Franklin Open最新文献

{"title":"Numerical solution of fuzzy non-linear equations under generalized trapezoidal fuzziness by Newton–Raphson method","authors":"Sanjoy Basu ,&nbsp;G.S. Mahapatra","doi":"10.1016/j.fraope.2024.100168","DOIUrl":"10.1016/j.fraope.2024.100168","url":null,"abstract":"<div><div>In the real world, we are faced with many problems that cannot be easily described by crisp values, as there is always some uncertainty involved in real-life situations and in those situations, we end up receiving fuzzy values rather than crisp ones in those situations. Some preliminary concepts of fuzzy sets and operations on trapezoidal fuzzy numbers incorporated with the membership function have been discussed here. This paper aims to demonstrate the advantages of the newly developed fuzzified newton–raphson method with the help of trapezoidal fuzzy numbers for solving algebraic nonlinear equations arising in fuzzy environments. The algorithm of newton–raphson techniques for solving the same has been described. This paper presents several examples of how the new fuzzified newton–raphson method works.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"9 ","pages":"Article 100168"},"PeriodicalIF":0.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142529349","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}

{"title":"Optimization of a fractional-order interval type-2 fuzzy PID controller based on BBO for real-time applications","authors":"Mohamed I. Abdo,&nbsp;Emad A. Elsheikh","doi":"10.1016/j.fraope.2024.100121","DOIUrl":"10.1016/j.fraope.2024.100121","url":null,"abstract":"<div><p>This paper addresses the development of a robust controller for a nonlinear system to minimize the tracking errors and reduce the effects of external noise and disturbances. To achieve this, the biogeography-based optimization (BBO) algorithm is utilized for an optimally robust interval type 2 fractional-order fuzzy proportional integral derivative controller (BB0-IT2FO-FPID) is proposed. The proposed method offers several advantages. Firstly, the proposed controller is optimized to achieve robustness and minimize tracking errors. Secondly, it effectively handles external noise and disturbances, making it suitable for real-world applications. Thirdly, the use of the BBO algorithm enhances the controller's performance by dynamically adjusting its parameters based on system requirements. The performance of the proposed controller is validated by applying it to control a robotic manipulator, which presents challenges due to its nonlinear characteristics and interacting multi-input multi-output (MIMO) dynamics. Additionally, a real-time evaluation of the proposed controller is conducted by applying it to the speed control of a direct current (DC) machine. The effectiveness of the proposed controller is verified through simulation and practical experiments and comparisons with other optimized controllers, namely FO fuzzy type 1 PID (T1FO-FPID) and FOPID. The simulation and practical results demonstrate the superior performance of the BBO-IT2FO-FPID controller in the presence of system uncertainties and different types of disturbances.</p></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"8 ","pages":"Article 100121"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773186324000513/pdfft?md5=85279f1552f83128002f003370ba23e1&pid=1-s2.0-S2773186324000513-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096377","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}

{"title":"Assessment of hybrid machine learning models for non-linear system identification of fatigue test rigs","authors":"L. Heindel ,&nbsp;P. Hantschke ,&nbsp;M. Kästner","doi":"10.1016/j.fraope.2024.100157","DOIUrl":"10.1016/j.fraope.2024.100157","url":null,"abstract":"<div><p>The prediction of system responses for a given fatigue test bench drive signal is a challenging problem, since highly dynamic loads from measurement campaigns must be reproduced accurately. Linear frequency response function models are commonly used for this system identification task, but energy intensive experimental iterations are required to account for system non-linearities. Two novel hybrid modeling strategies are suggested, which augment existing approaches using non-linear Long Short-Term Memory networks. These are trained and deployed on short subsequences of measurement data and recombined using a windowing technique, which enables their application to measurement data with high sampling rates. In addition to fatigue test bench commissioning, these hybrid models can also be employed in the field of virtual sensing. The approach is tested using non-linear experimental data from a servo-hydraulic test rig and this dataset is made publicly available. A variety of metrics in time and frequency domains, as well as fatigue strength under variable amplitudes, are employed in the evaluation. It is shown, that hybrid models can successfully use frequency response function models as a linear baseline estimate, which is further improved by Long Short-Term Memory networks to enable non-linear predictions.</p></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"8 ","pages":"Article 100157"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773186324000872/pdfft?md5=3af8b7d379159b873557bb6cdb4c3d9a&pid=1-s2.0-S2773186324000872-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142242040","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}

{"title":"XU-NetI: Simple U-shaped encoder-decoder network for accurate imputation of multivariate missing data","authors":"Firdaus Firdaus ,&nbsp;Siti Nurmaini ,&nbsp;Bambang Tutuko ,&nbsp;Muhammad Naufal Rachmatullah ,&nbsp;Anggun Islami ,&nbsp;Annisa Darmawahyuni ,&nbsp;Ade Iriani Sapitri ,&nbsp;Widya Rohadatul Ais'sy ,&nbsp;Muhammad Irfan Karim ,&nbsp;Muhammad Fachrurrozi ,&nbsp;Ahmad Zarkasi","doi":"10.1016/j.fraope.2024.100151","DOIUrl":"10.1016/j.fraope.2024.100151","url":null,"abstract":"<div><p>Patients in intensive care unit (ICU) often have multiple vital signs monitored continuously. However, missing data is common in ICU settings, negatively impacting clinical decision-making and patient outcomes. In this study propose a multivariate data imputation method based on simple U-Shaped encoder-decoder network imputation (XU-NetI) method to learn the underlying patterns in the data and generate imputations for missing values of vital signs data with ICU patients. To evaluate the performance of this study's imputation methods, this study employed a publicly available database such the medical information mart for intensive care III (MIMIC III) v1.4. In this study proposed model has been developed to analyze 219.281 vital sign worth of data, focusing on eight essential vital sign features: body temperature, heart rate, respiration rate, systolic blood pressure, diastolic blood pressure, mean blood pressure, oxygen saturation, and glucose. The evaluation results demonstrates the effectiveness of the imputation techniques in improving the accuracy of predictive models. This study compared the XU-NetI approach to other state-of-the-art imputation methods including Autoencoder and Convolutional Neural Networks. As a result found, the technique using XU-NetI architecture outperformed them, in terms of root mean square error (RSME) by approximately 0.01, mean absolute error (MAE) by approximately 0.009, and R square (R2) by approximately 0.99. The XU-NetI method has the potential to enhance clinical decision-making and improve patient outcomes.</p></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"8 ","pages":"Article 100151"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773186324000811/pdfft?md5=402392e0a948ad019703d151ddcc2e8d&pid=1-s2.0-S2773186324000811-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142270707","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}

{"title":"Crowd anomaly estimation and detection: A review","authors":"A. Hussein ,&nbsp;M.W. Raed ,&nbsp;A. Al-Shaikhi ,&nbsp;M. Mohandes ,&nbsp;B. Liu","doi":"10.1016/j.fraope.2024.100169","DOIUrl":"10.1016/j.fraope.2024.100169","url":null,"abstract":"<div><div>Abnormal crowd detection and estimation are critical in video surveillance for ensuring public safety and preventing stampedes. Owing to occlusions and blind spots, traditional video surveillance methods cannot detect, estimate, or locate people in dense moving crowds with acceptable accuracy, posing a major challenge. Therefore, this study aims to provide an in-depth analysis of the most recent advancements in recognizing abnormal behaviors in large crowds. We present a comprehensive literature review on crowd anomaly detection using disruptive technologies such as radio frequency identification, wireless sensor networks, Wi-Fi, and Bluetooth low energy, employing device-free noninvasive algorithms based on received signal strength indicator variations to detect the speed and direction of a moving crowd to predict the onset of a stampede. Furthermore, this study presents the most recent findings on mobile crowdsensing based on edge computing, urban dynamics, optical flow, and machine learning techniques. Finally, we critically analyze the major challenges, shedding light on opportunities and directions for future work.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"8 ","pages":"Article 100169"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142534817","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}

{"title":"Chaos-based audio encryption: Efficacy of 2D and 3D hyperchaotic systems","authors":"Thejas Haridas,&nbsp;Upasana S.D.,&nbsp;Vyshnavi G.,&nbsp;Malavika S. Krishnan,&nbsp;Sishu Shankar Muni","doi":"10.1016/j.fraope.2024.100158","DOIUrl":"10.1016/j.fraope.2024.100158","url":null,"abstract":"<div><p>Secure communication in the digital age is necessary; securing audio data becomes very critical since this is normally transmitted across susceptible networks. Traditional approaches to encryption, like Advanced Encryption Standard and Rivest–Shamir–Adleman, are pretty solid but mostly too computationally intensive for real-time audio applications. This paper presents a new audio encryption scheme using chaotic systems, characterized by high sensitivity to initial conditions, pseudo-randomness, and determinism. These properties make chaotic systems ideal for generating keys for cryptographic purposes. Indeed, complex keys that would be nearly impossible to reverse-engineer without exact initial parameters can be obtained with them. This methodology first digitizes the audio signal and subsequently encrypts each sample according to chaotic sequences from multiple systems, like 2D Memristive Hyperchaotic Maps and 3D Hyperchaotic Quadratic Maps. The encryption processes enormously increase the randomness of the encrypted audio and blind the original data, demonstrating the strength of the chaotic systems in securing audio information.</p><p>Simulation of this encryption approach confirms its effectuality in providing strong security for audio data while maintaining efficiency, thus being suitable for real-time applications. The developed encryption schemes show high resistance to differential attacks, while the quality of the encrypted audio remains acceptable after transformation. This result can demonstrate chaotic systems’ potential to provide a secure and efficient solution for audio communications, which has broad applications in telecommunications, military communications, and confidential conferencing systems. This work, described in the paper, thus satisfies the growing demand for robust security in digital communications and opens up avenues of future research toward chaotic parameter optimization and an extension to other forms of data, enhancing the security features in all types of digital communication channels.</p></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"8 ","pages":"Article 100158"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773186324000884/pdfft?md5=cd74e6d4bc084f15b3e78c419930a783&pid=1-s2.0-S2773186324000884-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142270709","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}

{"title":"Further finite-time stability analysis of neural networks with proportional delay","authors":"Binbin Gan ,&nbsp;Mengqing Yang","doi":"10.1016/j.fraope.2024.100159","DOIUrl":"10.1016/j.fraope.2024.100159","url":null,"abstract":"<div><div>Different from fixed delays between neurons, proportional delay is a time-varying unbounded delay. In this paper, the issue of finite-time stability of fractional-order neural networks with proportional delay is investigated. To address the proportional delay terms in the system, a new Gronwall-type inequality with delay is proposed. Based on this inequality, order-related criterion for finite-time stability of fractional-order neural networks with proportional delay is obtained. Finally, some numerical experiments demonstrate the effectiveness and superiority of the results.</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"8 ","pages":"Article 100159"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142327942","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}

{"title":"Review of advancements in wall climbing robot techniques","authors":"Junru Zhu ,&nbsp;Yongqiang Zhu ,&nbsp;Pingxia Zhang","doi":"10.1016/j.fraope.2024.100148","DOIUrl":"10.1016/j.fraope.2024.100148","url":null,"abstract":"<div><p>Wall Climbing Robots (WCRs) represent the proliferation in the field of robotics. Research on wall-climbing robots has led to significant advancements in various capabilities, particularly in abilities such as navigation on curved surfaces and transitioning between different walls. This systematic review offers a detailed analysis of the current advancements in wall-climbing robots, highlighting their promising applications in real-life scenarios such as inspection and maintenance. We discussed and evaluated the different methods of adhesion and locomotion, considering their effectiveness across different scenarios and key factors impacting their performance. The control strategies employed in wall-climbing robots and their perception abilities were also examined in this review. Possible challenges ahead for wall-climbing robots include the optimization of their robustness and adaptability to complex environments, which are crucial for optimizing the robot's efficiency.</p></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"8 ","pages":"Article 100148"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773186324000781/pdfft?md5=2c44f8b140c7a43bf837138c2b42e5d0&pid=1-s2.0-S2773186324000781-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096510","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}

{"title":"Expected value of generalized trapezoidal bipolar fuzzy number to solve a multi-item marketing planning inventory model with allowable shortages","authors":"Sourav Kumar Giri ,&nbsp;Totan Garai ,&nbsp;Sahidul Islam","doi":"10.1016/j.fraope.2024.100164","DOIUrl":"10.1016/j.fraope.2024.100164","url":null,"abstract":"<div><div>Decision makers often grapple with the complexity of multi-faceted real-life problems, where uncertainty arises from both positive and negative states of mind. This duality reflects the decision maker’s optimistic and pessimistic perspectives during the decision-making process. To address this, our paper introduces innovative concepts and frameworks for generalized bipolar trapezoidal fuzzy numbers. We propose novel arithmetic operations on these fuzzy numbers, computing the negative <span><math><mi>α</mi></math></span>-cut and positive <span><math><mi>β</mi></math></span>-cut methods. Furthermore, we uniquely compute the convex combination of expected values from both the positive and negative membership parts. These theoretical advancements are applied to a practical case study: a multi-item marketing planning inventory model with allowable shortages. Our proposed method’s efficacy is highlighted through detailed numerical illustrations, sensitivity analyses and comparative studies complemented by compelling graphical presentations</div></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"8 ","pages":"Article 100164"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427114","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}

{"title":"Assessment of retinal blood vessel segmentation using U-Net model: A deep learning approach","authors":"Smita Das ,&nbsp;Suvadip Chakraborty ,&nbsp;Madhusudhan Mishra ,&nbsp;Swanirbhar Majumder","doi":"10.1016/j.fraope.2024.100143","DOIUrl":"10.1016/j.fraope.2024.100143","url":null,"abstract":"<div><p>Segmentation of retinal blood vessels from fundus images is vital to assist ophthalmologists in diagnosing different eye diseases like Arteriosclerosis, Glaucoma, Diabetic Retinopathy, Hypertension, and Choroidal Neovascularization. Accurate detection and timely treatment of these eye diseases can prevent irreversible impairment of vision. In computer-aided automatic diagnosis, Preprocessing of fundus images is necessary to reduce the uneven retinal image illumination, as well as the undesirable effect arising from the contrast differences between the retinal blood vessels and the background. In this study, the Hessian-based Frangi vesselness filter is proposed to enhance vasculature in fundus images. This approach seeks to extract thin vessels to diminish the intensity disparity between thick and thin vessels. Its accuracy has never, however, been thoroughly evaluated. To verify the effectiveness of the suggested filter for boosting vessel-like structures in the fundus images, an experimental approach is presented in this paper. The ability of the filter to improve vessel-like structures in fundus images is validated, and an experimental technique for evaluating filter performance using the U-Net model is described. Five quantitative performances, namely Accuracy, Recall, Specificity, Precision, and F1 Score measures on the DRIVE, HRF, DIARETDB1, DIARETDB0, CHASEDB1, ORIGA, DRISHTI GS, DRIONS DB, FIRE, and FIOT datasets, were evaluated and quantified in these experiments to validate the efficacy of the proposed filter. The results demonstrated a noteworthy improvement by achieving an Accuracy of 99.79 %, 99.84 %, 99.64 %, 99.72 %, 99.57 %, 99.48 %, 99.77 %, 99.05 %, 99.93 %, and 99.40 % respectively. Empirical evidence supports the advantages of this approach.</p></div>","PeriodicalId":100554,"journal":{"name":"Franklin Open","volume":"8 ","pages":"Article 100143"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773186324000732/pdfft?md5=18f62e660d2cb2d8c276c6814e44e47c&pid=1-s2.0-S2773186324000732-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142096513","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}