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Photoneutron dose and flux determination of a typical LINAC by MCNP simulation

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Radiation Detection Technology and Methods 2021年第4期5卷 627-632页

作者： Aydin Ghalehasadi Eren Sahiner saleh ashrafi Sasan Geranmayeh Hadi kasani Niyazi Meriç University of Tabriz TabrizIran Institute of Nuclear Sciences Ankara University06100 Be¸sevlerAnkaraTurkey

Purpose High-energy electron linear accelerators(LINACs)have a wide use in *** photoneutron production in medical linear accelerators,when operating at energies greater than 10 MeV,is an important subject to consider in patient’s treatment *** this work,we simulate a typical LINAC to calculate photoneutron dose and flux in radiotherapy *** The latest version of MCNPX Monte Carlo code along with MCNP visual editor has been used to simulate the LINAC and its *** production has been successfully simulated by selecting appropriate physics card and *** and flux of produced photoneutrons have been calculated by using mesh tally *** Production of photoneutrons in LINAC head and its components have been successfully simulated by using MCNPX *** visual editor has been used to track the *** dose and flux have been calculated using mesh tally function,with good results of statistical *** The photoneutron production has been successfully simulated and *** proposed simulation code is able to calculate photoneutron dose and *** to photoneutron production cross sections,the appropriate parameters have been selected to reduce the run-time of simulation code.

关键词： LINAC Photoneutron Dose Flux MCNPX code

Blockchain for secure and decentralized artificial intelligence in cybersecurity: A comprehensive review

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Blockchain(Research and Applications) 2024年第3期5卷 184-208页

作者： Ahmed M.Shamsan saleh Department of Information Technology University of TabukTabuk47512Saudi Arabia

As the use of artificial intelligence (AI) grows within the field of cybersecurity, so does the demand for secure and decentralized AI systems to protect against potential cyber threats. Blockchain technology has emerged as the ideal approach for increasing both the security and privacy of AI systems since it provides decentralized and immutable data storage. This systematic literature review focuses on the integration of blockchain technology with decentralized AI within cybersecurity. It provides a comprehensive taxonomy of blockchain technology and decentralized AI for cybersecurity, serving as the starting point for the study. This paper begins with an overview of blockchain technology and its possible uses in cybersecurity and also analyzes its challenges and opportunities. Decentralized AI is also covered in the study, along with its potential advantages and difficulties in decentralized AI cybersecurity. Building on that foundation, this study provides convincing findings highlighting the beneficial relationships between blockchain technology and decentralized AI for cybersecurity, contributing to a nuanced comprehension of their integration. Moreover, it offers real-world uses of blockchain-enabled, decentralized AI to discuss its usefulness in tackling cybersecurity concerns. Finally, this paper discusses future research directions for blockchain-enabled decentralized AI in cybersecurity, including potential applications and implications of this technology in the field, emphasizing the potential of blockchain-enabled decentralized AI in cybersecurity to enhance security, privacy, and trust in AI systems.

关键词： Blockchain Artificial intelligence Decentralized Cybersecurity

Advanced Nanocomposite Arabic Gum Polyacrylic Acid Hydrogels for Flexible Supercapacitors

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Journal of Renewable Materials 2024年第7期12卷 1219-1236页

作者： Borhan Albiss Asala saleh Nanotechnology Institute Jordan University of Science and TechnologyP.O.Box 3030Irbid22110Jordan

In this work,the fabrication and characterization of the nanocomposite hydrogel,as a solid electrode in electro-chemical cell and gel electrolyte material using Indium titanium oxide/polyethylene terephthalate(ITO/PET)ﬂex-ible substrate for double-layer supercapacitors have been *** nanocomposite hydrogel composed of Arabic gum(AG),Acrylic acid(AA),reduced graphene oxide(RGO),and silver nanoparticles(AgNPs)was fab-ricated via a physical cross-linked polymerization reaction,in which the ascorbic acid was used as a reducing agent to generate AgNPs and to convert Graphene oxide(GO)to RGO during the polymerization *** morphology and structural characteristics of nanocomposite hydrogel were investigated using atomic force microscopy(AFM),scanning electron microscope(SEM),Fourier transfer infrared(FTIR),and X-rayﬂuores-cence(XRF).Additionally,the effect of RGO and AgNPs on hydrogel stability was assessed through Thermogra-vimetric analysis(TGA)and differential scanning calorimetry(DSC),while its mechanical properties were studied using the nanoindentation *** impedance spectroscopy(EIS),and cyclic voltammetry(CV)were also conducted to study the electrochemical properties of the prepared *** effects of AgNPs,RGO,and water content were all considered in the study of supercapacitor *** microstructural tests showed that the nanocomposite hydrogel has a relatively high swelling rate,which has a crucial effect on the ***,the effects of increasing AgNP concentration and water content in the hydrogel matrix showed a signiﬁcant improvement in its electrochemical performance,compared with that for Arabic gum poly acrylic acid(AGPAA)hydrogel itself,were the speciﬁc capacitance exhibited a signiﬁcant enhancement,convert-ing from a low value to a substantially higher capacitance ***,when the nanocomposite hydrogel was used as the working electrode in an electrochemical cell with a hydrochloric acid

关键词： Supercapacitor energy harvesting nanocomposite hydrogel reduced graphene oxide

The necessity to expand mycorrhizal boundaries:Including the fungal endophytes that possess key mycorrhizal criteria

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Pedosphere 2024年第2期34卷 520-523页

作者： Khalil KARIMAN Zed RENGEL Rodica PENA saleh RAHIMLOU Mark TIBBETT UWA School of Agriculture and Environment The University of Western AustraliaPerth WA 6009Australia Department of Sustainable Land Management&Soil Research Centre School of AgriculturePolicy and DevelopmentUniversity of ReadingReading RG66ARUK Department of Ecology and Evolutionary Biology University of MichiganAnn Arbor MI 48109USA

Dear editor,This letter aims to urge the necessity to expand the boundaries of mycorrhizal symbiosis to include certain root fungal *** conventional classification of mycorrhizal associations emphasizes specialized fu... 详细信息

关键词： editor specialized interface

The Future Trend of E-Mobility in Terms of Battery Electric Vehicles and Their Impact on Climate Change: A Case Study Applied in Hungary

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American Journal of Climate Change 2024年第2期13卷 83-102页

作者： Mohamad Ali saleh saleh Department of Economics and Management Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

The transportation sector is responsible for 25% of the total Carbon dioxide (CO2) emissions, whereas 60.6% of this sector represents small and medium passenger cars. However, as noted by the European Union Long-term strategy, there are two ways to reduce the amount of CO2 emissions in the transportation sector. The first way is characterized by creating more efficient vehicles. In contrast, the second way is characterized by changing the fuel used. The current study addressed the second way, changing the fuel type. The study examined the potential of battery electric vehicles (BEVs) as an alternative fuel type to reduce CO2 emissions in Hungarys transportation sector. The study used secondary data retrieved from Statista and *** to analyze the future trends of BEVs in Hungary. The results showed that the percentage of BEVs in Hungary in 2022 was 0.4% compared to the total number of registered passenger cars, which is 3.8 million. The simple exponential smoothing (SES) time series forecast revealed that the number of BEVs is expected to reach 84,192 in 2030, indicating a percentage increase of 2.21% in the next eight years. The study suggests that increasing the number of BEVs is necessary to address the negative impact of CO2 emissions on society. The Hungarian Ministry of Innovation and Technologys strategy to reduce the cost of BEVs may increase the percentage of BEVs by 10%, resulting in a potential average reduction of 76,957,600 g/km of CO2 compared to gasoline, diesel, hybrid electric vehicles (HEVs), and plug-in hybrid vehicles (PHEVs).

关键词： Battery Electric Vehicles (BEVS) Gasoline Diesel Hybrid Electric Vehicles (HEVs) Plug-In Hybrid Vehicles (PHEVs) Climate Change Carbon Dioxide (CO2) Emissions

Japanese Sign Language Recognition by Combining Joint Skeleton-Based Handcrafted and Pixel-Based Deep Learning Features with Machine Learning Classification

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Computer Modeling in Engineering & Sciences 2024年第6期139卷 2605-2625页

作者： Jungpil Shin Md.Al Mehedi Hasan Abu saleh Musa Miah Kota Suzuki Koki Hirooka School of Computer Science and Engineering The University of AizuAizuwakamatsu965-8580Japan Department of Computer Science&Engineering Rajshahi University of Engineering&TechnologyRajshahi6204Bangladesh

Sign language recognition is vital for enhancing communication accessibility among the Deaf and hard-of-hearing *** Japan,approximately 360,000 individualswith hearing and speech disabilities rely on Japanese Sign Language(JSL)for ***,existing JSL recognition systems have faced significant performance limitations due to inherent *** response to these challenges,we present a novel JSL recognition system that employs a strategic fusion approach,combining joint skeleton-based handcrafted features and pixel-based deep learning *** system incorporates two distinct streams:the first stream extracts crucial handcrafted features,emphasizing the capture of hand and body movements within JSL ***,a deep learning-based transfer learning stream captures hierarchical representations of JSL gestures in the second ***,we concatenated the critical information of the first stream and the hierarchy of the second stream features to produce the multiple levels of the fusion features,aiming to create a comprehensive representation of the JSL *** reducing the dimensionality of the feature,a feature selection approach and a kernel-based support vector machine(SVM)were used for the *** assess the effectiveness of our approach,we conducted extensive experiments on our Lab JSL dataset and a publicly available Arabic sign language(ArSL)*** results unequivocally demonstrate that our fusion approach significantly enhances JSL recognition accuracy and robustness compared to individual feature sets or traditional recognition methods.

关键词： Japanese Sign Language(JSL) hand gesture recognition geometric feature distance feature angle feature GoogleNet

Adaptive Cloud Intrusion Detection System Based on Pruned Exact Linear Time Technique

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Computers, Materials & Continua 2024年第6期79卷 3725-3756页

作者： Widad Elbakri Maheyzah Md.Siraj Bander Ali saleh Al-rimy Sultan Noman Qasem Tawfik Al-Hadhrami Faculty of Computing Universiti Teknologi MalaysiaJohor BahruJohor81310Malaysia Computer Science Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia School of Science and Technology Nottingham Trent UniversityNottinghamNG118NSUK

Cloud computing environments,characterized by dynamic scaling,distributed architectures,and complex work-loads,are increasingly targeted by malicious *** threats encompass unauthorized access,data breaches,denial-of-service attacks,and evolving malware *** security solutions often struggle with the dynamic nature of cloud environments,highlighting the need for robust Adaptive Cloud Intrusion Detection Systems(CIDS).Existing adaptive CIDS solutions,while offering improved detection capabilities,often face limitations such as reliance on approximations for change point detection,hindering their precision in identifying *** can lead to missed attacks or an abundance of false alarms,impacting overall security *** address these challenges,we propose ACIDS(Adaptive Cloud Intrusion Detection System)-*** novel Adaptive CIDS framework leverages the Pruned Exact Linear Time(PELT)algorithm and a Support Vector Machine(SVM)for enhanced accuracy and ***-PELT comprises four key components:(1)Feature Selection:Utilizing a hybrid harmony search algorithm and the symmetrical uncertainty filter(HSO-SU)to identify the most relevant features that effectively differentiate between normal and anomalous network traffic in the cloud environment.(2)Surveillance:Employing the PELT algorithm to detect change points within the network traffic data,enabling the identification of anomalies and potential security threats with improved precision compared to existing approaches.(3)Training Set:Labeled network traffic data forms the training set used to train the SVM classifier to distinguish between normal and anomalous behaviour patterns.(4)Testing Set:The testing set evaluates ACIDS-PELT’s performance by measuring its accuracy,precision,and recall in detecting security threats within the cloud *** evaluate the performance of ACIDS-PELT using the NSL-KDD benchmark *** results demonstrate that ACIDS-PELT outperf

关键词： Adaptive cloud IDS harmony search distributed denial of service(DDoS) PELT machine learning SVM ISOTCID NSL-KDD

TANG TO TODAY:CHINA AND BAHRAIN'S EVOLVING TIES

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Beijing Review 2024年第24期67卷 20-21页

作者： Mohammed saleh China University of Political Science and Law

The relations between China and Bahrain can be traced back to the Tang Dynasty(618-907),with solid evidence supporting the existence of commercial ties between the two *** forward to modern times and formal diplomatic relations between the People's Republic of China and the Kingdom of Bahrain were established on April 18,1989,building on the foundation of centuries-old cultural and commercial exchanges.

关键词： formal supporting foundation

CapsNet-FR: Capsule Networks for Improved Recognition of Facial Features

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Computers, Materials & Continua 2024年第5期79卷 2169-2186页

作者： Mahmood Ul Haq Muhammad Athar Javed Sethi Najib Ben Aoun Ala saleh Alluhaidan Sadique Ahmad Zahid farid Department of Computer System Engineering University of Engineering&TechnologyPeshawar25000Pakistan College of Computer Science and Information Technology Al-Baha UniversityAlaqiq65779-7738Saudi Arabia REGIM-Lab:Research Groups in Intelligent Machines National School of Engineers of Sfax(ENIS)University of SfaxSfax3038Tunisia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia EIAS:Data Science and Blockchain Laboratory College of Computer and Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia Department of Computer Sciences Bahria University Karachi CampusKarachi541004Pakistan Department of Electrical Engineering Abasyn UniversityPeshawar25000Pakistan

Face recognition (FR) technology has numerous applications in artificial intelligence including biometrics, security,authentication, law enforcement, and surveillance. Deep learning (DL) models, notably convolutional neuralnetworks (CNNs), have shown promising results in the field of FR. However CNNs are easily fooled since theydo not encode position and orientation correlations between features. Hinton et al. envisioned Capsule Networksas a more robust design capable of retaining pose information and spatial correlations to recognize objects morelike the brain does. Lower-level capsules hold 8-dimensional vectors of attributes like position, hue, texture, andso on, which are routed to higher-level capsules via a new routing by agreement algorithm. This provides capsulenetworks with viewpoint invariance, which has previously evaded CNNs. This research presents a FR model basedon capsule networks that was tested using the LFW dataset, COMSATS face dataset, and own acquired photos usingcameras measuring 128 × 128 pixels, 40 × 40 pixels, and 30 × 30 pixels. The trained model outperforms state-ofthe-art algorithms, achieving 95.82% test accuracy and performing well on unseen faces that have been blurred orrotated. Additionally, the suggested model outperformed the recently released approaches on the COMSATS facedataset, achieving a high accuracy of 92.47%. Based on the results of this research as well as previous results, capsulenetworks perform better than deeper CNNs on unobserved altered data because of their special equivarianceproperties.

关键词： CapsNet face recognition artificial intelligence