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Analyzing dynamic curve widening on forest roads

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Journal of Forestry Research 2017年第2期28卷 411-417页

作者： Mustafa Akgul Murat Demir abdullah e.akay Forest engineering Division Faculty of ForestryForest Construction and TransportationIstanbul UniversitySariyerIstanbulTurkey Forest engineering Department Faculty of ForestryBursa Technical UniversityOsmangazi16200 BursaTurkey

Forest roads require important design specifications to ensure all-season access for various vehicles. Long and heavy log trucks can face serious maneuvering problems on forest roads due to insufficient amount of area to the left for road widening on horizontal curves. In order to provide safe and continuous shipment and transportation,appropriate curve widening areas should be provided for long vehicles along horizontal curves. In this study, a statistical model was developed to provide curve-widening solutions for long trucks（e.g., those with 18 wheels） considering various curve radius and deflection angles. The dynamic curve widening feature of Plateia 2013 program was employed to calculate curve widening for the specified vehicle. During the solution process, nine different horizontal curve diameters from 10 to 50 m（by 5 m intervals）and 17 different deflection angles from 90° to 170°（by 5°intervals） were evaluated to run horizontal curve-widening analysis. Using a multiple regression model, we made suitable predictions about curve widening. The curvewidening areas decrease as the horizontal curve radius increases, while increasing the deflection angle on horizontal curves increases curve widening areas. Clearly, the computer-based dynamic curve widening model developed in this study can be effectively used in determining optimum widening for horizontal curves by evaluating the number of alternatives that fit geometrical specifications and vehicle types.

关键词： deflection diameters radius specifications transportation alternatives determining evaluating insufficient season

Assessing the effects of site factors on the productivity of a feller buncher:a time and motion analysis

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Journal of Forestry Research 2019年第4期30卷 1471-1478页

作者： ebru Bilici abdullah e.akay Dalia Abbas Department of Forestry Dereli Vocational SchoolGiresun UniversityGiresunTurkey Department of Forest engineering Faculty of ForestryBursa Technical UniversityBursaTurkey Department of Forestry Wildlife and FisheriesUniversity of TennesseeKnoxvilleTNUSA Department of environmental Science American UniversityWashingtonDCUSA

We evaluated,for the first time in Turkey,the productivity of a feller buncher during clear-cut operations of two Brutian pine stands located in Canakkale,northwestern Turkey with different diameter classes and terrain conditions.In the first stand with 24.6 cm average DBH,the feller buncher cut full trees and moved them to roadside.In the second stand with 34.3 cm average DBH,the feller buncher cut trees in two stages due to their larger diameters and the relatively steep and rough terrain conditions of the site.The effects of specific stand features,DBH and tree height measurements were assessed through statistical analysis in relation to productivity.The results indicate that the average productivity for the first stand was about 118 m^3h^-1,while it was about 80 m3h-1 in the second stand.even though tree diameter and volume were higher in the second stand,productivity decreased by32.3%due to extra time spent on the two-stage cutting operation.The results revealed that harvesting operations should be planned carefully and the right equipment selected by accounting for different tree sizes,terrain conditions and machine specifications in order to better understand their effects on production.

关键词： Timber harvesting Feller buncher Timber size Productivity Time and motion study

evolutionary Optimization Methods for High-Dimensional expensive Problems:A Survey

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Ieee/CAA Journal of Automatica Sinica 2024年第5期11卷 1092-1105页

作者： MengChu Zhou Meiji Cui Dian Xu Shuwei Zhu Ziyan Zhao abdullah Abusorrah Department of electrical and Computer engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA School of Information and electronic engineering Zhejiang Gongshang UniversityHangzhou 310018China School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China Institute of Systems engineering Macao University of Science and TechnologyMacao 999078China School of Artificial Intelligence and Computer Jiangnan UniversityWuxi 214122China School of Information Science and engineering Northeastern UniversityShenyang 110819China Center of Research excellence in Renewable energy and Power Systems Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia K.A.CARe energy Research and Innovation Center King Abdulaziz UniversityJeddah 21589Saudi Arabia

evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization problems.The past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HePs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer simulations.Moreover,it is hard to traverse the huge search space within reasonable resource as problem dimension increases.Traditional evolutionary algorithms(eAs)tend to fail to solve HePs competently because they need to conduct many such expensive evaluations before achieving satisfactory results.To reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HePs in recent years.Yet there lacks a thorough review of the state of the art in this specific and important area.This paper provides a comprehensive survey of these evolutionary algorithms for HePs.We start with a brief introduction to the research status and the basic concepts of HePs.Then,we present surrogate-assisted evolutionary algorithms for HePs from four main aspects.We also give comparative results of some representative algorithms and application examples.Finally,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HePs.

关键词： computer optimization evolutionary

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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 constraints.The 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 efficiency.Biomass or biomass waste will continue to have a vital role to play in the future FBC technology-based power generation.Biomass often contains high levels of inorganic species that can form sticky agglomerates posing a significant risk to boiler operation resulting in unscheduled outages.This 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 technology.To resolve this problem,this research devised a simulation strategy for the detection of agglomeration using the eulerian–eulerian approach.The developed modelling strategy is validated with the experimental data available in literature for two-dimensional simplified geometry of a pilot-scale fluidised bed combustor.The 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

A New Method for Diagnosis of Leukemia Utilizing a Hybrid DL-ML Approach for Binary and Multi-Class Classification on a Limited-Sized Database

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Computer Modeling in engineering & Sciences 2024年第4期139卷 593-631页

作者： Nilkanth Mukund Deshpande Shilpa Gite Biswajeet Pradhan abdullah Alamri Chang-Wook Lee Department of electronics&Telecommunication LavaleSymbiosis Institute of TechnologySymbiosis International(Deemed University)PuneMaharashtra412115India electronics&Telecommunication Dr.Vithalrao Vikhe Patil College of EngineeringAhmednagarMaharashtra414111India Artificial Intelligence and Machine Learning Department Symbiosis Institute of TechnologySymbiosis International(Deemed)UniversityPune412115India Symbiosis Centre of Applied AI(SCAAI) Symbiosis International(Deemed)UniversityPune412115India Centre for AdvancedModelling and Geospatial Information Systems(CAMGIS) School of Civil and Environmental EngineeringFaculty of Engineering&ITUniversity of Technology SydneySydneyAustralia earth Observation Centre Institute of Climate ChangeUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia Department of Geology&Geophysics College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia Department of Science education Kangwon National UniversityChuncheon-si24341Korea

Infection of leukemia in humans causes many complications in its later stages.It impairs bone marrow’s ability to produce blood.Morphological diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this case.The binary classification is employed to distinguish between normal and leukemiainfected cells.In addition,various subtypes of leukemia require different treatments.These sub-classes must also be detected to obtain an accurate diagnosis of the type of leukemia.This entails using multi-class classification to determine the leukemia subtype.This is usually done using a microscopic examination of these blood cells.Due to the requirement of a trained pathologist,the decision process is critical,which leads to the development of an automated software framework for diagnosis.Researchers utilized state-of-the-art machine learning approaches,such as Support Vector Machine(SVM),Random Forest(RF),Na飗e Bayes,K-Nearest Neighbor(KNN),and others,to provide limited accuracies of classification.More advanced deep-learning methods are also utilized.Due to constrained dataset sizes,these approaches result in over-fitting,reducing their outstanding performances.This study introduces a deep learning-machine learning combined approach for leukemia diagnosis.It uses deep transfer learning frameworks to extract and classify features using state-of-the-artmachine learning classifiers.The transfer learning frameworks such as VGGNet,Xception,InceptionResV2,Densenet,and ResNet are employed as feature extractors.The extracted features are given to RF and XGBoost classifiers for the binary and multi-class classification of leukemia cells.For the experimentation,a very popular ALL-IDB dataset is used,approaching a maximum accuracy of 100%.A private real images dataset with three subclasses of leukemia images,including Acute Myloid Leukemia(AML),Chronic Lymphocytic Leukemia(CLL),and Chronic Myloid Leukemia(CML),is also employed to generalize the system.This dataset achieves an impressive multi-class classi

关键词： Leukemia diagnosis deep learning machine learning random forest XGBoost

Adaptation of Federated explainable Artificial Intelligence for efficient and Secure e-Healthcare Systems

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Computers, Materials & Continua 2024年第3期78卷 3413-3429页

作者： Rabia Abid Muhammad Rizwan Abdulatif Alabdulatif abdullah Alnajim Meznah Alamro Mourade Azrour Department of Computer Science Kinnaird College for WomenLahorePakistan College of Science and engineering University of DerbyDerbyDE221GBUK Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia STI Laboratory IDMS TeamFaculty of Sciences and TechniquesMoulay Ismail University of MeknèsMeknesMorocco

explainable Artificial Intelligence(XAI)has an advanced feature to enhance the decision-making feature and improve the rule-based technique by using more advanced Machine Learning(ML)and Deep Learning(DL)based algorithms.In this paper,we chose e-healthcare systems for efficient decision-making and data classification,especially in data security,data handling,diagnostics,laboratories,and decision-making.Federated Machine Learning(FML)is a new and advanced technology that helps to maintain privacy for Personal Health Records(PHR)and handle a large amount of medical data effectively.In this context,XAI,along with FML,increases efficiency and improves the security of e-healthcare systems.The experiments show efficient system performance by implementing a federated averaging algorithm on an open-source Federated Learning(FL)platform.The experimental evaluation demonstrates the accuracy rate by taking epochs size 5,batch size 16,and the number of clients 5,which shows a higher accuracy rate(19,104).We conclude the paper by discussing the existing gaps and future work in an e-healthcare system.

关键词： Artificial intelligence data privacy federated machine learning healthcare system security

Commentary on "Association of daily sitting time and leisure-time physical activity with body fat among U.S.adults"

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Journal of Sport and Health Science 2024年第2期13卷 127-129页

作者： Barbara e.Ainsworth School of exercise and Health Shanghai University of SportShanghai 200438China

In their study,association of daily sitting time and leisure-time physical activity (LTPA) with body fat among U.S.Adults,Liao et al.^(1) analyzed data from the 2011-2018 National Health and examination Survey to examine associations between h/day sitting,meeting (or not meeting) the U.S.Physical Activity Guidelines of≥150 min/week of moderate-and vigorous-intensity LTPA,and combinations of sitting time and LTPA on totaland trunk percent body fat (BF%).

关键词： U.S. adult among

Advances in spinal cord injury:insights from non-human primates

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Neural Regeneration Research 2024年第11期19卷 2354-2364页

作者： Gaetan Poulen Florence e.Perrin University of Montpellier INSERMEPHEMontpellierFrance Department of Neurosurgery Gui de Chauliac HospitalMontpellier University Medical CenterMontpellierFrance Institut Universitaire de France(IUF) ParisFrance

Spinal cord injury results in significant sensorimotor deficits,currently,there is no curative treatment for the symptoms induced by spinal cord injury.Basic and pre-clinical research on spinal cord injury relies on the development and characterization of appropriate animal models.These models should replicate the symptoms observed in human,allowing for the exploration of functional deficits and investigation into various aspects of physiopathology of spinal cord injury.Non-human primates,due to their close phylogenetic association with humans,share more neuroanatomical,genetic,and physiological similarities with humans than rodents.Therefore,the responses to spinal cord injury in nonhuman primates most likely resemble the responses to traumatism in humans.In this review,we will discuss nonhuman primate models of spinal cord injury,focusing on in vivo assessments,including behavioral tests,magnetic resonance imaging,and electrical activity recordings,as well as ex vivo histological analyses.Additionally,we will present therapeutic strategies developed in non-human primates and discuss the unique specificities of non-human primate models of spinal cord injury.

关键词： behavior cellular analysis non-human primates spinal cord injury tissue analysis

event-triggered H_(∞) consensus control for input-constrained multi-agent systems via reinforcement learning

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Control Theory and Technology 2024年第1期22卷 25-38页

作者： Jinxuan Zhang Chang-e Ren College of Information engineering Capital Normal UniversityBeijing100089China

This article presents an event-triggered H_(∞) consensus control scheme using reinforcement learning (RL) for nonlinear second-order multi-agent systems (MASs) with control constraints. First, considering control constraints, the constrained H_(∞) consensus problem is transformed into a multi-player zero-sum game with non-quadratic performance functions. Then, an event-triggered control method is presented to conserve communication resources and a new triggering condition is developed for each agent to make the triggering threshold independent of the disturbance attenuation level. To derive the optimal controller that can minimize the cost function in the case of worst disturbance, a constrained Hamilton–Jacobi–Bellman (HJB) equation is defined. Since it is difficult to solve analytically due to its strongly non-linearity, reinforcement learning (RL) is implemented to obtain the optimal controller. In specific, the optimal performance function and the worst-case disturbance are approximated by a time-triggered critic network;meanwhile, the optimal controller is approximated by event-triggered actor network. After that, Lyapunov analysis is utilized to prove the uniformly ultimately bounded (UUB) stability of the system and that the network weight errors are UUB. Finally, a simulation example is utilized to demonstrate the effectiveness of the control strategy provided.

关键词： H_(∞)optimal control Input constrains Multi-agent systems(MASs) Reinforcement learning(RL)