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Identifcation of large-scale goaf instability in underground mine using particle swarm optimization and support vector machine

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International Journal of Mining Science and Technology 2013年第5期23卷 701-707页

作者： Zhou Jian Li Xibing hani S.Mitri Wang Shiming Wei Wei School of Resources and Safety Engineering Central South University Hunan Key Lab of Resources Exploitation and Hazard Control for Deep Metal Mines Department of Mining and Materials Engineering McGill University

An approach which combines particle swarm optimization and support vector machine(PSO–SVM)is proposed to forecast large-scale goaf instability(LSGI).Firstly,influencing factors of goaf safety are analyzed,and following parameters were selected as evaluation indexes in the LSGI:uniaxial compressive strength(UCS)of rock,elastic modulus(E)of rock,rock quality designation(RQD),area ration of pillar(Sp),the ratio of width to height of the pillar(w/h),depth of ore body(H),volume of goaf(V),dip of ore body(a)and area of goaf(Sg).Then LSGI forecasting model by PSO-SVM was established according to the influencing *** performance of hybrid model(PSO+SVM=PSO–SVM)has been compared with the grid search method of support vector machine(GSM–SVM)*** actual data of 40 goafs are applied to research the forecasting ability of the proposed method,and two cases of underground mine are also validated by the proposed *** results indicated that the heuristic algorithm of PSO can speed up the SVM parameter optimization search,and the predictive ability of the PSO–SVM model with the RBF kernel function is acceptable and robust,which might hold a high potential to become a useful tool in goaf risky prediction research.

关键词： Goaf Risk identifcation Underground mine Prediction Particle swarm optimization Support vector machine

Antimicrobial properties of dental cements modified with zein-coated magnesium oxide nanoparticles

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Bioactive Materials 2022年第2期7卷 49-56页

作者： Ghada H.Naguib hani M.Nassar Mohamed T.Hamed Department of Restorative Dentistry Faculty of DentistryKing Abdulaziz UniversityJeddahSaudi Arabia Department of Oral Biology Faculty of DentistryCairo UniversityCairoEgypt Department of Oral and Maxillofacial Prosthodontics King Abdulaziz UniversityFaculty of DentistryJeddahSaudi Arabia Department of Fixed Prosthodontics Faculty of DentistryCairo UniversityCairoEgypt

The aim of this study was to test the antimicrobial properties of dental cements modified with magnesium oxide(MgO)***-modified MgO nanoparticles(zMgO)in concentrations(0.0,0.3,0.5,and 1.0%)were mixed with dental cements(Fuji II,Rely X Temp E,Ionoglass Cem,Es Temp NE,and System P link).Eight discs were fabricated from each zMgO-cement pair for a total of 32 specimens for each *** of the dental cements incorporating zMgO was done by X-ray Diffraction(XRD)and Field Emission Scanning Electron Microscopy(FESEM).The antimicrobial properties of the mixtures were tested using direct contact and agar diffusion assays against Streptococcus mutans,Staphylococcus aureus,Enterococcus faecalis,and Candida *** was analyzed using two-way analysis of variance and LSD post hoc test at 0.05 significance *** spectra showed sharp peaks of zMgO indicating its high crystalline nature,while the amorphous dental cements with zMgO had broad *** analysis showed a uniform distribution of the zMgO nanoparticles in the *** were significant inhibition zone values associated with all concentrations of zMgO-cement mixtures tested compared to controls(p<0.001)with a dose-response recorded only with Fuji *** density values were significantly lower in zMgO groups compared to controls for all *** effect was most prominent with Rely X against *** and *** cements containing zMgO showed significant antimicrobial properties that were dependent on the specific initial cement substrate.

关键词： Magnesium oxide nanoparticles Antimicrobial biomaterials Dental cement Nanocoatings

The Relationship between Time Pressure and Burnout Syndrome: A Cross-Sectional Survey among Jordanian Nurses

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Health 2015年第1期7卷 14-22页

作者： Muhammad W. Darawad hani Nawafleh Mahmoud Maharmeh Ayman M. Hamdan-mansour Saleh N. Azzeghaiby Faculty of Nursing The University of Jordan Amman Jordan Faculty of Nursing Al-Hussein Bin Talal University Maan Jordan Al-Farabi College for Dentistry and Nursing Al-Farabi College Riyadh KSA

Burnout among nurses is well documented in literature. Precursors of burnout such as time pressure need further study for better understanding. In Jordan literature, studies regarding time pressure and burnout among Jordanian nurses are scarce. This study aimed to 1) evaluate the relationship between time pressure and burnout, and 2) identify participants’ characteristics that may have relationship with time pressure and burnout. A descriptive correlational design was utilized using a self-reported cross-sectional survey to collect data from 175 Jordanian nurses. Participants reported high level of time pressure (24.8 out of 126) and burnout (72.9 out of 126). Time pressure was correlated with emotional exhaustion and depersonalization (r = 0.561, 0.491, P < 0.01, respectively). Burnout was highest on the emotional exhaustion (72%) compared to 53.9% for depersonalization and 49.2% for personal achievement. Depersonalization showed the most frequent correlation with participants’ characteristics. Burnout was found to be common among Jordanian nurses, and time pressure is a precursor of this phenomenon, giving rise to the consequences on both patients’ and nurses’ health. Healthcare administrators have to modify the nursing work environment to be less stressful and more appealing to overcome the causes of nurses’ burnout.

关键词： Time Pressure Burnout Work Environment Nurses Jordan

Encryption with Image Steganography Based Data Hiding Technique in IIoT Environment

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Computers, Materials & Continua 2022年第7期72卷 1323-1338页

作者： Mahmoud Ragab Samah Alshehri hani A.Alhadrami Faris Kateb Ehab Bahaudien Ashary SAbdel-khalek Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Centre of Artificial Intelligence for Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Department of Pharmacy Practice Faculty of PharmacyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Medical Laboratory Technology Faculty of Applied Medical SciencesKing Abdulaziz UniversityJeddah21589Saudi Arabia Molecular Diagnostic Lab King Abdulaziz University HospitalKing Abdulaziz UniversityJeddah21589Saudi Arabia Special Infectious Agent Unit King Fahd Medical Research CenterKing Abdulaziz UniversityJeddah21589Saudi Arabia Electrical and Computer Engineering Department Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceTaif UniversityTaif21944Saudi Arabia Department of Mathematics Faculty of ScienceSohag UniversitySohag82524Egypt

Rapid advancements of the Industrial Internet of Things(IIoT)and artificial intelligence(AI)pose serious security issues by revealing secret ***,security data becomes a crucial issue in IIoT communication where secrecy needs to be guaranteed in real ***,AI techniques can be utilized to design image steganographic techniques in *** addition,encryption techniques act as an important role to save the actual information generated from the IIoT devices to avoid unauthorized *** order to accomplish secure data transmission in IIoT environment,this study presents novel encryption with image steganography based data hiding technique(EISDHT)for IIoT *** proposed EIS-DHT technique involves a new quantum black widow optimization(QBWO)to competently choose the pixel values for hiding secrete data in the cover *** addition,the multi-level discrete wavelet transform(DWT)based transformation process takes ***,the secret image is divided into three R,G,and B bands which are then individually encrypted using Blowfish,Twofish,and Lorenz Hyperchaotic *** last,the stego image gets generated by placing the encrypted images into the optimum pixel locations of the cover *** order to validate the enhanced data hiding performance of the EIS-DHT technique,a set of simulation analyses take place and the results are inspected interms of different *** experimental outcomes stated the supremacy of the EIS-DHT technique over the other existing techniques and ensure maximum security.

关键词： IIoT security data hiding technique image steganography encryption secure communication

Enhancing Bandwidth Utilization of IP Telephony Over IPv6 Networks

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Computer Systems Science & Engineering 2023年第2期44卷 1039-1049页

作者： hani Al-Mimi Yousef Alrabanah Mosleh M.Abualhaj Sumaya N.Al-khatib Al-Zaytooanh University of Jordan Faculty of Science and Information TechnologyDepartment of CybersecurityAmman11733Jordan Al-Ahliyya Amman University Faculty of Information TechnologyDepartment of Software EngineeringAmman19328Jordan Al-Ahliyya Amman University Faculty of Information TechnologyDepartment of Networks and Information SecurityAmman19328Jordan

The demand for the telecommunication services,such as IP telephony,has increased dramatically during the COVID-19 pandemic *** tele-phony should be enhanced to provide the expected *** of the issues that should be investigated in IP telephony is bandwidth *** telephony pro-duces very small speech samples attached to a large packet *** header of the IP telephony consumes a considerable share of the bandwidth allotted to the IP *** wastes the network's bandwidth and inﬂuences the IP telephony *** paper proposes a mechanism(called Smallerize)that reduces the bandwidth consumed by both the speech sample and the *** is achieved by assembling numerous IP telephony packets in one header and use the header'sﬁelds to carry the speech *** metrics have been used to measure the achievement Smallerize *** number of calls has been increased by 245.1%compared to the typical *** bandwidth saving has also reached 68%with the G.28 ***,Smallerize is a possible mechanism to enhance bandwidth utilization of the IP telephony.

关键词： –IP telephony codec bandwidth utilization IPv6

Optimal Deep Transfer Learning Based Colorectal Cancer Detection and Classification Model

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Computers, Materials & Continua 2023年第2期74卷 3279-3295页

作者： Mahmoud Ragab Maged Mostafa Mahmoud Amer H.Asseri hani Choudhry Haitham A.Yacoub Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Center for Artificial Intelligence in Precision Medicines King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser City11884CairoEgypt Cancer Biology Unit King Fahd Medical Research CenterKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Medical Laboratory Sciences Faculty of Applied Medical SciencesKing Abdulaziz UniversityJeddah22252Saudi Arabia Department of Molecular Genetics and Enzymology Human Genetics and Genome Research InstituteNational Research CentreCairo12622Egypt Biochemistry Department Faculty of ScienceKing Abdulaziz UniversityJeddah21589Saudi Arabia Cell Biology Department Biotechnology Research InstituteNational Research CentreGiza12622Egypt

Colorectal carcinoma(CRC)is one such dispersed cancer globally and also prominent one in causing cancer-based ***,pathologists execute CRC diagnosis through visible scrutinizing under the microscope the resected tissue samples,stained and fixed through Haematoxylin and Eosin(H&E).The advancement of graphical processing systems has resulted in high potentiality for deep learning(DL)techniques in interpretating visual anatomy from high resolution medical *** study develops a slime mould algorithm with deep transfer learning enabled colorectal cancer detection and classification(SMADTL-CCDC)*** presented SMADTL-CCDC technique intends to appropriately recognize the occurrence of colorectal *** accomplish this,the SMADTLCCDC model initially undergoes pre-processing to improve the input image *** addition,a dense-EfficientNet technique was employed to extract feature vectors from the pre-processed ***,SMA with Discrete Hopfield neural network(DHNN)method was applied for the recognition and classification of colorectal *** utilization of SMA assists in appropriately selecting the parameters involved in the DHNN approach.A wide range of experiments was implemented on benchmark datasets to assess the classification performance.A comprehensive comparative study highlighted the better performance of the SMADTL-CDC model over the recent approaches.

关键词： Colorectal cancer deep transfer learning slime mould algorithm hyperparameter optimization biomedical imaging

Electric Vehicles Lithium-Polymer Ion Battery Dynamic Behaviour Charging Identification and Modelling Scheme

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Journal of Dynamics, Monitoring and Diagnostics 2023年第3期2卷 170-176页

作者： Peter Makeen hani AGhali Saim Memon Fang Duan Electrical Engineering Department Faculty of EngineeringThe British University in Egypt(BUE)El-Sherouk11837 Egypt London Centre for Energy Engineering Division of Electrical and Electronic EngineeringSchool of EngineeringLondon South Bank UniversityLondonSE10AA UK School of Engineering Arden UniversityCoventryCV34FJ UK Jiangsu Sanyou Dior Energy-Saving New Materials Co. Ltd(SANYOU DIOR)ChangzhouJiangsu 213149China Department for Engineering School of Engineering and the Built EnvironmentBirmingham City UniversityBirmingham B47XG UK

Lithium-ion batteries are considered the substantial electrical storage element for electric vehicles(EVs). The battery model is the basis of battery monitoring, efficient charging, and safety management. Non-linearmodelling is the key to representing the battery and its dynamic internal parameters and performance. This paperproposes a smart scheme to model the lithium-polymer ion battery while monitoring its present charging currentand terminal voltage at various ambient conditions (temperature and relative humidity). Firstly, the suggestedframework investigated the impact of temperature and relative humidity on the charging process using the constantcurrent-constant voltage (CC-CV) charging protocol. This will be followed by monitoring the battery at thesurrounding operating temperature and relative humidity. Hence, efficient non-linear modelling of the EV batterydynamic behaviour using the Hammerstein-Wiener (H-W) model is implemented. The H-W model is considered ablack box model that can represent the battery without any mathematical equivalent circuit model which reducesthe computation complexity. Finally, the model beholds the boundaries of the charging process, not affecting onthe lifetime of the battery. Several dynamic models are applied and tested experimentally to ensure theeffectiveness of the proposed scheme under various ambient conditions where the temperature is fixed at40°C and the relative humidity (RH) at 35%, 52%, and 70%. The best fit using the H-W model reached 91.83% todescribe the dynamic behaviour of the battery with a maximum percentage of error 0.1 V which is in goodagreement with the literature survey. Besides, the model has been scaled up to represent a real EV and expressedthe significance of the proposed H-W model.

关键词： battery identification electric vehicles EV fast charging Hammerstein-Wiener Lithium-polymer ion battery

Fruits and Vegetables Freshness Categorization Using Deep Learning

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Computers, Materials & Continua 2022年第6期71卷 5083-5098页

作者： Labiba Gillani Fahad Syed Fahad Tahir Usama Rasheed Hafsa Saqib Mehdi Hassan hani Alquhayz Department of Computer Science National University of Computer and Emerging SciencesIslamabad44000Pakistan Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Information College of Science in ZulfiMajmaah UniversityAl-Majmaah11952Kingdom of Saudi Arabia

The nutritional value of perishable food items,such as fruits and vegetables,depends on their freshness *** existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten *** propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories:purefresh,medium-fresh,and *** gathered a dataset comprising of 60K images of 11 fruits and vegetables,each is further divided into three categories of freshness,using hand-held *** recognition and categorization of fruits and vegetables are performed through two deep learning models:Visual Geometry Group(VGG-16)and You Only Look Once(YOLO),and their results are ***-16 classifies fruits and vegetables and categorizes their freshness,while YOLO also localizes them within the ***,we have developed an android based application that takes the image of the fruit or vegetable as input and returns its class label and its freshness degree.A comprehensive experimental evaluation of proposed approach demonstrates that the proposed approach can achieve a high accuracy and F1score on gathered FruitVeg Freshness *** dataset is publicly available for further evaluation by the research community.

关键词： Fruits and vegetables classification degree of freshness deep learning object detection model VGG-16 YOLO-v5

A pediatric robotic thumb exoskeleton for at-home rehabilitation The isolated orthosis for thumb actuation(IOTA)

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International Journal of Intelligent Computing and Cybernetics 2014年第3期7卷 233-252页

作者： Patrick Aubin Kelsey Petersen hani Sallum Conor Walsh Annette Correia Leia Stirling Rehabilitation and Development Center of Excellence for Limb Loss Prevention and Prosthetic Engineering VA Puget Sound Health Care SystemSeattleWashingtonUSA Wyss Institute for Biologically Inspired Engineering Harvard UniversityBostonMassachusettsUSA Boston Children’s Hospital BostonMassachusettsUSA Wyss Institute for Biologically Inspired Engineering Harvard UniversityBostonMassachusettsUSA and Massachusetts Institute of TechnologyCambridgeMassachusettsUSA

Purpose–Pediatric disorders,such as cerebral palsy and stroke,can result in thumb-in-palm deformity greatly limiting hand *** not only limits children’s ability to perform activities of daily living but also limits important motor skill ***,the isolated orthosis for thumb actuation(IOTA)is 2 degrees of freedom(DOF)thumb exoskeleton that can actuate the carpometacarpal(CMC)and metacarpophalangeal(MCP)joints through ranges of motion required for activities of daily *** paper aims to discuss these ***/methodology/approach–IOTA consists of a lightweight hand-mounted mechanism that can be secured and aligned to individual *** mechanism is actuated via flexible cables that connect to a portable control *** encoders and bend sensors monitor the 2 DOF of the thumb and flexion/extension of the wrist.A linear force characterization was performed to test the mechanical efficiency of the cable-drive transmission and the output torque at the exoskeletal CMC and MCP joints was ***–Using this platform,a number of control modes can be implemented that will enable the device to be controlled by a patient to assist with opposition grasp and fine motor *** force and torque studies showed a maximum efficiency of 44 percent,resulting in a torque of 2.3971.06 in.-lbf and 0.6970.31 in.-lbf at the CMC and MCP joints,*** implications–The authors envision this at-home device augmenting the current in-clinic and at-home therapy,enabling telerehabilitation ***/value–This paper presents the design and characterization of a novel device specifically designed for pediatric grasp telerehabilitation to facilitate improved functionality and somatosensory learning。

关键词： Pediatric Exoskeleton At-home hand rehabilitation Rehabilitation robotics Thumb