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Optimization of Multigrain Premix for High Protein and Dietary Fibre Biscuits Using Response Surface Methodology (RSM)

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Food and Nutrition Sciences 2015年第9期6卷 747-756页

作者： Kathalsar Ashwath Kumar Gopal Kumar Sharma mohammed ayub khan Anil Dutt Semwal Cereals and Pulses Technology Division Defence Food Research Laboratory Siddarthanagar Mysore Karnataka India

In order to improve the nutritional quality of biscuits, a multigrain premix (MGP) was developed by using whole barley, sorghum, chickpea, pea and defatted soya flour, each at 20% level. The developed MGP had 26.28% protein, 10.13% insoluble dietary fiber and 7.38% soluble dietary fiber. The experiment was designed to optimise the MGP and wheat flour concentration for the development of multigrain biscuits with high protein, dietary fibre and to maximize the acceptability by the application of central composite rotatable design (CCRD) of Response Surface Methodology (RSM). The levels of incorporation of MGP and wheat flour were taken as variables whereas protein, soluble, insoluble fibers, biscuit dough hardness, breaking strength and overall acceptability (OAA) as responses. The optimum level of MGP and wheat flour obtained using numerical optimization was found to be 40 g and 60 g respectively. The biscuits prepared using these had 16.61% protein, 2.57% soluble fibre, and 6.67% insoluble fibre which is significantly (p ≤ 0.05) higher than control biscuit.

关键词： Multigrain Biscuits Breaking Strength High Protein and Fiber Multigrain Premix Response Surface Methodology (RSM)

Base Pressure Control with Semi-Circular Ribs at Critical Mach Number

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Fluid Dynamics & Materials Processing 2024年第9期20卷 2007-2028页

作者： Ambareen khan Sher Afghan khan mohammed Nishat Akhtar Abdul Aabid Muneer Baig School of Aerospace Engineering Universiti Sains MalaysiaPenang11600Malaysia Department of Mechanical and Aerospace Engineering Faculty of EngineeringInternational Islamic University MalaysiaKuala Lumpur59000Malaysia Department of Engineering Management College of EngineeringPrince Sultan UniversityP.O.Box 66833Riyadh11586Saudi Arabia

When better fuel-air mixing in the combustion chamber or a reduction in base drag are required in vehicles,rockets,and aeroplanes,the base pressure control is *** the base pressure and drag is necessary in both *** this work,semi-circular ribs with varying diameters(2,4,and 6 mm)positioned at six distinct positions(0.5D,1D,1.5D,2D,3D,and 4D)inside a square duct with a side of 15 mm are proposed as an efficient way to apply the passive control ***-depth research is done on optimising rib size for various rib *** to this study,the base pressure rises as rib height ***,the optimal location for the semi-circular ribs with a diameter of 2 mm is at *** 1D location appears to be optimal for the 4 mm size as *** the 6 mm size,however,the 4D position fills this function.

关键词： Base pressure nozzle pressure ratio base drag sonic Mach number passive control

Posture Detection of Heart Disease Using Multi-Head Attention Vision Hybrid(MHAVH)Model

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Computers, Materials & Continua 2024年第5期79卷 2673-2696页

作者： Hina Naz Zuping Zhang mohammed Al-Habib Fuad A.Awwad Emad A.A.Ismail Zaid Ali khan School of Computer Science and Engineering Central South UniversityChangsha410003China Department of Quantitative analysis College of Business AdministrationKing Saud UniversityP.O.Box 71115Riyadh11587Saudi Arabia Electrical and Computer Engineering University of VictoriaVictoriaV9A1B8Canada

Cardiovascular disease is the leading cause of death *** disease causes loss of heart muscles and is also responsible for the death of heart cells,sometimes damaging their functionality.A person’s life may depend on receiving timely assistance as soon as ***,minimizing the death ratio can be achieved by early detection of heart attack(HA)*** the United States alone,an estimated 610,000 people die fromheart attacks each year,accounting for one in every four ***,by identifying and reporting heart attack symptoms early on,it is possible to reduce damage and save many lives *** objective is to devise an algorithm aimed at helping individuals,particularly elderly individuals living independently,to safeguard their *** address these challenges,we employ deep learning *** have utilized a vision transformer(ViT)to address this ***,it has a significant overhead cost due to its memory consumption and computational complexity because of scaling dot-product ***,since transformer performance typically relies on large-scale or adequate data,adapting ViT for smaller datasets is more *** response,we propose a three-in-one steam model,theMulti-Head Attention Vision Hybrid(MHAVH).Thismodel integrates a real-time posture recognition framework to identify chest pain postures indicative of heart attacks using transfer learning techniques,such as ResNet-50 and VGG-16,renowned for their robust feature extraction *** incorporatingmultiple heads into the vision transformer to generate additional metrics and enhance heart-detection capabilities,we leverage a 2019 posture-based dataset comprising RGB images,a novel creation by the author that marks the first dataset tailored for posture-based heart attack *** the limited online data availability,we segmented this dataset into gender categories(male and female)and conducted testing on both segmented and original dat

关键词： Image analysis posture of heart attack(PHA)detection hybrid features VGG-16 ResNet-50 vision transformer advance multi-head attention layer

Network Security Enhanced with Deep Neural Network-Based Intrusion Detection System

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Computers, Materials & Continua 2024年第7期80卷 1457-1490页

作者： Fatma S.Alrayes mohammed Zakariah Syed Umar Amin Zafar Iqbal khan Jehad Saad Alqurni Information Systems Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia College of Computer and Information Sciences King Saud UniversityRiyadh11362Saudi Arabia College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Department of Educational Technologies College of EducationImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

This study describes improving network security by implementing and assessing an intrusion detection system(IDS)based on deep neural networks(DNNs).The paper investigates contemporary technical ways for enhancing intrusion detection performance,given the vital relevance of safeguarding computer networks against harmful *** DNN-based IDS is trained and validated by the model using the NSL-KDD dataset,a popular benchmark for IDS *** model performs well in both the training and validation stages,with 91.30%training accuracy and 94.38%validation ***,the model shows good learning and generalization capabilities with minor losses of 0.22 in training and 0.1553 in ***,for both macro and micro averages across class 0(normal)and class 1(anomalous)data,the study evaluates the model using a variety of assessment measures,such as accuracy scores,precision,recall,and F1 *** macro-average recall is 0.9422,the macro-average precision is 0.9482,and the accuracy scores are ***,macro-averaged F1 scores of 0.9245 for class 1 and 0.9434 for class 0 demonstrate the model’s ability to precisely identify anomalies *** research also highlights how real-time threat monitoring and enhanced resistance against new online attacks may be achieved byDNN-based intrusion detection systems,which can significantly improve network *** study underscores the critical function ofDNN-based IDS in contemporary cybersecurity procedures by setting the foundation for further developments in this *** research aims to enhance intrusion detection systems by examining cooperative learning techniques and integrating up-to-date threat knowledge.

关键词： Machine-Learning Deep-Learning intrusion detection system security privacy deep neural network NSL-KDD Dataset

CNN Channel Attention Intrusion Detection SystemUsing NSL-KDD Dataset

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Computers, Materials & Continua 2024年第6期79卷 4319-4347页

Intrusion detection systems(IDS)are essential in the field of cybersecurity because they protect networks from a wide range of online *** goal of this research is to meet the urgent need for small-footprint,highly-adaptable Network Intrusion Detection Systems(NIDS)that can identify *** NSL-KDD dataset is used in the study;it is a sizable collection comprising 43 variables with the label’s“attack”and“level.”It proposes a novel approach to intrusion detection based on the combination of channel attention and convolutional neural networks(CNN).Furthermore,this dataset makes it easier to conduct a thorough assessment of the suggested intrusion detection ***,maintaining operating efficiency while improving detection accuracy is the primary goal of this ***,typical NIDS examines both risky and typical behavior using a variety of *** the NSL-KDD dataset,our CNN-based approach achieves an astounding 99.728%accuracy rate when paired with channel *** to previous approaches such as ensemble learning,CNN,RBM(Boltzmann machine),ANN,hybrid auto-encoders with CNN,MCNN,and ANN,and adaptive algorithms,our solution significantly improves intrusion detection ***,the results highlight the effectiveness of our suggested method in improving intrusion detection precision,signifying a noteworthy advancement in this *** efforts will focus on strengthening and expanding our approach in order to counteract growing cyberthreats and adjust to changing network circumstances.

关键词： Intrusion detection system(IDS) NSL-KDD dataset deep-learning machine-learning CNN channel Attention network security

Smartphone-Based Wi-Fi Analysis for Bus Passenger Counting

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Computers, Materials & Continua 2024年第4期79卷 875-907页

作者： mohammed Alatiyyah Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

In the contemporary era of technological advancement,smartphones have become an indispensable part of individuals’daily lives,exerting a pervasive *** paper presents an innovative approach to passenger countingonbuses throughthe analysis ofWi-Fi signals emanating frompassengers’mobile *** study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels,thereby addressing a crucial aspect of public *** proposed system comprises three crucial elements:Signal capture,data filtration,and the calculation and estimation of passenger *** pivotal findings reveal that the system demonstrates commendable accuracy in estimating passenger counts undermoderate-crowding conditions,with an average deviation of 20%from the ground truth and an accuracy rate ranging from 90%to 100%.This underscores its efficacy in scenarios characterized by moderate levels of ***,in densely crowded conditions,the system exhibits a tendency to overestimate passenger numbers,occasionally doubling the actual *** acknowledging the need for further research to enhance accuracy in crowded conditions,this study presents a pioneering avenue to address a significant concern in public *** implications of the findings are poised to contribute substantially to the enhancement of bus operations and service quality.

关键词： Public transportation digital environment passenger estimation signal capturing Wi-Fi

EECLP: AWireless Sensor Networks Energy Efficient Cross-Layer Protocol

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Computers, Materials & Continua 2024年第8期80卷 2611-2631页

作者： mohammed Kaddi mohammed Omari Moamen Alnatoor LDDI Laboratory University of AdrarAdrar01000Algeria Computer Science and Engineering Department School of EngineeringAmerican University of Ras Al KhaimahRas Al Khaimah72603United Arab Emirates

Recent advancements in wireless communications have allowed the birth of novel wireless sensor networks(WSN).A sensor network comprises several micro-sensors deployed randomly in an area of interest.A micro-sensor is provided with an energy resource to supply electricity to all of its ***,the disposed energy resource is limited and battery replacement is generally *** this restriction,the sensors must conserve energy to prolong their *** energy conservation strategies for WSNs have been presented in the literature,from the application to the physical *** of these solutions focus only on optimizing a single layer in terms of energy *** this research,a novel cross-layer technique for WSNs’effective energy usage is *** most energy consumption factors exist in the Medium Access Control(MAC)layer and network layer,our EECLP protocol(Energy Efficient Cross-Layer Protocol for Wireless Sensor Networks)integrates these two layers to satisfy energy efficiency *** gain access to the transmission channel,we implement a communication regime at the MAC layer based on CSMA/CA(Carrier Sense Multiple Access/Collision Avoidance)***,depending on the activity and a standby period,we employ the RTS/CTS(Request to Send/Clear to Send)method to prevent collisions and resolve hidden node concerns by utilizing the network allocation vector(NAV)to calculate the transmission *** a greedy strategy,we establish chains amongst cluster members to mitigate the issue of high energy consumption in routing *** objective function was utilized to determine the optimal cross-chain path based on the distances to the base station(BS)and residual energy(RE).The simulation,testing,and comparison of the proposed protocol to peer protocols have shown superior outcomes and a prolonged network *** the suggested protocol,the network lifetime increases by 10%compared to FAMACO(Fuzzy and Ant Col

关键词： WSN energy consumption MAC layer network layer EECLP energy-efficient lifespan

Numerical investigation of the effects of soil-structure and granular material-structure interaction on the seismic response of a flat-bottom reinforced concrete silo

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Earthquake Engineering and Engineering Vibration 2024年第3期23卷 609-623页

作者： Sonia Benkhellat mohammed Kadri Abdelghani Seghir Laboratory of Solid Mechanics and Systems University of M’Hamed BougaraBoumerdes 35000Algeria Laboratory of Geomaterials Environment and DevelopmentUniversity of M’Hamed BougaraBoumerdes 35000Algeria Research Laboratory of Applied Hydraulics and Environment Faculty of TechnologyUniversity of BejaiaBejaia 06000Algeria

In this work,a numerical study of the effects of soil-structure interaction(SSI)and granular material-structure interaction(GSI)on the nonlinear response and seismic capacity of flat-bottomed storage silos is conducted.A series of incremental dynamic analyses(IDA)are performed on a case of large reinforced concrete silo using 10 seismic *** IDA results are given by two average IDA capacity curves,which are represented,as well as the seismic capacity of the studied structure,with and without a consideration of the SSI while accounting for the effect of *** curves are used to quantify and evaluate the damage of the studied silo by utilizing two damage indices,one based on dissipated energy and the other on displacement and dissipated *** cumulative energy dissipation curves obtained by the average IDA capacity curves with and without SSI are presented as a function of the base shear,and these curves allow one to obtain the two critical points and the different limit states of the *** is observed that the SSI and GSI significantly influence the seismic response and capacity of the studied structure,particularly at higher levels of ***,the effect of the SSI reduces the damage index of the studied structure by 4%.

关键词： reinforced concrete silo perfectly matched layers soil-structure interaction granular material-structure interaction effective seismic input method damage index

Improved Dwarf Mongoose Optimization Algorithm for Feature Selection:Application in Software Fault Prediction Datasets

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Journal of Bionic Engineering 2024年第4期21卷 2000-2033页

作者： Abdelaziz I.Hammouri mohammed A.Awadallah Malik ShBraik mohammed Azmi Al-Betar Majdi Beseiso Department of Computer Science Al-Balqa Applied UniversityAl-Salt19117Jordan Department of Scientific Research and Graduate Studies University of Prince Mugrin42241MedinaSaudi Arabia Department of Computer Science Al-Aqsa UniversityGaza4051Palestine Artificial Intelligence Research Center(AIRC) Ajman UniversityAjmanUnited Arab Emirates Department of Information Technology Al-Huson University CollegeAl-Balqa Applied UniversityAl-HusonIrbid21110Jordan

Feature selection(FS)plays a crucial role in pre-processing machine learning datasets,as it eliminates redundant features to improve classification accuracy and reduce computational *** paper presents an enhanced approach to FS for software fault prediction,specifically by enhancing the binary dwarf mongoose optimization(BDMO)algorithm with a crossover mechanism and a modified positioning updating *** proposed approach,termed iBDMOcr,aims to fortify exploration capability,promote population diversity,and lastly improve the wrapper-based FS process for software fault prediction *** gained superb performance compared to other well-esteemed optimization methods across 17 benchmark *** ranked first in 11 out of 17 datasets in terms of average classification ***,iBDMOcr outperformed other methods in terms of average fitness values and number of selected features across all *** findings demonstrate the effectiveness of iBDMOcr in addressing FS problems in software fault prediction,leading to more accurate and efficient models.

关键词： Dwarf mongoose optimization algorithm Optimization Feature selection Classification