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Research 2024年第2期2024卷 55-79页

作者： Yang Yang Lee Zaini ab.ul Halim mohd Nadhir ab wahab Tarik Adnan Almohamad School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal 14300 Penang Malaysia School of Computer Sciences Universiti Sains MalaysiaGelugor11800 PenangMalaysia Electrical-Electronics Engineering Department Faculty of EngineeringKarabuk University78050 KarabukTurkiye

Stochastic computing(SC)has a substantial amount of study on application-specific integrated circuit(ASIC)design for artificial intelligence(AI)edge computing,especially the convolutional neural network(CNN)***,SC has little to no optimization on field-programmable gate array(FPGA).Scaling up the ASIC logic without FPGA-oriented designs is inefficient,while aggregating thousands of bitstreams is still challenging in the conventional *** research has reinvented several FPGA-efficient 8-bit SC CNN computing architectures,i.e.,SC multiplexer multiply-accumulate,multiply-accumulate function generator,and binary rectified linear unit,and successfully scaled and implemented a fully parallel CNN model on Kintex7 *** proposed SC hardware only compromises 0.14%accuracy compared to binary computing on the handwriting modified National Institute of Standards and Technology classification task and achieved at least 99.72%energy saving per image feedforward and 31?more data throughput than modern *** to SC,early decision termination pushed the performance baseline exponentially with minimum accuracy loss,making SC CNN extremely lucrative for AI edge computing but limited to classification *** SC's inherent noise heavily penalizes CNN regression performance,rendering SC unsuitable for regression tasks.

关键词： hardware Highly rendering

Synergistic Interactions of Soil and Vegetation in Agroforestry Systems in mitigating Climate Change in Upper East Region, Ghana

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American Journal of Climate Change 2024年第2期13卷 140-162页

作者： Joshua A. Adombire ab.ul-wahab m. imoro Eunice Essel Nang B. Douti Department of Environmental Science C. K. Tedam University of Technology and Applied Sciences Navrongo Ghana Department of Forestry and Forest Resources management University for Development Studies Tamale Ghana Department of Crop Science and Biotechnology C. K. Tedam University of Technology and Applied Sciences Navrongo Ghana

Climate change has been a global pandemic with its adverse impacts affecting environments and livelihoods. This has been largely attributed to anthropogenic activities which generate large amounts of Green House Gases (GHGs), notably carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) among others. In the Upper East of Ghana, climate change manifests in erratic rainfalls, drought, high temperatures, high wind speeds, high intensity rainfall, windstorms, flooding, declining vegetation cover, perennial devastating bushfires etc. Practices such as burning farm residues, use of dung as fuel for cooking, excessive application of nitrogenous fertilizers, and deforestation that are prevalent in the region exacerbate the situation. Although, efforts made by governmental and none-governmental organizations to mitigate climate change through afforestation, agroforestry and promotion of less fuelwood consuming cook stoves, land management practices antagonize these efforts as more CO2 is generated than the carrying capacity of vegetation in the region. Research findings have established the role of trees and soil in carbon sequestration in mitigating climate. However, there is limited knowledge on how the vegetation and soil in agroforestry interplay in mitigation climate change. It is against this background that this review seeks to investigate how vegetation and soil in an agroforestry interact synergistically to sequester carbon and contribute to mitigating climate change in Upper East region of Ghana. In this review, it was discovered soil stored more carbon than vegetation in an agroforestry system and is much effective in mitigating climate change. It was found out that in order to make soil and vegetation in an agroforestry system interact synergistically to effectively mitigate climate change, Climate Smart Agriculture practice which integrates trees, and perennials crops effectively mitigates climate. The review concluded that tillage practices that ensure r

关键词： Climate Change Carbon Sequestration Agroforestry Photosynthesis Nutrient mining Synergistic

Bilateral adrenal histoplasmosis in a malaysian tertiary hospital:Report of four cases

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Asian Pacific Journal of Tropical medicine 2024年第2期17卷 91-94页

作者： Kang WH Norasyikin ab.ul wahab Department of medicine Faculty of Medicine and Health SciencesUniversity Tunku Abdul RahmanMalaysia Department of medicine Pusat Perubatan Universiti KebangsaanMalaysia

Rationale:Adrenal histoplasmosis can present as bilateral adrenal enlargement with constitutional symptoms and/or adrenal *** these patients are initially investigated as secondary adrenal metastases before eventually their diagnosis established by histopathological examination of the adrenal *** concerns:We report 4 cases of patients aged 55-78 who presented with hypocortisolism and bilateral adrenal ***:Bilateral adrenal ***:Three patients received antifungal treatment for at least one year while 1 patient passed away before the initiation of antifungal ***:Two patients’adrenal function recovered not requiring any steroid replacement,while 1 patient still requires long-term steroid ***:Adrenal histoplasmosis should be excluded in patients from endemic areas presenting with bilateral adrenal masses and adrenal *** patients have an exposure to bird droppings,bat guano or soil contaminated with histoplasmosis *** examination of biopsied adrenal tissues is still the gold standard investigation as serology and molecular diagnostic methods are still not widely available in most centers in malaysia.

关键词： Adrenal histoplasmosis Histoplasmosis Bilateral adrenal masses

Adaptable and Dynamic Access Control Decision-Enforcement Approach Based on multilayer Hybrid Deep Learning Techniques in BYOD Environment

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Computers, materials & Continua 2024年第9期80卷 4663-4686页

作者： Aljuaid Turkea Ayedh m Ainuddin Wahid ab.ul wahab mohd Yamani Idna Idris Faculty of Computer Science and Information Technology Universiti MalayaKuala Lumpur50603Malaysia Faculty of Computer Science and Information Technology Shaqra UniversityShaqra11961Saudi Arabia Center for mobile Cloud Computing Faculty of Computer Science and Information TechnologyUniversiti MalayaKuala Lumpur50603Malaysia

Organizations are adopting the Bring Your Own Device(BYOD)concept to enhance productivity and reduce ***,this trend introduces security challenges,such as unauthorized *** access control systems,such as Attribute-Based Access Control(abAC)and Role-Based Access Control(RBAC),are limited in their ability to enforce access decisions due to the variability and dynamism of attributes related to users and *** paper proposes a method for enforcing access decisions that is adaptable and dynamic,based on multilayer hybrid deep learning techniques,particularly the Tabular Deep Neural Network Tabular DNN *** technique transforms all input attributes in an access request into a binary classification(allow or deny)using multiple layers,ensuring accurate and efficient access *** proposed solution was evaluated using the Kaggle Amazon access control policy dataset and demonstrated its effectiveness by achieving a 94%accuracy ***,the proposed solution enhances the implementation of access decisions based on a variety of resource and user attributes while ensuring privacy through indirect communication with the Policy Administration Point(PAP).This solution significantly improves the flexibility of access control systems,making themmore dynamic and adaptable to the evolving needs ofmodern ***,it offers a scalable approach to manage the complexities associated with the BYOD environment,providing a robust framework for secure and efficient access management.

关键词： BYOD security access control access control decision-enforcement deep learning neural network techniques TabularDNN multilayer dynamic adaptable flexibility bottlenecks performance policy conflict

Growth, Development and Yield of Kenaf as Affected by Planting Dates and N Fertilization

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Open Journal of Applied Sciences 2024年第3期14卷 707-720页

作者： Julius Yirzagla Peter Quandahor Iddrisu Yahaya Olivia Aguriboba Akanbelum Listowell Aditwin Akologo John Bokaligidi Lambon ab.ul-wahab m. imoro Kwadwo Gyasi Santo CSIR-SARI Nyankpala Ghana St Vincent College of Education Yendi Ghana Gbewaah College of Education Pusiga-Bawku Ghana CSIR-Head Office Accra Ghana C.K. Tedam University of Technology and Applied Sciences Navrongo Ghana University of Energy and Natural Resources Sunyani Ghana

Kenaf (Hibiscus cannabinus L) consists of various beneficial components like stalks, seeds, leaves, fibers, oils, proteins, allelopathic chemicals, and fiber strands, among other things. Despite the numerous uses of the crop, there is little or no information on optimum agronomic practices such as planting date and N fertilization of the crop in the Upper East Region (UER) of Ghana where the crop is widely cultivated by smallholder farmers. Field experiments were therefore carried out in 2020 and repeated during the 2021 cropping season in the study area. The objective of the study was to determine appropriate planting date and N fertilization for increased kenaf productivity. In each year, the treatments consisted of 3 × 5 factorial combinations of three planting dates (1st July, 7th July and 14th July) and five levels of N (0, 20, 40, 60 and 80 kg/ha) replicated three times. The design of the experiment was a split-plot with the N fertilizer as the main plot and the planting date assigned to sub plot. The results showed that, planting kenaf in early (1st) July or N fertilization at the rate of 60 kg/ha increased plant density, stem height, stem diameter, dry bast and core yields in both cropping seasons.

关键词： Growth Fibres Bast Yield Core Yield

Identification of Software Bugs by Analyzing Natural Language-Based Requirements Using Optimized Deep Learning Features

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Computers, materials & Continua 2024年第3期78卷 4379-4397页

作者： Qazi mazhar ul Haq Fahim Arif Khursheed Aurangzeb Noor ul Ain Javed Ali Khan Saddaf Rubab muhammad Shahid Anwar Department of Computer Science and Engineering and International Bachelor’s Program in Informatics Yuan Ze UniversityZhongliTaoyuan320315Taiwan Department of Computer Science National University of PakistanRawalpindiPunjab46000Pakistan Department of Computer Software Engineering MCSNational University of Sciences and TechnologyIslamabad44000Pakistan Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia Department of Computer Science School of PhysicsEngineering and Computer ScienceUniversity of HertfordshireHatfieldAL109ABUK Department of Computer Engineering College of Computing and InformaticsUniversity of SharjahSharjah27272United Arab Emirates Department of AI and Software Gachon UniversitySeongnam-SI13120South Korea

Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty *** are exploring machine learning to predict software bugs,but a more precise and general approach is *** bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning ***,these studies are not generalized and efficient when extended to other ***,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification *** methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a *** National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were *** reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.

关键词： Natural language processing software bug prediction transfer learning ensemble learning feature selection

From seawater to hydrogen via direct photocatalytic vapor splitting: A review on device design and system integration

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Frontiers in Energy 2024年第3期18卷 291-307页

作者： Hongxia LI Khaja wahab AHmED mohamed A.abDELSALAm michael FOWLER Xiao-Yu WU Technology Innovation Institute Masdar CityAbu Dhabi 9639United Arab Emirates Department of Chemical Engineering University of WaterlooWaterlooON N2L 3G1Canada Department of mechanical and Nuclear Engineering Khalifa University of Science and TechnologyAbu Dhabi 127788United Arab Emirates Department of mechanical and mechatronics Engineering University of WaterlooWaterlooON N2L 3G1Canada

Solar-driven hydrogen production from seawater attracts great interest for its emerging role in decarbonizing global energy consumption. Given the complexity of natural seawater content, photocatalytic vapor splitting offers a low-cost and safe solution, but with a very low solar-to-hydrogen conversion efficiency. With a focus on cutting-edge photothermal–photocatalytic device design and system integration, the recent research advances on vapor splitting from seawater, as well as industrial implementations in the past decades were reviewed. In addition, the design strategies of the key processes were reviewed, including vapor temperature and pressure control during solar thermal vapor generation from seawater, capillary-fed vaporization with salt repellent, and direct photocatalytic vapor splitting for hydrogen production. moreover, the existing laboratory-scale and industrial-scale systems, and the integration principles and remaining challenges in the future seawater-to-hydrogen technology were discussed.

关键词： seawater hydrogen photocatalytic vapor splitting solar-driven

Robust design of sliding mode control for airship trajectory tracking with uncertainty and disturbance estimation

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Journal of Systems Engineering and Electronics 2024年第1期35卷 242-258页

作者： WASIm muhammad ALI Ahsan CHOUDHRY mohammad Ahmad SHAIKH Inam ul Hasan SALEEm Faisal Department of Aeronautics and Astronautics Engineering Institute of Space TechnologyIslamabad 44000Pakistan Department of Electrical Engineering University of Engineering and TechnologyTaxila 47080Pakistan Department of measurements and Control Systems Silesian University of TechnologyGliwice 44-101Poland The Joint Doctoral School Silesian University of TechnologyGliwice 44-100Poland

The robotic airship can provide a promising aerostatic platform for many potential *** applications require a precise autonomous trajectory tracking control for *** has a nonlinear and uncertain *** is prone to wind disturbances that offer a challenge for a trajectory tracking control *** paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed *** uses extended Kalman filter(EKF)for uncertainty and disturbance *** estimated parameters are used by sliding mode controller(SmC)for ultimate control of airship trajectory *** comprehensive algorithm,EKF based SmC(ESmC),is used as a robust solution to track airship *** proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model *** stability and convergence of the proposed method are investigated using the Lyapunov stability *** simulation results show that the proposed method efficiently tracks the desired *** method solves the stability,convergence,and chattering problem of SmC under model uncertainties and wind disturbances.

关键词： airship chattering extended Kalman filter(EKF) model uncertainties estimation sliding mode controller(SmC)

Enhancing IoT Data Security with Lightweight Blockchain and Okamoto Uchiyama Homomorphic Encryption

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Computer modeling in Engineering & Sciences 2024年第2期138卷 1731-1748页

作者： mohanad A.mohammed Hala B.ab.ul wahab Computer Science Department The University of TechnologyBaghdadIraq

Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system ***,the Internet of Things(IoT)has revolutionized the Fourth Industrial Revolution by enabling interconnected devices to offer innovative services,ultimately enhancing human *** paper presents a new approach utilizing lightweight blockchain technology,effectively reducing the computational burden typically associated with conventional blockchain *** integrating this lightweight blockchain with IoT systems,substantial reductions in implementation time and computational complexity can be ***,the paper proposes the utilization of the Okamoto Uchiyama encryption algorithm,renowned for its homomorphic characteristics,to reinforce the privacy and security of IoT-generated *** integration of homomorphic encryption and blockchain technology establishes a secure and decentralized platformfor storing and analyzing sensitive data of the supply chain *** platformfacilitates the development of some business models and empowers decentralized applications to perform computations on encrypted data while maintaining data *** results validate the robust security of the proposed system,comparable to standard blockchain implementations,leveraging the distinctive homomorphic attributes of the Okamoto Uchiyama algorithm and the lightweight blockchain paradigm.

关键词： Blockchain IoT integration of IoT and blockchain consensus algorithm Okamoto Uchiyama homomorphic encryption lightweight blockchain

Re-analysis of temperature dependent neutron capture rates and stellarβ-decay rates of^(95-98)mo

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Chinese Physics C 2024年第9期48卷 142-149页

作者： ab.ul Kabir Jameel-Un Nabi muhammad Tahir ab.ul muneem Zain ul abideen Space and Astrophysics Research lab National Centre of GIS and Space ApplicationsDepartment of Space ScienceInstitute of Space TechnologyIslamabad 44000Pakistan University of Wah Quaid AvenueWah Cantt 47040PunjabPakistan Faculty of Engineering Sciences GIK Institute of Engineering Sciences and TechnologyTopi 23640Khyber PakhtunkhwaPakistan

The neutron capture rates and temperature dependent stellar beta decay rates of mo isotopes are investigated within the framework of the statistical code TALYS v1.96 and the proton neutron quasi particle random phase approximation(pn-QRPA)*** maxwellian average cross-section(mACS)and neutron capture rates for the^(95-98)mo(n,γ)^(96-99)mo radiative capture process are analyzed within the framework of the statistical code TALYS v1.96 based on the phenomenological nuclear level density model and gamma strength *** present model-based computations for the mACS are comparable to the existing measured *** sensitivity of stellar weak interaction rates to various densities and temperatures is investigated within the framework of the pn-QRPA *** attention is paid to the impact of thermally filled excited states in the decaying nuclei(^(95-98)mo)on electron emission and positron capture ***,we compare the neutron capture rates and stellar beta decay *** is found that neutron capture rates are higher than stellar beta decay rates at both lower and higher temperatures.

关键词： cross-section TALYS nuclear level density decay rates capture rates