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An Integrated Deep Learning Framework for Fruits Diseases Classification

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Computers, Materials & Continua 2022年第4期71卷 1387-1402页

作者： Abdul majid Muhammad Attique Khan Majed Alhaisoni Muhammad Asfand Eyar Usman Tariq Nazar hussain Yunyoung Nam Seifedine Kadry Department of Computer Science HITEC University TaxilaTaxilaPakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia Department of Computer Science Bahria UniversityIslamabad College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway

:Agriculture has been an important research area in the field of image processing for the last five *** affect the quality and quantity of fruits,thereby disrupting the economy of a *** computerized techniques have been introduced for detecting and recognizing fruit ***,some issues remain to be addressed,such as irrelevant features and the dimensionality of feature vectors,which increase the computational time of the ***,we propose an integrated deep learning framework for classifying fruit *** consider seven types of fruits,i.e.,apple,cherry,blueberry,grapes,peach,citrus,and *** proposed method comprises several important ***,data increase is applied,and then two different types of features are *** the first feature type,texture and color features,i.e.,classical features,are *** the second type,deep learning characteristics are extracted using a pretrained *** pretrained model is reused through transfer ***,both types of features are merged using the maximum mean value of the serial ***,the resulting fused vector is optimized using a harmonic threshold-based genetic ***,the selected features are classified using multiple *** evaluation is performed on the PlantVillage dataset,and an accuracy of 99%is achieved.A comparison with recent techniques indicate the superiority of the proposed method.

关键词： Fruit diseases data augmentation deep learning classical features features fusion features selection

Classification of Nonlinear Confusion Component Using Hybrid Multi-Criteria Decision Making

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Intelligent Automation & Soft Computing 2023年第5期36卷 1451-1463页

作者： Nabilah Abughazalah Iqra Ishaque majid Khan Ammar S.Alanazi Iqtadar hussain Department of Mathematical Sciences College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Applied Mathematics and Statistics Institute of Space TechnologyIslamabadPakistan Department of Mathematics King Abdulaziz UniversityFaculty of ScienceJeddahSaudi Arabia Mathematics Program Department of MathematicsStatistics and PhysicsCollege of Arts and SciencesQatar University2713DohaQatar Statistical Consulting Unit College of Arts and ScienceQatar UniversityDohaQatar

In today’s digital world,the most inevitable challenge is the protection of digital *** to the weak conﬁdentiality preserving techniques,the existing world is facing several digital information *** make our digital data indecipherable to the unauthorized person,a technique forﬁnding a crypto-graphically strong Substitution box(S-box)have *** S-box with sound cryptographic assets such as nonlinearity(NL),strict avalanche criterion(SAC),bit independence criteria(BIC),bit independence criteria of nonlinearity(BIC-NL),Bit independence criteria of Strict avalanche criteria(BIC-SAC),and Input/output XOR is considered as the robust *** Decision-Making Trial and Evaluation Laboratory(DEMATEL)approach of multi-criteria decision making(MCDM)is proposed forﬁnding the interrelation among cryptographic properties.A combination of two MCDM methods namely Entropy and multi-objective optimization based on ratio analysis(MOORA)is applied for the best S-box selection.A robust substitution box is selected for secure communications in cryptography by using the combination of DEMETAL selection criteria,entro-py weight assigning,and MOORA ranking *** combination of these three methods provides a fast selection procedure for the secure confusion *** offered selection method can also be utilized for the choice of the best cryptosystem with highly secure properties and resistive against all possible linear and differential attacks in the cryptanalysis.

关键词： DEMATEL MCDM MOORA nonlinearity S-box

Classification of Positive COVID-19 CT Scans Using Deep Learning

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Computers, Materials & Continua 2021年第3期66卷 2923-2938页

作者： Muhammad Attique Khan Nazar hussain Abdul majid Majed Alhaisoni Syed Ahmad Chan Bukhari Seifedine Kadry Yunyoung Nam Yu-Dong Zhang Department of Computer Science HITEC University TaxilaPakistan College of Computer Science and Engineering University of Ha’ilHa’ilSaudi Arabia Division of Computer Science Mathematics and ScienceCollins College of Professional StudiesSt.’John’s UniversityNew YorkUSA Department of Mathematics and Computer Science Beirut Arab UniversityLebanon Department of Computer Science and Engineering Soonchunhyang UniversityAsanSouth Korea Department of Informatics University of LeicesterLeicesterUK

In medical imaging,computer vision researchers are faced with a variety of features for verifying the authenticity of classifiers for an accurate *** response to the coronavirus 2019(COVID-19)pandemic,new testing procedures,medical treatments,and vaccines are being developed *** potential diagnostic tool is a reverse-transcription polymerase chain reaction(RT-PCR).RT-PCR,typically a time-consuming process,was less sensitive to COVID-19 recognition in the disease’s early *** we introduce an optimized deep learning(DL)scheme to distinguish COVID-19-infected patients from normal patients according to computed tomography(CT)*** the proposed method,contrast enhancement is used to improve the quality of the original images.A pretrained DenseNet-201 DL model is then trained using transfer *** fully connected layers and an average pool are used for feature *** extracted deep features are then optimized with a Firefly algorithm to select the most optimal learning *** the selected features is important to improving the accuracy of the approach;however,it directly affects the computational cost of the *** the proposed method,a new parallel high index technique is used to fuse two optimal vectors;the outcome is then passed on to an extreme learning machine for final *** were conducted on a collected database of patients using a 70:30 training:Testing *** results indicated an average classification accuracy of 94.76%with the proposed approach.A comparison of the outcomes to several other DL models demonstrated the effectiveness of our DL method for classifying COVID-19 based on CT scans.

关键词： Coronavirus contrast enhancement deep learning features optimization fusion classification

Spatial and Temporal Analyses of Water Quality in the Dhrabi Watershed of Pakistan： Issues and Options

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Journal of Environmental Science and Engineering(A) 2012年第3期1卷 329-340页

作者： Muhammad Ashraf Theib Y. Oweis Abdur Razzaq Bashir hussain Abdul majid International Center for Agricultural Research in the Dry Areas （ICARDA） National Agricultural Research Centre lslamabad 44000 Pakistan International Center for Agricultural Research in the Dry Areas （ICARDA） Aleppo 15310 Syria Soil and Water Conservation Research Institute （SA WCRI） Chakwa148800 Pakistan

Monitoring water quality is important for maintaining a healthy watershed, but it is mostly ignored in watershed planning and management. In the Dhrabi watershed of Pakistan, the quality of surface water was monitored at 16 locations to assess suitability for irrigation over regular intervals during the period 2007-2010. Similarly, groundwater quality was monitored at 10 locations for drinking and irrigation purposes. There was high spatial and temporal variability in surface water quality. Electrical conductivity （EC） and residual sodium carbonate （RSC） either exceeded or fluctuated around permissible limits at most of the locations throughout the monitoring period. Therefore, the use of such water for irrigation needs special care, otherwise its prolonged use may pose soil salinity and sodicity problems. The trend of EC and RSC for groundwater was similar to that for surface water. Exchangeable Mg2＋ exceeded permissible limits for most of the surface water and groundwater samples. In addition, microbial analysis of groundwater revealed that only two out of eight monitoring points during August 2009, none out of eight points during February 2010, and one out of nine points during June 2010 provided water fit for drinking. Soil samples were collected from the catchment areas of the major contributing streams and from the beds of the Kallar Kahar Lake and the Dhrabi Reservoir. The soil samples from the catchments showed high salinity and sodicity that may be the cause of high salinity and sodicity in the streams. The highest EC, sodium adsorption ratio （SAP,） and exchangeable sodium percentage （ESP） in the bed samples from the Kallar Kahar Lake were about 43 dS/m, 56, and 45, respectively. These high values were due to the saline water brought into the lake with the runoff.

关键词： Surface water quality groundwater quality drinking water quality wastewater.

Electromagnetic Response Studies of the Antenna for Deep Water Deep Target CSEM Environments

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Journal of Electromagnetic Analysis and Applications 2012年第12期4卷 513-522页

作者： Noorhana Yahya Nadeem Nasir majid Niaz Akhtar Muhammad Kashif Tanvir hussain Hasnah Mohd Zaid Afza Shafie Electrical and Electronic Engineering Department Tronoh Malayia Electrical and Electronic Engineering Department Tronoh Malayia 3Fundamental and Applied Science Department National Textile University Faisalabad Pakistan Fundamental and Applied Science Department Tronoh Malayia Fundamental and Applied Science Department Tronoh Malayia 2Electrical and Electronic Engineering Department Tronoh Malayia Mechanical Engineering Department Universiti Teknologi PETRONAS Tronoh Malaysia.

The Controlled Source Electromagnetic Method (CSEM) is used for offshore hydrocarbon exploration. Hydrocarbon detection in seabed logging (SBL) is a very challenging task for deep hydrocarbon reservoirs. The electromagnetic field response of an antenna is unable to detect deep hydrocarbon reservoirs due to a weak electromagnetic signal response in the seabed logging environment. This work premise deals with the comparison of the electromagnetic signal strength of a new antenna with a straight antenna and the orientation of an antenna for deep target hydrocarbon exploration. Antenna position and orientation (Tx and Ty) was studied using Computer Simulation Technology software (CST) for deep targets in marine CSEM environments. The model area was assigned as (40 ′ 40 km) to replicate the real seabed environment. From the results, the new dipole antenna shows an 804% and 278% increase in electric and magnetic field strength than the straight antenna. An electric (E) and magnetic (H) field component study was done with and without the presence of a hydrocarbon reservoir. Ex and Hz field component responses with the new antenna at the1 kmtarget were measured in a deep water environment. It was analyzed that the antenna shows 53.10% (Ex) and 83.13% (Hz) field difference in deep water with and without a hydrocarbon reservoir at the30 mantenna position from the sea floor. From the antenna orientation results, it was observed that, the electric field Ex and magnetic field Hz responses decreased from 18% to 12% and 21% to 16%, respectively but was still able to detect the deep target hydrocarbon reservoir at the4 kmtarget depth. This EM antenna may open new frontiers for the oil and gas industry for deep target hydrocarbon detection (HC).

关键词： Control Source Electromagnetic (CSEM) Seabed Logging (SBL) Antenna Computer Simulation Technology (CST) Hydrocarbon (HC)

The Relevant Roles of Plastic and Orthopedic Surgery in Hand Salvage

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Modern Plastic Surgery 2018年第2期8卷 29-43页

作者： Bassam Ahmed Almutlaq Mohammad M. Al-Qattan majid Zannon Alturkstani Rakan Fraih Almuazzi Abdulkarim Saleh Alkhateeb Ayman Talla Talla Muqbil Sayer Alshammari hussain Gadelkarim Ahmed College of Medicine University of Hail Hail KSA Division of Plastic Surgery Head of Research Centre College of Medicine King Saud University Riyadh KSA Batterjee Medical College Jeddah Saudi Arabia

Over the recent past few years, there is a huge innovation in plastic surgery and orthopedic surgery through implantation of new techniques, which enabled a great level of success in hand salvage. Conditions such as trauma, tumor, sepsis, or vascular disease, may necessitate hand salvage. The most frequent argument among surgeon from different subspecialties (orthopedics, plastics, trauma, and vascular surgery) are characterized by in what way each one can do his own part of the salvage operation, be it bony fixation, revascularization, or soft-tissue coverage, but none of them is sure whether it should be endeavored. What is necessary in such clinical situations is an interdisciplinary team attitude led by individual or groups of clinicians who are conversant not only with their identifiable subspecialized skills but also with those of their coworkers and the consequences accompanying the joined efforts at hand salvage. The perception of orthoplastic surgery is based on such an indication, where the integrated skills and techniques of the orthopedic surgeon and reconstructive microsurgeon are performed in recital to direct efforts concerning hand salvage or choose against it when it is not designated. The current article reviews the roles of orthopedic and plastic surgery and how this team can deal with the existing techniques to improve outcomes in hand salvage surgery.

关键词： Hand Salvage Plastic Surgery Orthopedic Surgery Hand Transplantation Prosthetic Fitting

多器官床旁即时超声在新型冠状病毒肺炎中的应用:国际专家共识

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中国呼吸与危重监护杂志 2021年第2期20卷 77-84页

作者：王臻(译) Arif hussain Gabriele Via Lawrence Melniker Alberto Goffi Guido Tavazzi Luca Neri Tomas Villen Richard Hoppmann Francesco Mojoli Vicki Noble Laurent Zieleskiewicz Pablo Blanco Irene W.Y.Ma Mahathar Abd.Wahab Abdulmohsen Alsaawi majid AI Salamah Martin Balik Diego Barca Karim Bendjelid Belaid Bouhemad Pablo Bravo-Figueroa Raoul Breitkreutz Juan Calderon Jim Connolly Roberto Copetti Francesco Corradi Anthony J.Dean AndréDenault Deepak Govil Carmela Graci Young-Rock Ha Laura Hurtado Toru Kameda Michael Lanspa Christian B Laursen Francis Lee Rachel Liu Massimiliano Meineri Miguel Montorfano Peiman Nazerian Bret P.Nelson Aleksandar N.Neskovic Ramon Nogue Adi Osman JoséPazeli Elmo Pereira-Junior Tomislav Petrovic Emanuele Pivetta Jan Poelaert Susanna Price Gregor Prosen Shalim Rodriguez Philippe Rola Colin Royse Yale Tung Chen Mike Wells Adrian Wong Wang Xiaoting Wang Zhen Yaseen Arabi 中国人民解放军空军军医大学航空航天医学系陕西西安710032 Department of Cardiac Sciences King Abdulaziz Medical City and King Abdullah International Medical Research Center 不详

新型冠状病毒肺炎(简称新冠肺炎,COVID-19)自首次报道以来,已造成全球超一亿人感染,给各国的公共卫生体系造成了巨大威胁。新冠肺炎的临床表现以呼吸系统体征和症状为主,80%的患者症状轻微,约5%为危重症患者,常表现为急性呼吸窘迫综合征... 详细信息

新型冠状病毒肺炎(简称新冠肺炎,COVID-19)自首次报道以来,已造成全球超一亿人感染,给各国的公共卫生体系造成了巨大威胁。新冠肺炎的临床表现以呼吸系统体征和症状为主,80%的患者症状轻微,约5%为危重症患者,常表现为急性呼吸窘迫综合征(ARDS)。前期,由于缺乏相关研究,面对日益紧迫的临床困境,医务人员不得不借鉴采取一些经验性措施以应对疫情。

关键词：体征和症状肺炎公共卫生体系呼吸系统首次报道专家共识疫情