahnashi , Frank P.A. Coolen , Tahani Coolen-Maturi

{"title":"Exceedance probabilities using Nonparametric Predictive Inference","authors":"Ali M.Y. Mahnashi , Frank P.A. Coolen , Tahani Coolen-Maturi","doi":"10.1016/j.fraope.2025.100241","DOIUrl":"10.1016/j.fraope.2025.100241","url":null,"abstract":"<div><div>Some statistical methods for extreme value analysis assume that the maximum observed value represents the endpoint of the support. However, in cases involving right-censored observations, it is often unclear whether the true value of a censored observation exceeds the largest observed value. This paper is inspired by the Supercentenarian dataset, which contains the ages at death of individuals who lived beyond 110 years, with right-censored data for those still alive at the time of data collection. This study employs Nonparametric Predictive Inference (NPI), a method that provides probability statements for a range of events of interest. NPI is a frequentist method that relies on minimal assumptions, focusing explicitly on future observations. It uses imprecise probabilities based on Hill’s assumption <span><math><msub><mrow><mi>A</mi></mrow><mrow><mrow><mo>(</mo><mi>n</mi><mo>)</mo></mrow></mrow></msub></math></span> to quantify uncertainty. In this paper, we derive the probability that the true lifetime of at least one right-censored observation – or one of the future observations – exceeds the largest observed value. Furthermore, we extend this analysis to the exceedance of multiple largest observations, provided that they exceed the largest censored observation. We also investigate the time between any two of these largest observations, deriving the lower and upper probabilities for the exceedance of this time. We then demonstrate the proposed method using the Supercentenarian dataset, where the analysis is performed separately for men and women. We show how this approach can help to assess the likelihood of future extreme observations and provide insights into the validity of assuming the largest observed value as the endpoint of support. This work highlights the strengths of NPI in handling right-censored data and its application to real-world datasets.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"11 ","pages":"Article 100241"},"PeriodicalIF":0.0,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of Groundwater level and Potential Zone Identification in Keonjhar, Odisha based on Machine Learning and GIS Techniques 基于机器学习和地理信息系统技术的奥迪沙邦 Keonjhar 地下水位预测和潜在区域识别

Franklin Open Pub Date : 2025-03-22 DOI: 10.1016/j.fraope.2025.100250

B. Ritushree , Shubhshree Panda , Abinash Sahoo , Sandeep Samantaray , Deba P Satapathy

{"title":"Prediction of Groundwater level and Potential Zone Identification in Keonjhar, Odisha based on Machine Learning and GIS Techniques","authors":"B. Ritushree , Shubhshree Panda , Abinash Sahoo , Sandeep Samantaray , Deba P Satapathy","doi":"10.1016/j.fraope.2025.100250","DOIUrl":"10.1016/j.fraope.2025.100250","url":null,"abstract":"<div><div>Population growth, change in climate, changing land use pattern, and increase in mining activities causes over exploitation of groundwater in Keonjhar district to fulfill the freshwater demand. This over extraction causes depletion in groundwater level. Therefore, the present study determines the best-fit model for groundwater level prediction in the Keonjhar district in Odisha, India, which is extremely reliant on groundwater for survival. The efficiency of machine learning models ANN, SVM, and LSTM is investigated for forecasting groundwater level (GWL) and to find the best-fit model for the prediction. The models were trained and evaluated using historical GWL data and meteorological parameters such as rainfall, humidity, temperature, and soil moisture. Through the analysis, the model LSTM was found to be superior in prediction of GWL with its ability to capture long-term dependencies and complex patterns in data. It achieves an impressive R<sup>2</sup> value of 0.97793 and an incredibly low RMSE of 0.00057, surpassing all other models in accuracy and reliability. This study provides vital insights into effective management of groundwater resources in regions facing comparable difficulties around the world. The study also aimed to identify groundwater potential regions in the Odisha district using remote sensing applications, MCDM, and GIS approaches. GW is a key source of freshwater worldwide, but little is known about its possibility, appearance, and distribution. The study considered a number of characteristics, including geology, rainfall, land use/coverage, soil type, drainage density, lineament density, and slope in Keonjhar District to determining the potential zone of groundwater.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"11 ","pages":"Article 100250"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal control and cost-effectiveness of the control strategies chlamydiosis 衣原体病的最优控制及控制策略的成本效益

Franklin Open Pub Date : 2025-03-22 DOI: 10.1016/j.fraope.2025.100236

Yustina Amon Liana

{"title":"Optimal control and cost-effectiveness of the control strategies chlamydiosis","authors":"Yustina Amon Liana","doi":"10.1016/j.fraope.2025.100236","DOIUrl":"10.1016/j.fraope.2025.100236","url":null,"abstract":"<div><div>Chlamydiosis is a prevalent sexually transmitted infection affecting both men and women. Despite some modeling studies exploring its transmission dynamics, limited knowledge exists on the optimal combination of available controls for the disease. This paper presents a mathematical model with time-dependent variables to investigate the optimal control and cost-effectiveness of a combination of environmental hygiene, public health education, and vaccination control measures. The goal was to reduce the number of infections caused by contact with the infected individuals and contaminated environment while minimizing the cost associated with implementing control efforts. The necessary conditions and the existence of an optimal control problem were examined using Pontryagin’s Maximum Principle. The numerical simulations of the optimal control problem were carried out using a forward and backward-in-time fourth-order Runge–Kutta scheme. Findings from optimal control show that the scenario that incorporates all three control interventions yields superior results out of the seven control scenarios examined in this study. Also, cost-effectiveness analyses indicated that the combination of vaccination and sanitation effectively controls the spread of the disease at affordable costs. Therefore, this strategy is recommended for implementation due to its health benefits and cost-effectiveness.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"11 ","pages":"Article 100236"},"PeriodicalIF":0.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CCC-Trans: Hue-preserving color image enhancement method based on convex combination coefficient transformation cc - trans：基于凸组合系数变换的保色调彩色图像增强方法

Franklin Open Pub Date : 2025-03-01 DOI: 10.1016/j.fraope.2025.100213

Yoshiaki Ueda , Noriaki Suetake

{"title":"CCC-Trans: Hue-preserving color image enhancement method based on convex combination coefficient transformation","authors":"Yoshiaki Ueda , Noriaki Suetake","doi":"10.1016/j.fraope.2025.100213","DOIUrl":"10.1016/j.fraope.2025.100213","url":null,"abstract":"<div><div>In general, color image enhancement is conducted in a color space represented by hue, saturation, and intensity. It is not always guaranteeing the hue preserving since the color gamut. However, the clipping process could lead to unexpected hue changes if the enhancement process is not guaranteed within a color gamut. In this paper, we propose hue-preserving color image enhancement without the gamut problem based on a transformation of convex combination coefficients. Each pixel is decomposed into a convex combination of white, black, and pure color in the proposed method. The intensity contrast and colorfulness are enhanced while ensuring hue preservation and the color gamut by transforming the coefficients of the convex combination. The novelty of the proposed method is that the coefficients of the convex combination are transformed using histograms derived from a uniform distribution in the sRGB color space. In this paper, we describe the relationship between the coefficients of the convex combination and those of the HSV color space. Experiments show that the proposed method achieves better enhancement results than conventional methods and that the degrees of intensity contrast and colorfulness enhancement can be adjusted. The code is available at <span><span>https://github.com/uedayos/CCC-Trans</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"10 ","pages":"Article 100213"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143601342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A multi active full bridge integrated renewable energy standalone EV charging station with battery storage backup 一种多主动全桥集成可再生能源独立电动汽车充电站与备用电池存储

Franklin Open Pub Date : 2025-03-01 DOI: 10.1016/j.fraope.2025.100235

Rathod Rama Krishna , G. Yesuratnam , Dr. Punnaiah Veeraboina

{"title":"A multi active full bridge integrated renewable energy standalone EV charging station with battery storage backup","authors":"Rathod Rama Krishna , G. Yesuratnam , Dr. Punnaiah Veeraboina","doi":"10.1016/j.fraope.2025.100235","DOIUrl":"10.1016/j.fraope.2025.100235","url":null,"abstract":"<div><div>A standalone EV charging station powered by renewable sources presents a complex and often unreliable system due to the instability of renewable energy. Typically, the most cost-effective and low-maintenance renewable source is solar power. Solar panels generate electricity based on solar insolation, which can be unpredictable. In this paper, we propose a standalone EV charging station that utilizes solar panels combined with a BSM system to ensure power and voltage stability. The solar panels are designed with a bifacial structure, which enhances power generation by capturing reflected solar insolation on the back of the panels. The BSM regulates the charging and discharging processes according to the available solar power and the demands of the EV charging station. The charging station is equipped with a MAFB circuit that can charge multiple EV batteries while minimizing ripple content. The primary port of the MAFB is connected to a common DC link that shares power between the BSM and the solar module. The secondary ports of the MAFB connect to the EV batteries. The system's performance characteristics are evaluated under V2 G and G2 V operating conditions. Additionally, a comparative analysis is conducted between the performance of a conventional DC-DC bidirectional converter and the MAFB. This analysis considers various factors such as ripple, disturbances, and damping factors to identify the superior circuit topology. The complete analysis and simulation results are generated using the Simulink environment in MATLAB, utilizing components from the 'Power System' Simulink library.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"10 ","pages":"Article 100235"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advancing capsicum detection in night-time greenhouse environments using deep learning models: Comparative analysis and improved zero-shot detection through fusion with a single-shot detector 利用深度学习模型推进夜间温室环境中的辣椒检测：通过与单发探测器融合的比较分析和改进的零发检测

Franklin Open Pub Date : 2025-03-01 DOI: 10.1016/j.fraope.2025.100243

Ayan Paul, Rajendra Machavaram

{"title":"Advancing capsicum detection in night-time greenhouse environments using deep learning models: Comparative analysis and improved zero-shot detection through fusion with a single-shot detector","authors":"Ayan Paul, Rajendra Machavaram","doi":"10.1016/j.fraope.2025.100243","DOIUrl":"10.1016/j.fraope.2025.100243","url":null,"abstract":"<div><div>This study addresses capsicum detection in night-time greenhouse settings using a robust approach. A dataset of 300 images was curated, capturing various shooting distances, heights, occlusions, and lighting intensities, and underwent extensive pre-processing and augmentation. The single-shot custom-trained You Only Look Once version 9 (YOLOv9) model was evaluated, achieving precision, recall, F1 score, and mean Average Precision (mAP) of 0.898, 0.864, 0.881, and 0.947, respectively, with a detection speed of 38.46 frames per second (FPS). Concurrently, the zero-shot Grounding self-DIstillation with NO labels (Grounding DINO) model required no training and was hypertuned for capsicum detection using Google Colaboratory. Utilizing its Open Vocabulary Object Detection (OVOD) capability, the model successfully performed capsicum detection, positional search, growth stage detection, and diseased capsicum detection with confidence scores of 74 %, 43 %, 74 %, and 43 %, respectively. Comparative testing of both models on 100 test images containing 175 capsicums showed that YOLOv9 outperformed Grounding DINO with precision, recall, and F1 scores of 0.88, 0.86, and 0.87, compared to Grounding DINO's 0.72, 0.69, and 0.70. YOLOv9 also demonstrated an inference speed of 26 milliseconds, approximately five times faster than Grounding DINO. The fusion of YOLOv9 and Grounding DINO into You Only Look Once version Open Vocabulary Object Detection (YOLOvOVOD) significantly improved performance, achieving the highest confidence of 88 % for growth stage detection and a 65.11 % increase in confidence for positional search. This integrated approach leverages the strengths of both models, presenting a robust solution for future automation in agricultural machine vision.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"10 ","pages":"Article 100243"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143685175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lithium-ion battery state of health estimation using intelligent methods 锂离子电池健康状态智能评估方法研究

Franklin Open Pub Date : 2025-03-01 DOI: 10.1016/j.fraope.2025.100237

Hemavathi S

{"title":"Lithium-ion battery state of health estimation using intelligent methods","authors":"Hemavathi S","doi":"10.1016/j.fraope.2025.100237","DOIUrl":"10.1016/j.fraope.2025.100237","url":null,"abstract":"<div><div>In electric vehicle applications, detecting Li-ion battery degradation is essential to ensure safety and reliability. A key approach to assessing battery health is monitoring the internal impedance and capacity over the battery's lifetime, which provides insight into the State of Health (SOH) and indicates whether the battery has reached its End of Life (EOL). This study proposes an intelligent SOH estimation algorithm utilizing Feed-forward and Recurrent Neural Networks, trained with the Levenberg-Marquardt function, to predict battery SOH under various aging conditions. The methodology begins with life cycle and Electrochemical Impedance Spectroscopy (EIS) tests to establish the charge-discharge characteristics and create an Equivalent Circuit Model that represents the dynamic properties and degradation indicators of an 18650 Li-ion battery. Key model parameters, such as internal resistance, are extracted per cycle to track aging progression. Finally, the SOH estimation models, developed in SIMULINK, utilize internal impedance and capacity metrics to predict SOH under various aging scenarios. Results in SIMULINK demonstrate that both networks provide accurate SOH estimations; however, the Recurrent Neural Network achieves faster convergence, reaching accurate predictions within 10 epochs. This improved convergence speed, along with high measurement accuracy and reliability, underscores the Recurrent Neural Network's suitability for real-time SOH monitoring in electric vehicle applications.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"10 ","pages":"Article 100237"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143577212","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Partial detectability and generalized functional observer design for linear descriptor systems 线性广义系统的部分可检测性与广义泛函观测器设计

Franklin Open Pub Date : 2025-03-01 DOI: 10.1016/j.fraope.2025.100238

Juhi Jaiswal , Thomas Berger , Nutan Kumar Tomar

{"title":"Partial detectability and generalized functional observer design for linear descriptor systems","authors":"Juhi Jaiswal , Thomas Berger , Nutan Kumar Tomar","doi":"10.1016/j.fraope.2025.100238","DOIUrl":"10.1016/j.fraope.2025.100238","url":null,"abstract":"<div><div>In this study, we present two primary contributions to the theory of detectability for linear time-invariant descriptor systems. First, we establish a necessary and sufficient condition for the partial detectability by proving that it holds if and only if a specific rank condition involving the system’s coefficient matrices is satisfied. We define partial detectability through the system’s behavior approach and also provide a geometric characterization of this concept in terms of Wong sequences. Additionally, we discuss particular cases of the rank characterization in detail and establish a novel algebraic characterization of partial observability for state-space systems. The second major contribution is demonstrating that partial detectability is equivalent to the existence of a generalized functional estimator. However, we show that while partial detectability is necessary for the existence of generalized functional observers, it is not a sufficient condition. We derive an additional requirement that, when combined with partial detectability, ensures the construction of a generalized functional observer. The results are illustrated through numerical examples.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"10 ","pages":"Article 100238"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644953","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0