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Impediments of Cognitive System Engineering in Machine-Human Modeling

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Computers, Materials & Continua 2023年第3期74卷 6689-6701页

作者： Fayaz Ahmad Fayaz Arun Malik Isha Batra Akber Abid Gardezi syed immamul ansarullah Shafiq Ahmad Mejdal Alqahtani Muhammad Shafiq National Institute of Electronics and Information Technology(NIELIT) J&K191132India Department of Computer Science&Engineering Lovely Professional University(LPU)Punjab144402India Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Computer Science Govt.Degree College Sumbal Kashmir193501India Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

A comprehensive understanding of human intelligence is still an ongoing process,i.e.,human and information security are not yet perfectly *** understanding cognitive processes,designers can design humanized cognitive information systems(CIS).The need for this research is justified because today’s business decision makers are faced with questions they cannot answer in a given amount of time without the use of cognitive information *** researchers aim to better strengthen cognitive information systems with more pronounced cognitive thresholds by demonstrating the resilience of cognitive resonant frequencies to reveal possible responses to improve the efficiency of human-computer interaction(HCI).Apractice-oriented research approach included research analysis and a review of existing articles to pursue a comparative research model;thereafter,amodel development paradigm was used to observe and monitor the progression of CIS during *** scope of our research provides a broader perspective on how different disciplines affect HCI and how human cognitive models can be enhanced to enrich *** have identified a significant gap in the current literature on mental processing resulting from a wide range of theory and practice.

关键词： Cognitive-IoT human-computer interaction decision making

A Framework to Assess Possible Sources of Stakeholder Exploitation:A Developing Country Case

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International Journal of Disaster Risk Science 2024年第1期15卷 32-44页

作者： Kamran Shafique syed Shams Tapan Sarker School of Business University of Southern QueenslandSpringfeldQLD 4300Australia Business School University of QueenslandSt LuciaQLD 4072Australia

Solving complex post-disaster reconstruction challenges requires the altruistic involvement of heterogeneous stakeholder ***,small,more organized groups,such as government parastatals,private developers,and contractors often exploit large,unorganized groups,such as affected communities,leaving them more vulnerable to future *** on data collected from a case study in Pakistan,this study proposed a framework to assess,anticipate,and mitigate the exploitation of vulnerable stakeholders in post-disaster reconstruction *** framework draws on influential management theories and utilizes reciprocal relationships between stakeholder attributes(power,legitimacy,and urgency),participation,and *** study also argued for non-binary treatment of stakeholder *** framework will allow practitioners to address issues around the exploitation of stakeholder interests in future post-disaster reconstruction projects.

关键词： Collective action Pakistan Post-disaster reconstruction-Stakeholder participation Stakeholder exploitation

Automatic Finding of Brain-Tumour Group Using CNN Segmentation and Moth-Flame-Algorithm,Selected Deep and Handcrafted Features

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Computers, Materials & Continua 2024年第5期79卷 2585-2608页

作者： Imad Saud Al Naimi syed Alwee Aljunid syed Junid Muhammad lmran Ahmad K.Suresh Manic Faculty of Electronic Engineering Technology University Malaysia Perils(UniMAP)Pauh Putra CampusArauPerlis02600Malaysia Department of Electrical and Communication Engineering National University of Science and TechnologyAL HailAL Seeb130Sultanate of Oman Department of Research and Innovation Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMATS)ChennaiTamiNadu602105India

Augmentation of abnormal cells in the brain causes brain tumor(BT),and early screening and treatmentwill reduce its harshness in ***’s clinical level screening is usually performed with Magnetic Resonance Imaging(MRI)due to its multi-modality *** overall aims of the study is to introduce,test and verify an advanced image processing technique with algorithms to automatically extract tumour sections from brain MRI scans,facilitating improved *** research intends to devise a reliable framework for detecting the BT region in the twodimensional(2D)MRI slice,and identifying its class with improved *** methodology for the devised framework comprises the phases of:(i)Collection and resizing of images,(ii)Implementation and Segmentation of Convolutional Neural Network(CNN),(iii)Deep feature extraction,(iv)Handcrafted feature extraction,(v)Moth-Flame-Algorithm(MFA)supported feature reduction,and(vi)Performance *** study utilized clinical-grade brain MRI of BRATS and TCIA datasets for the *** framework segments detected the glioma(low/high grade)and glioblastoma class *** work helped to get a segmentation accuracy of over 98%with VGG-UNet and a classification accuracy of over 98%with the VGG16 *** study has confirmed that the implemented framework is very efficient in detecting the BT in MRI slices with/without the skull section.

关键词： Brain tumour VGG-UNet VGG16 moth-flame-algorithm classification

Refined Anam-Net:Lightweight Deep Learning Model for Improved Segmentation Performance of Optic Cup and Disc for Glaucoma Diagnosis

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Computers, Materials & Continua 2024年第7期80卷 1381-1405页

作者： Khursheed Aurangzeb syed Irtaza Haider Musaed Alhussein Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia

In this work,we aim to introduce some modifications to the Anam-Net deep neural network(DNN)model for segmenting optic cup(OC)and optic disc(OD)in retinal fundus images to estimate the cup-to-disc ratio(CDR).The CDR is a reliable measure for the early diagnosis of *** this study,we developed a lightweight DNN model for OC and OD segmentation in retinal fundus *** DNN model is based on modifications to Anam-Net,incorporating an anamorphic depth embedding *** reduce computational complexity,we employ a fixed filter size for all convolution layers in the encoder and decoder stages as the network *** modification significantly reduces the number of trainable parameters,making the model lightweight and suitable for resource-constrained *** evaluate the performance of the developed model using two publicly available retinal image databases,namely RIM-ONE and *** results demonstrate promising OC segmentation performance across most standard evaluation metrics while achieving analogous results for OD *** used two retinal fundus image databases named RIM-ONE and Drishti-GS that contained 159 images and 101 retinal images,*** OD segmentation using the RIM-ONE we obtain an f1-score(F1),Jaccard coefficient(JC),and overlapping error(OE)of 0.950,0.9219,and 0.0781,***,for OC segmentation using the same databases,we achieve scores of 0.8481(F1),0.7428(JC),and 0.2572(OE).Based on these experimental results and the significantly lower number of trainable parameters,we conclude that the developed model is highly suitable for the early diagnosis of glaucoma by accurately estimating the CDR.

关键词： Refined Anam-Net parameter tuning deep learning optic cup optic disc cup-to-disc ratio glaucoma diagnosis

An efficient permutation approach for SbPN-based symmetric block ciphers

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Cybersecurity 2024年第2期7卷 113-130页

作者： Mir Nazish M.Tariq Banday Insha syed Sheena Banday Department of Electronics and Instrumentation Technology University ofKashmirSrinagar 190006India

It is challenging to devise lightweight cryptographic primitives efficient in both hardware and software that can provide an optimum level of security to diverse Internet of Things applications running on low-end constrained ***,an effcient hardware design approach that requires some specific hardware resource may not be effcient if implemented in *** bit Permutation Network based ciphers such as PRESENT and GIFT are effcient,lightweight cryptographic hardware design *** ciphers introduce confusion and diffu-sion by employing a 4×4 static substitution box and bit *** bit-wise permutation is realised by sim-ple rerouting,which is most cost-effective to implement in hardware,resulting in negligible power ***,this method is highly resource-consuming in software,particularly for large block-sized ciphers,with each single-bit permutation requiring multiple *** paper proposes a novel software-based design approach for permutation operation in Substitution bit Permutation Network based ciphers using a bit-banding *** conventional permutation using bit rotation and the proposed approach have been implemented,analysed and compared for GIFT and PRESENT ciphers on ARM Cortex-M3-based LPC1768 development platform with KEIL MDK used as an Integrated Development *** real-time performance comparison between conven-tional and the proposed approaches in terms of memory(RAM/ROM)footprint,power,energy and execution time has been carried out using ULINKpro and ULINKplus debug adapters for various code and speed optimisation *** proposed approach substantially reduces execution time,energy and power consumption for both PRE-SENT and GIFT ciphers,thus demonstrating the effciency of the proposed method for Substitution bit Permutation Network based symmetric block ciphers.

关键词： Lightweight cryptography PRESENT GIFT SbPN Cortex-M LPC1768 Bit-band memory

Conservation laws,Lie symmetries,self adjointness,and soliton solutions for the Selkov–Schnakenberg system

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Communications in Theoretical Physics 2024年第2期76卷 29-44页

作者： Kashif Ali Aly R Seadawy syed T R Rizvi Noor Aziz Department of Mathematics COMSATS University IslamabadLahore CampusPakistan Mathematics Department Faculty of ScienceTaibah UniversityAl-Madinah Al-Munawarah41411Saudi Arabia

In this article,we explore the famous Selkov–Schnakenberg(SS)system of coupled nonlinear partial differential equations(PDEs)for Lie symmetry analysis,self-adjointness,and conservation ***,miscellaneous soliton solutions like dark,bright,periodic,rational,Jacobian elliptic function,Weierstrass elliptic function,and hyperbolic solutions of the SS system will be achieved by a well-known technique called sub-ordinary differential *** these results are displayed graphically by 3D,2D,and contour plots.

关键词： Selkov-Schnakenberg system Lie symmetry analysis conservation laws adjointness integrability

Detection of onset of agglomeration in a bubbling fluidized bed biomass combustor using reactive Eulerian computational fluid dynamics

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Particuology 2024年第7期90卷 504-515页

作者： Abdullah Tasleem Atta Ullah Fei Li Qun Yi William Nimmo syed Sheraz Daood Department of Chemical Engineering Pakistan Institute of Engineering and Applied Sciences(PIEAS)Lehtrar RoadP.O.Nilore45650IslamabadPakistan Institute of Process Engineering Chinese Academy of SciencesBeijing100190China School of Chemical Engineering and Pharmacy Wuhan Institute of TechnologyWuhan430205China Energy Engineering Group Energy 2050Department of Mechanical EngineeringUniversity of SheffieldSheffieldS37RDUnited Kingdom Institute of Energy and Environmental Engineering Faculty of ElectricalEnergy&Environmental EngineeringUniversity of the PunjabQuaid-e-Azam CampusLahorePakistan Energy Engineering Research and Development Centre Faculty of ElectricalEnergy&Environmental EngineeringUniversity of the PunjabQuaid-e-Azam CampusLahorePakistan

The choice of a type of combustion technology to be used for heat or power generation depends on economic,technical,operational and fuel availability *** benefits associated with the evolving market driven by the fluidised bed combustion(FBC)technology cannot be overlooked especially when gauged at 65 GWth of worldwide installed capacity alongside added benefits of handling fuel variation,low pollutant emissions and high combustion *** or biomass waste will continue to have a vital role to play in the future FBC technology-based power *** often contains high levels of inorganic species that can form sticky agglomerates posing a significant risk to boiler operation resulting in unscheduled *** added complexity of the behaviour of the fuel and bed material mix highlights the requirement for simulation models to identify agglomeration to help improve the overall performance and reliability of FBC *** resolve this problem,this research devised a simulation strategy for the detection of agglomeration using the Eulerian–Eulerian *** developed modelling strategy is validated with the experimental data available in literature for two-dimensional simplified geometry of a pilot-scale fluidised bed *** model results were found promising and robust to predict bed defluidisation times and other parameters consistent with the experimental data.

关键词： Fluidized bed combustion Eulerian Models Biomass Agglomeration Defluidisation

An asymmetrical multilevel inverter with minimum voltage stress and fewer components for photovoltaic renewable-energy system

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Clean Energy 2024年第1期8卷 1-22页

作者： Rabail Memon Mukhtiar Ahmed Mahar Abdul Sattar Larik syed Asif Ali shah Department of Electrical Engineering Mehran University of Engineering and TechnologyJamshoroPakistan

The enhanced power quality provided by multilevel inverters(MLIs)has made them more appropriate for medium-and high-power applications,including photovoltaic ***,a prevalent limitation involves the necessity for numerous switches and increased voltage stress across these switches,consequently increasing the overall system *** address these challenges,a new 17-level asymmetrical MLI with fewer components and low voltage stress is proposed for the photovoltaic *** innovative MLI configuration has four direct current(DC)sources and 10 *** on the trinary sequence,the proposed topology uses photovoltaics with boost converters and fuzzy logic controllers as its DC *** equations are used to calculate cru-cial parameters for this proposed design,including total standing voltage per unit(TSVPU),cost function per level(CF/L),component count per level(CC/L)and voltage stress across the *** comparison is conducted by considering switches,DC sources,TSVPU,CF/L,gate driver circuits and CC/L with other existing MLI *** analysis is carried out under various conditions,encompassing different levels of irradiance,variable loads and modulation *** reduce the total harmonic distortion of the suggested topology,the phase opposition disposition approach has been *** suggested framework is simulated in MATLAB®/Simulink®.The results indicate that the proposed topology achieves a well-distributed stress profile across the switches and has CC/L of 1.23,TSVPU of 5 and CF/L of 4.58 and 5.76 with weight coefficients of 0.5 and 1.5,*** values are not-ably superior to those of existing MLI *** results demonstrate that the proposed topology maintains a consistent output at varying irradiance levels with FLCs and exhibits robust performance under variable loads and diverse modulation ***,the total harmonic distortion achieved with phase opposition disposi

关键词： asymmetrical multilevel inverter photovoltaic system renewable energy component count per level cost function per level total standing voltage per unit phase opposition disposition technique

Enhancing Skin Cancer Diagnosis with Deep Learning:A Hybrid CNN-RNN Approach

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Computers, Materials & Continua 2024年第4期79卷 1497-1519页

作者： syeda Shamaila Zareen Guangmin Sun Mahwish Kundi syed Furqan Qadri Salman Qadri Faculty of Information Technology Beijing University of TechnologyBeijing100124China Computer Science International Engineering Collage Maynooth UniversityKildareW23 F2H6Irland Research Center for Data Hub and Security Zhejiang LabHangzhou311121China Computer Science Department MNS University of AgricultureMultan59220Pakistan

Skin cancer diagnosis is difficult due to lesion presentation variability. Conventionalmethods struggle to manuallyextract features and capture lesions spatial and temporal variations. This study introduces a deep learning-basedConvolutional and Recurrent Neural Network (CNN-RNN) model with a ResNet-50 architecture which usedas the feature extractor to enhance skin cancer classification. Leveraging synergistic spatial feature extractionand temporal sequence learning, the model demonstrates robust performance on a dataset of 9000 skin lesionphotos from nine cancer types. Using pre-trained ResNet-50 for spatial data extraction and Long Short-TermMemory (LSTM) for temporal dependencies, the model achieves a high average recognition accuracy, surpassingprevious methods. The comprehensive evaluation, including accuracy, precision, recall, and F1-score, underscoresthe model’s competence in categorizing skin cancer types. This research contributes a sophisticated model andvaluable guidance for deep learning-based diagnostics, also this model excels in overcoming spatial and temporalcomplexities, offering a sophisticated solution for dermatological diagnostics research.

关键词： Skin cancer classification deep learning Convolutional Neural Network(CNN) RNN ResNet-50