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Adaptive Segmentation for Unconstrained Iris Recognition

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Computers, Materials & Continua 2024年第2期78卷 1591-1609页

作者： Mustafa AlRifaee Sally Almanasra Adnan Hnaif Ahmad Althunibat mohammad Abdallah Thamer Alrawashdeh Faculty of Architecture and Design Al-Zaytoonah University of JordanAmman11733Jordan Faculty of Computer Studies Arab Open UniversityRiyadh11681Saudi Arabia Faculty of Science and Information Technology Al-Zaytoonah University of JordanAmman11733Jordan

In standard iris recognition systems,a cooperative imaging framework is employed that includes a light source with a near-infrared wavelength to reveal iris texture,look-and-stare constraints,and a close distance requirement to the capture *** these conditions are relaxed,the system’s performance significantly deteriorates due to segmentation and feature extraction ***,a novel segmentation algorithm is proposed to correctly detect the pupil and limbus boundaries of iris images captured in unconstrained ***,the algorithm scans the whole iris image in the Hue Saturation Value(HSV)color space for local maxima to detect the sclera *** image quality is then assessed by computing global features in red,green and blue(RGB)space,as noisy images have heterogeneous *** iris images are accordingly classified into seven categories based on their global RGB *** the classification process,the images are filtered,and adaptive thresholding is applied to enhance the global contrast and detect the outer iris ***,to characterize the pupil area,the algorithm scans the cropped outer ring region for local minima values to identify the darkest area in the iris *** experimental results show that our method outperforms existing segmentation techniques using the UBIRIS.v1 and v2 databases and achieved a segmentation accuracy of 99.32 on UBIRIS.v1 and an error rate of 1.59 on UBIRIS.v2.

关键词： Image recognition color segmentation image processing localization

Metaheuristic-Driven Two-Stage Ensemble Deep Learning for Lung/Colon Cancer Classification

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Computers, Materials & Continua 2024年第9期80卷 3855-3880页

作者： Pouyan Razmjouei Elaheh Moharamkhani Mohamad Hasanvand Maryam Daneshfar mohammad Shokouhifar Department of Electrical&Computer Engineering Valie-e-Asr University of RafsanjanKerman***Iran International Academic Relations Office(IRO) Computer Science DepartmentUniversity of HalabjaHalabja46018Iraq Department of Computer Engineering University of Mohaghegh ArdabiliArdabil***Iran Department of Biomedical Engineering Islamic Azad University of MashhadMashhad***Iran Department of Electrical&Computer Engineering Shahid Beheshti UniversityTehran***Iran

This study investigates the application of deep learning,ensemble learning,metaheuristic optimization,and image processing techniques for detecting lung and colon cancers,aiming to enhance treatment efficacy and improve survival *** introduce a metaheuristic-driven two-stage ensemble deep learning model for efficient lung/colon cancer *** diagnosis of lung and colon cancers is attempted using several unique indicators by different versions of deep Convolutional Neural Networks(CNNs)in feature extraction and model constructions,and utilizing the power of various Machine Learning(ML)algorithms for final ***,we consider different scenarios consisting of two-class colon cancer,three-class lung cancer,and fiveclass combined lung/colon cancer to conduct feature extraction using four *** extracted features are then integrated to create a comprehensive feature *** the next step,the optimization of the feature selection is conducted using a metaheuristic algorithm based on the Electric Eel Foraging Optimization(EEFO).This optimized feature subset is subsequently employed in various ML algorithms to determine the most effective ones through a rigorous evaluation *** top-performing algorithms are refined using the High-Performance Filter(HPF)and integrated into an ensemble learning framework employing weighted *** findings indicate that the proposed ensemble learning model significantly surpasses existing methods in classification accuracy across all datasets,achieving accuracies of 99.85%for the two-class,98.70%for the three-class,and 98.96%for the five-class datasets.

关键词： Lung cancer colon cancer feature selection electric eel foraging optimization deep learning ensemble learning

A Review of Image Steganography Based on Multiple Hashing Algorithm

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Computers, Materials & Continua 2024年第8期80卷 2463-2494页

作者： Abdullah Alenizi mohammad Sajid mohammadi Ahmad A.Al-Hajji Arshiya Sajid Ansari Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science College of Engineering and Information TechnologyOnaizah CollegesQassim56312Saudi Arabia

Steganography is a technique for hiding secret messages while sending and receiving communications through a cover *** ancient times to the present,the security of secret or vital information has always been a significant *** development of secure communication methods that keep recipient-only data transmissions secret has always been an area of ***,several approaches,including steganography,have been developed by researchers over time to enable safe data *** this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,*** have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)*** this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this *** encoding the data and embedding it into a carry image,this review verifies that it has been ***,embedded text in photos conveys crucial signals about the *** review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data *** the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.

关键词： Image steganography multiple hashing algorithms Hash-LSB approach RSA algorithm discrete cosine transform(DCT)algorithm blowfish algorithm

Characterization and Selection of Microcrystalline Cellulose from Oil Palm Empty Fruit Bunches for Strengthening Hydrogel Films

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Journal of Renewable Materials 2024年第3期12卷 513-537页

作者： Susi Susi Makhmudun Ainuri Wagiman Wagiman mohammad Affan Fajar Falah Department of Agroindustrial Technology Faculty of AgricultureUniversitas Lambung MangkuratJl A Yani Km 36BanjarbaruSouth Kalimantan70714Indonesia Doctoral Programme of Agroindustrial Technology Faculty of Agricultural TechnologyUniversitas Gadjah MadaJl Flora No.1BulaksumurYogyakarta55281Indonesia Department of Agroindustrial Technology Faculty of Agricultural TechnologyUniversitas Gadjah MadaJl Flora No.1BulaksumurYogyakarta55281Indonesia

Microcrystalline cellulose(MCC)is one of the cellulose derivatives produced as a result of the depolymerization of a part of cellulose to achieve high *** implemented in other polymers,high crystallinity correlates with greater strength and stiffnes,but it can reduce the water-holding *** acid concentration and hydrolysis time will affect the acquisition of crystallinity and water absorption capacity,both of which have significance as properties of hydrogel *** study aimed to evaluate the properties and select the MCC generated from varying the proportion of hydrochloric acid(HCl)and the appropriate hydrolysis time as a filler for film *** was produced by hydrolyzing cellulose of oil palm empty fruit bunches(OPEFB)with the HCl solution at varied concentrations and *** results show that the longer hydrolysis times and higher HCl concentrations increase crystallinity and density while lowering yield and water *** extensive acid hydrolysis reduces the amorphous area significantly,allowing the depolymerization to occur and extend the crystalline *** morphological properties of the MCC,which are smaller but compact,indicate the presence of disintegrating and diminishing structures.A 2.5 N HCl concentration and a 45-min hydrolysis time succeed in sufficient crystallinity as well as maintaining good water absorption *** treatment produced MCC with absorption capacity of 4.03±0.26 g/g,swelling capacity of 5.03±0.26 g/g,loss on drying of 1.44%±0.36,bulk and tapped density of 0.27±0.031 g/cm^(3) and 0.3±0.006 g/cm^(3),respectively,with a crystallinity index of 88.89%±4.76 and a crystallite size of 4.23±0.70 *** MCC generated could potentially be utilized as a hydrogel film filler,since a given proportion will be able to maintain the strength of the hydrogel,not readily dissolve but absorb water significantly.

关键词： Acid hydrolysis hydrogel OPEFB microcrystalline cellulose water absorption

Coupling of reduced inorganic fertilizer with plant-based organic fertilizer as a promising fertilizer management strategy for colored rice in tropical regions

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Journal of Integrative Agriculture 2024年第1期23卷 93-107页

作者： Tingcheng Zhao Aibin He mohammad Nauman Khan Qi Yin Shaokun Song Lixiao Nie Research Center for Physiology and Ecology and Green Cultivation of Tropical Crops School of Breeding and Multiplication(Sanya Institute of Breeding and Multiplication)Hainan UniversitySanya 572000China

Colored rice is a type of high-quality,high-added-value rice that has attracted increasing attention in recent *** use of large amounts of inorganic nitrogen fertilizer in rice fields results in low fertilizer use efficiency and high environmental *** fertilizer is a promising way to improve soil quality and sustain high ***,most studies focus on the effect of animal-based organic *** effects of different ratios of plantbased organic fertilizer and inorganic fertilizer on the grain yield and quality of colored rice have rarely been ***,a two-year field experiment was conducted in 2020 and 2021 to study the effects of replacing inorganic N fertilizers with plant-based organic fertilizers on the yield,nitrogen use efficiency(NUE),and anthocyanin content of two colored rice varieties in a tropical region in *** experimental treatments included no nitrogen fertilization(T1),100% inorganic nitrogen fertilizer(T2),30%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T3),60%inorganic nitrogen fertilizer substitution with plant-based organic fertilizer(T4),and 100% plantbased organic fertilizer(T5).The total nitrogen provided to all the treatments except T1 was the same at 120 kg *** results showed that the T3 treatment enhanced the grain yield and anthocyanin content of colored rice by increasing nitrogen use efficiency compared with *** average,grain yields were increased by 9 and 8%,while the anthocyanin content increased by 16 and 10% in the two colored rice varieties under T3 across the two years,respectively,as compared with *** study of the residual effect of partial substitution of inorganic fertilizers showed that the substitution of inorganic fertilizer with plant-based organic fertilizer improved the soil physiochemical properties,and thus increased the rice grain yield,in the subsequent *** highest grain yield of the subsequent rice crop was observe

关键词： colored rice organic fertilizer soil quality grain yield anthocyanin

Platform Evolution in an Oligo-Miocene Back-arc Basin:An Example from the Central Iran Basin

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Acta Geologica Sinica(English Edition) 2024年第1期98卷 185-206页

作者： Masoud SHARIFI-YAZDI Amirhossein ENAYATI Jamal SALEHI AGHDAM mohammad BAHREHVAR Seyed Mustafa REZAEI Department of Geology Faculty of Earth SciencesGeography and AstronomyUniversity of Vienna1090 Vienna.Austria Geology and Geophysics Department Tehran Energy Consultants(TEC Co.)TehranIran School of Geology College of ScienceUniversity of TehranTehranIran Department of Geology Tarbiat Modares UniversityTehranIran

The Qom Formation is the most important hydrocarbon reservoir target in Central *** Qom platform developed in a back-arc basin during the Oligo-Miocene due to the closing of the Tethyan *** formation consists of a variety of carbonate and non-carbonate facies deposited on a platform ranging from supratidal to basin.A combination of tectonic and eustatic events led to some lateral and vertical facies variations in the study *** third-order depositional sequences and related surfaces were identified regarding vertical facies changes in the studied sections of this Oligo-Miocene *** to all results and data,this succession was initially deposited during the Chattian upon a distally steepened ramp of siliciclastic-carbonate composition,including the Bouma ***,from the late Chattian to the Aquitanian,the platform changed into a homoclinal carbonate ramp with a gentle *** respect to tectonic activity,this phase was a calm period during the deposition of the Qom ***,a drowned carbonate platform and a rimmed shelf emerged during the Burdigalian,terminated by the continental deposits of the Upper Red *** all geological characteristics,three main tectono-eustatic evolutionary phases have been recognized in the Qom back-arcbasin.

关键词： carbonate ramp depositional facies submarine fan eustasy basement faults back-arc basin

Revealing connectivity in residential Architecture: An algorithmic approach to extracting adjacency matrices from floor plans

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Frontiers of Architectural Research 2024年第2期13卷 370-386页

作者： mohammad Amin Moradi Omid mohammadrashidi Navid Niazkar Morteza Rahbar School of Architecture and Engineering University College of RouzbahanMazandaranIran School of Architecture Islamic Azad UniversitySafaDasht CampusTehranIran A.James Clark School of Engineering University of MarylandCollege ParkMDUSA School of Architecture and Environmental Design Iran University of Science and TechnologyTehranIran

In today's world, various approaches and parameters exist for designing a plan and determining its spatial, placement. Hence, various modes for identifying crucial locations can be explored when an architectural plan is designed in different dimensions. While designing all these modes takes considerable time, there are numerous potential applications for artificial intelligence (AI) in this domain. This study aims to compute and use an adjacency matrix to generate architectural residential plans. Additionally, it develops a plan generation algorithm in Rhinoceros software, utilizing the Grasshopper plugin to create a dataset of architectural plans. In the following step, the data was entered into a neural network to identify the architectural plan's type, furniture, icons, and use of spaces, which was achieved using YOLOv4, EfficientDet, YOLOv5, DetectoRS, and RetinaNet. The algorithm's execution, testing, and training were conducted using Darknet and PyTorch. The research dataset comprises 12,000 plans, with 70% employed in the training phase and 30% in the testing phase. The network was appropriately trained practically and precisely in relation to an average precision (AP) resulting of 91.50%. After detecting the types of space use, the main research algorithm has been designed and coded, which includes determining the adjacency matrix of architectural plan spaces in seven stages. All research processes were conducted in Python, including dataset preparation, network object detection, and adjacency matrix algorithm design. Finally, the adjacency matrix is given to the input of the proposed plan generator network, which consequently, based on the resulting adjacency, obtains different placement modes for spaces and furniture.

关键词： Algorithm design Adjacency matrix Generate floor plan Detection plan

Transparent and Accurate COVID-19 Diagnosis:Integrating Explainable AI with Advanced Deep Learning in CT Imaging

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 3101-3123页

作者： mohammad Mehedi Hassan Salman A.AlQahtani Mabrook S.AlRakhami Ahmed Zohier Elhendi Department of Information Systems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Science Technology and Innovation Department King Saud UniversityRiyadh11543Saudi Arabia

In the current landscape of the COVID-19 pandemic,the utilization of deep learning in medical imaging,especially in chest computed tomography(CT)scan analysis for virus detection,has become increasingly *** its potential,deep learning’s“black box”nature has been a major impediment to its broader acceptance in clinical environments,where transparency in decision-making is *** bridge this gap,our research integrates Explainable AI(XAI)techniques,specifically the Local Interpretable Model-Agnostic Explanations(LIME)method,with advanced deep learning *** integration forms a sophisticated and transparent framework for COVID-19 identification,enhancing the capability of standard Convolutional Neural Network(CNN)models through transfer learning and data *** approach leverages the refined DenseNet201 architecture for superior feature extraction and employs data augmentation strategies to foster robust model *** pivotal element of our methodology is the use of LIME,which demystifies the AI decision-making process,providing clinicians with clear,interpretable insights into the AI’s *** unique combination of an optimized Deep Neural Network(DNN)with LIME not only elevates the precision in detecting COVID-19 cases but also equips healthcare professionals with a deeper understanding of the diagnostic *** method,validated on the SARS-COV-2 CT-Scan dataset,demonstrates exceptional diagnostic accuracy,with performance metrics that reinforce its potential for seamless integration into modern healthcare *** innovative approach marks a significant advancement in creating explainable and trustworthy AI tools for medical decisionmaking in the ongoing battle against COVID-19.

关键词： Explainable AI COVID-19 CT images deep learning

An Electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

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Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar Ayman Amer mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap Electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography