Cancer is a formidable andmultifaceted disease driven by genetic aberrations and metabolic disruptions.Around 19% of cancer-related deaths worldwide are attributable to lung and colon cancer,which is also the top caus...Cancer is a formidable andmultifaceted disease driven by genetic aberrations and metabolic disruptions.Around 19% of cancer-related deaths worldwide are attributable to lung and colon cancer,which is also the top cause of death worldwide.The malignancy has a terrible 5-year survival rate of 19%.Early diagnosis is critical for improving treatment outcomes and survival rates.The study aims to create a computer-aided diagnosis(CAD)that accurately diagnoses lung disease by classifying histopathological images.It uses a publicly accessible dataset that includes 15,000 images of benign,malignant,and squamous cell carcinomas in the lung.In addition,this research employs multiscale processing to extract relevant image features and conducts a comprehensive comparative analysis using four Convolutional Neural Network(CNN)based on pre-trained models such as AlexNet,VGG(Visual Geometry Group)16,ResNet-50,and VGG19,after hyper-tuning these models by optimizing factors such as batch size,learning rate,and epochs.The proposed(CNN+VGG19)model achieves the highest accuracy of 99.04%.This outstanding performance demonstrates the potential of the CAD system in accurately classifying lung cancer histopathological images.This study contributes significantly to the creation of a more precise CNN-based model for lung cancer identification,giving researchers and medical professionals in this vital sector a useful tool using advanced deep learning techniques and publicly available datasets.展开更多
The paper presents a novel quantum method for addressing two fundamental routing problems:the Traveling Salesman Problem(TSP)and theVehicle Routing Problem(VRP),both central to routing challenges.The proposed method,n...The paper presents a novel quantum method for addressing two fundamental routing problems:the Traveling Salesman Problem(TSP)and theVehicle Routing Problem(VRP),both central to routing challenges.The proposed method,named the Indirect Quantum Approximate Optimization Algorithm(IQAOA),leverages an indirect solution representation using ranking.Our contribution focuses on two main areas:1)the indirect representation of solutions,and 2)the integration of this representation into an extended version of QAOA,called IQAOA.This approach offers an alternative to QAOA and includes the following components:1)a quantum parameterized circuit designed to simulate string vectors on a quantum processor,2)a classical meta-optimization method executed on a classical computer,and 3)the computation of the average cost for each string vector,achieved through a well-established algorithm from the operations research community tailored to the specific problem.IQAOA provides an efficient means to address quantum optimization problems by combining quantum and classical computation methods.Its primary advantage lies in deriving a quantum circuit that requires significantly fewer gates,making it suitable for execution on current noisy quantum computing platforms.Through numerical experiments employing IQAOA,we successfully solved instances of the 10-customer Traveling Salesman Problem(TSP)using the IBM simulator.To our knowledge,this is the largest application of a QAOA-based approach to solving the TSP.Additionally,IQAOA enables the resolution of the Vehicle Routing Problem(VRP)by leveraging the Split algorithm,which transforms a TSP permutation into a corresponding VRP solution.展开更多
针对应急疏散行为受社会化属性驱动而表现出不确定性、互动关系复杂等特征,基于Cell-DEVS语言构建人员疏散系统仿真模型,模型在强化描述行人运动能力的基础上,引入环境熟悉程度、个体视野、沟通与引导及速率区块等社会化互动因素,旨在...针对应急疏散行为受社会化属性驱动而表现出不确定性、互动关系复杂等特征,基于Cell-DEVS语言构建人员疏散系统仿真模型,模型在强化描述行人运动能力的基础上,引入环境熟悉程度、个体视野、沟通与引导及速率区块等社会化互动因素,旨在优化模型算法,完善个体与环境,个体之间互动关系的描述。RESTful web service远程仿真结果进一步证实了社会化互动的存在,提升了模型对疏散系统的描述能力,仿真结果更为可信。进一步显示了模型驱动理论与计算机仿真技术在建筑设计、应急方案制定、公共安全与危机管理等领域的先进性与可行性。展开更多
针对智能交通领域多车协同驾驶中存在的通信信息乱序、丢包问题,研究网联式自主驾驶车辆协同控制技术,建立基于零阶保持(Zero Order Hold,ZOH)信息处理机制的自主驾驶车队控制模型,通过非线性系统状态估计算法进行延迟补偿,使得车队控...针对智能交通领域多车协同驾驶中存在的通信信息乱序、丢包问题,研究网联式自主驾驶车辆协同控制技术,建立基于零阶保持(Zero Order Hold,ZOH)信息处理机制的自主驾驶车队控制模型,通过非线性系统状态估计算法进行延迟补偿,使得车队控制模型在复杂汽车行驶环境下保持有效。通过构建由多辆实车组成的网联式自主驾驶车队,在封闭道路环境下进行协同驾驶编队测试,结合网络传输及传感器数据进行模型仿真,验证了模型在实车编队环境下的稳定性、有效性和实用性。展开更多
In paddy soils of Thailand, the addition of organic matter （OM） is used to efficiently limit the effect of salinity on rice culture and production. OM used as an amendment and fertilizer promotes the reduced conditi...In paddy soils of Thailand, the addition of organic matter （OM） is used to efficiently limit the effect of salinity on rice culture and production. OM used as an amendment and fertilizer promotes the reduced condition and increases iron solubilization without provoking ferrous toxicity. In this study, the intricate biogeochemical role of iron-reducing bacteria （IRB） involved in the quality of water and soil of paddy fields, particularly when the paddy fields were subject to salinity and organic matter addition, were studied in paddy fields of Thailand. The results demonstrated that the addition of OM increased the proliferation of cultivable IRB and their specific activity. Cultivable IRB communities decreased in the presence of salt. The presence of salt modified the structure of the bacterial populations by favoring the development of alkaline and moderately halophilic bacteria （Virgibacillus spp., Occanobacillus spp., and PaenibaciUus spp.）. The paddy soils studied contained very diversified （halosensitive, halotolerant, and halophilic） IRB populations that could be adapted to a variety of salinity conditions （0-90 g L-1 NaCI） using different organic substrates （glucose, acetate, and soil organic matter） to maintain significant activities under extreme conditions of salinity. The rhizosphere of rice stimulated IRB community growth without organic matter, whereas organic matter addition limited the rhizosphere effect on IRB cultivable number in saline condition. The interactive action of salinity and organic amendment had a negative impact on the rhizosphere effect. The presence of specific iron-reducing populations （fermentative, iron-respiring, anaerobic, and facultative anaerobic）, having different behaviors under salt and redox stresses, appeared to be a key factor that contributed to the control or enhancement of the quality of water and soil in paddy fields.展开更多
The objective of this paper concerns at first the motivation and the method of Shor’s algorithm including remarks on quantum computing introducing an algorithmic description of the method.The corner stone of the Shor...The objective of this paper concerns at first the motivation and the method of Shor’s algorithm including remarks on quantum computing introducing an algorithmic description of the method.The corner stone of the Shor’s algorithm is the modular exponentiation that is themost computational component(in time and space).A linear depth unit based on phase estimation is introduced and a description of a generic version of a modular multiplier based on phases is introduced to build block of a gates to efficient modular exponentiation circuit.Our proposal includes numerical experiments achieved on both the IBM simulator using the Qiskit library and on quantum physical optimizers provided by IBM.The shor’s algorithm based on phase estimation succeeds in factoring integer numbers with more than 35 digits using circuits with about 100 qubits.展开更多
Mass renovation goals aimed at energy savings on a national scale require a significant level of public financial commitment.To identify target buildings,decision-makers need a thorough understanding of energy perform...Mass renovation goals aimed at energy savings on a national scale require a significant level of public financial commitment.To identify target buildings,decision-makers need a thorough understanding of energy performance.Energy Performance Certificates(EPC)provide information about areas of space,such as land plots or a building’s footprint,without specifying exact locations.They cover only a fraction of dwellings.This paper demonstrates that learning from observed EPCs to predict missing ones at the building level can be viewed as a spatial interpolation problem with uncertainty both on input and output variables.The Kriging methodology is applied to random fields observed at random locations to determine the Best Linear Unbiased Predictor(BLUP).Although the Gaussian setting is lost,conditional moments can still be derived.Covariates are admissible,even with missing observations.We present applications using both simulated and real data,with a specific case study of a city in France serving as an example.展开更多
We present HiLLS(High Level Language for System Specification),a graphical formalism that allows to specify Discrete Event System(DES)models for analysis using methodologies like simulation,formal methods and enactmen...We present HiLLS(High Level Language for System Specification),a graphical formalism that allows to specify Discrete Event System(DES)models for analysis using methodologies like simulation,formal methods and enactment.HiLLS’syntax is built from the integration of concepts from System Theory and Software Engineering aided by simple concrete notations to describe the structural and behavioral aspects of DESs.This paper provides the syntax of HiLLS and its simulation semantics which is based on the Discrete Event System Specification(DEVS)formalism.From DEVS-based Modeling and Simulation(M&S)perspective,HiLLS is a platform-independent visual language with generic expressions that can serve as a front-end for most existing DEVS-based simulation environments with the aid of Model-Driven Engineering(MDE)techniques.It also suggests ways to fill some gaps in existing DEVS-based visual formalisms that inhibit complete specification of the behavior of complex DESs.We provide a case study to illustrate the core features of the language.展开更多
The aim of this paper is to give an overview on models and methods used to solve tactical planning problems. The modeling and the elaboration of the well-know tactical planning problems （master planning ＆ scheduling...The aim of this paper is to give an overview on models and methods used to solve tactical planning problems. The modeling and the elaboration of the well-know tactical planning problems （master planning ＆ scheduling, material requirement planning and multi-site planning） are discussed. These problems are modeled from two ＂lot sizing＂ models called the Capacitated Lot Sizing Problem （CLSP） and Multi Level Capacitated Lot Sizing Problem （MLCLSP）. From both models, a lot of extensions has been proposed in the literature. The purpose of this paper is twofold： first, classifications of the CLSP and MLCLSP as well as their extensions are given. For each model, the major scientific contributions are mentioned. These classifications made from seventy papers give an overview of ＂lot sizing＂ models dedicated to the MPS, MRP and Multi-site and show the diversity of models. Second, from a classification, an analysis of methods used for each model is given. The instance size, best gap and reference for gap computation are given for each contribution, This work can be used to elaborate an optimization tool for tactical planning problematic such as Advanced Planning System.展开更多
Artificial neural networks(ANNs),a branch of artificial intelligence,has become a very interesting domain since the eighties when back-propagation(BP)learning algorithm for multilayer feed-forward architecture was int...Artificial neural networks(ANNs),a branch of artificial intelligence,has become a very interesting domain since the eighties when back-propagation(BP)learning algorithm for multilayer feed-forward architecture was introduced to solve nonlinear problems.It is used extensively to solve complex nonalgorithmic problems such as prediction,pattern recognition and clustering.However,in the context of a holistic study,there may be a need to integrate ANN with other models developed in various paradigms to solve a problem.In this paper,we suggest discrete event system specification(DEVS)be used as a model of computation(MoC)to make ANN models interoperable with other models(since all discrete event models can be expressed in DEVS,and continuous models can be approximated by DEVS).By combining ANN and DEVS,we can model the complex configuration of ANNs and express its internal workings.Therefore,we are extending the DEVS-based ANN proposed by Toma et al.[A new DEVS-based generic art-ficial neural network modeling approach,The 23rd European Modeling and Simulation Symp.(Simulation in Industry),Rome,Italy,2011]for comparing multiple configuration parameters and learning algorithms and also to do prediction.The DEVS models are described using the high level language for system specification(HiLLS),[Ma¨ıga et al.,A new approach to modeling dynamic structure systems,The 29th European Modeling and Simulation Symp.(Simulation in Industry),Leicester,United Kingdom,2015]a graphical modeling language for clarity.The developed platform is a tool to transform ANN models into DEVS computational models,making them more reusable and more interoperable in the context of larger multi-perspective modeling and simulation(MAS).展开更多
We propose a MATLAB implementation of the P1 finite element method for the numerical solutions of the Poisson problem and the linear elasticity problem in two-dimensional(2D)and three-dimensional(3D).The code consists...We propose a MATLAB implementation of the P1 finite element method for the numerical solutions of the Poisson problem and the linear elasticity problem in two-dimensional(2D)and three-dimensional(3D).The code consists of vectorized(and short)assembling functions for the matrices(mass and stiffness)and the right-hand sides.Since for the P1 finite element,the element mass matrix and right-hand side are simple,the implementation uses only the MATLAB function sparse on the elements volume.For the stiffness matrix,to obtain a MATLAB implementation close to the standard form,cell-arrays are used to store the gradients of the element basis functions.The assembling procedure can then use matrix/vector products on small size cell-arrays.Numerical experiments show that our implementation is fast,scalable with respect to time,and outperforms existing vectorized MATLAB FEM codes.展开更多
文摘Cancer is a formidable andmultifaceted disease driven by genetic aberrations and metabolic disruptions.Around 19% of cancer-related deaths worldwide are attributable to lung and colon cancer,which is also the top cause of death worldwide.The malignancy has a terrible 5-year survival rate of 19%.Early diagnosis is critical for improving treatment outcomes and survival rates.The study aims to create a computer-aided diagnosis(CAD)that accurately diagnoses lung disease by classifying histopathological images.It uses a publicly accessible dataset that includes 15,000 images of benign,malignant,and squamous cell carcinomas in the lung.In addition,this research employs multiscale processing to extract relevant image features and conducts a comprehensive comparative analysis using four Convolutional Neural Network(CNN)based on pre-trained models such as AlexNet,VGG(Visual Geometry Group)16,ResNet-50,and VGG19,after hyper-tuning these models by optimizing factors such as batch size,learning rate,and epochs.The proposed(CNN+VGG19)model achieves the highest accuracy of 99.04%.This outstanding performance demonstrates the potential of the CAD system in accurately classifying lung cancer histopathological images.This study contributes significantly to the creation of a more precise CNN-based model for lung cancer identification,giving researchers and medical professionals in this vital sector a useful tool using advanced deep learning techniques and publicly available datasets.
文摘The paper presents a novel quantum method for addressing two fundamental routing problems:the Traveling Salesman Problem(TSP)and theVehicle Routing Problem(VRP),both central to routing challenges.The proposed method,named the Indirect Quantum Approximate Optimization Algorithm(IQAOA),leverages an indirect solution representation using ranking.Our contribution focuses on two main areas:1)the indirect representation of solutions,and 2)the integration of this representation into an extended version of QAOA,called IQAOA.This approach offers an alternative to QAOA and includes the following components:1)a quantum parameterized circuit designed to simulate string vectors on a quantum processor,2)a classical meta-optimization method executed on a classical computer,and 3)the computation of the average cost for each string vector,achieved through a well-established algorithm from the operations research community tailored to the specific problem.IQAOA provides an efficient means to address quantum optimization problems by combining quantum and classical computation methods.Its primary advantage lies in deriving a quantum circuit that requires significantly fewer gates,making it suitable for execution on current noisy quantum computing platforms.Through numerical experiments employing IQAOA,we successfully solved instances of the 10-customer Traveling Salesman Problem(TSP)using the IBM simulator.To our knowledge,this is the largest application of a QAOA-based approach to solving the TSP.Additionally,IQAOA enables the resolution of the Vehicle Routing Problem(VRP)by leveraging the Split algorithm,which transforms a TSP permutation into a corresponding VRP solution.
文摘针对应急疏散行为受社会化属性驱动而表现出不确定性、互动关系复杂等特征,基于Cell-DEVS语言构建人员疏散系统仿真模型,模型在强化描述行人运动能力的基础上,引入环境熟悉程度、个体视野、沟通与引导及速率区块等社会化互动因素,旨在优化模型算法,完善个体与环境,个体之间互动关系的描述。RESTful web service远程仿真结果进一步证实了社会化互动的存在,提升了模型对疏散系统的描述能力,仿真结果更为可信。进一步显示了模型驱动理论与计算机仿真技术在建筑设计、应急方案制定、公共安全与危机管理等领域的先进性与可行性。
文摘针对智能交通领域多车协同驾驶中存在的通信信息乱序、丢包问题,研究网联式自主驾驶车辆协同控制技术,建立基于零阶保持(Zero Order Hold,ZOH)信息处理机制的自主驾驶车队控制模型,通过非线性系统状态估计算法进行延迟补偿,使得车队控制模型在复杂汽车行驶环境下保持有效。通过构建由多辆实车组成的网联式自主驾驶车队,在封闭道路环境下进行协同驾驶编队测试,结合网络传输及传感器数据进行模型仿真,验证了模型在实车编队环境下的稳定性、有效性和实用性。
基金Supported by the ECCO Program of the National Institute for Earth Sciences and Astronomy (INSU)French National Center for Scientific Research (CNRS)+1 种基金the Collaboration between the Institute for Research and Development (IRD)the Land Department and Development (LDD) of Thailand International Cooperation Agency (TICA)
文摘In paddy soils of Thailand, the addition of organic matter （OM） is used to efficiently limit the effect of salinity on rice culture and production. OM used as an amendment and fertilizer promotes the reduced condition and increases iron solubilization without provoking ferrous toxicity. In this study, the intricate biogeochemical role of iron-reducing bacteria （IRB） involved in the quality of water and soil of paddy fields, particularly when the paddy fields were subject to salinity and organic matter addition, were studied in paddy fields of Thailand. The results demonstrated that the addition of OM increased the proliferation of cultivable IRB and their specific activity. Cultivable IRB communities decreased in the presence of salt. The presence of salt modified the structure of the bacterial populations by favoring the development of alkaline and moderately halophilic bacteria （Virgibacillus spp., Occanobacillus spp., and PaenibaciUus spp.）. The paddy soils studied contained very diversified （halosensitive, halotolerant, and halophilic） IRB populations that could be adapted to a variety of salinity conditions （0-90 g L-1 NaCI） using different organic substrates （glucose, acetate, and soil organic matter） to maintain significant activities under extreme conditions of salinity. The rhizosphere of rice stimulated IRB community growth without organic matter, whereas organic matter addition limited the rhizosphere effect on IRB cultivable number in saline condition. The interactive action of salinity and organic amendment had a negative impact on the rhizosphere effect. The presence of specific iron-reducing populations （fermentative, iron-respiring, anaerobic, and facultative anaerobic）, having different behaviors under salt and redox stresses, appeared to be a key factor that contributed to the control or enhancement of the quality of water and soil in paddy fields.
文摘The objective of this paper concerns at first the motivation and the method of Shor’s algorithm including remarks on quantum computing introducing an algorithmic description of the method.The corner stone of the Shor’s algorithm is the modular exponentiation that is themost computational component(in time and space).A linear depth unit based on phase estimation is introduced and a description of a generic version of a modular multiplier based on phases is introduced to build block of a gates to efficient modular exponentiation circuit.Our proposal includes numerical experiments achieved on both the IBM simulator using the Qiskit library and on quantum physical optimizers provided by IBM.The shor’s algorithm based on phase estimation succeeds in factoring integer numbers with more than 35 digits using circuits with about 100 qubits.
文摘Mass renovation goals aimed at energy savings on a national scale require a significant level of public financial commitment.To identify target buildings,decision-makers need a thorough understanding of energy performance.Energy Performance Certificates(EPC)provide information about areas of space,such as land plots or a building’s footprint,without specifying exact locations.They cover only a fraction of dwellings.This paper demonstrates that learning from observed EPCs to predict missing ones at the building level can be viewed as a spatial interpolation problem with uncertainty both on input and output variables.The Kriging methodology is applied to random fields observed at random locations to determine the Best Linear Unbiased Predictor(BLUP).Although the Gaussian setting is lost,conditional moments can still be derived.Covariates are admissible,even with missing observations.We present applications using both simulated and real data,with a specific case study of a city in France serving as an example.
文摘We present HiLLS(High Level Language for System Specification),a graphical formalism that allows to specify Discrete Event System(DES)models for analysis using methodologies like simulation,formal methods and enactment.HiLLS’syntax is built from the integration of concepts from System Theory and Software Engineering aided by simple concrete notations to describe the structural and behavioral aspects of DESs.This paper provides the syntax of HiLLS and its simulation semantics which is based on the Discrete Event System Specification(DEVS)formalism.From DEVS-based Modeling and Simulation(M&S)perspective,HiLLS is a platform-independent visual language with generic expressions that can serve as a front-end for most existing DEVS-based simulation environments with the aid of Model-Driven Engineering(MDE)techniques.It also suggests ways to fill some gaps in existing DEVS-based visual formalisms that inhibit complete specification of the behavior of complex DESs.We provide a case study to illustrate the core features of the language.
文摘The aim of this paper is to give an overview on models and methods used to solve tactical planning problems. The modeling and the elaboration of the well-know tactical planning problems （master planning ＆ scheduling, material requirement planning and multi-site planning） are discussed. These problems are modeled from two ＂lot sizing＂ models called the Capacitated Lot Sizing Problem （CLSP） and Multi Level Capacitated Lot Sizing Problem （MLCLSP）. From both models, a lot of extensions has been proposed in the literature. The purpose of this paper is twofold： first, classifications of the CLSP and MLCLSP as well as their extensions are given. For each model, the major scientific contributions are mentioned. These classifications made from seventy papers give an overview of ＂lot sizing＂ models dedicated to the MPS, MRP and Multi-site and show the diversity of models. Second, from a classification, an analysis of methods used for each model is given. The instance size, best gap and reference for gap computation are given for each contribution, This work can be used to elaborate an optimization tool for tactical planning problematic such as Advanced Planning System.
基金funding agency in the public,commercial or not-for-profit sectors.
文摘Artificial neural networks(ANNs),a branch of artificial intelligence,has become a very interesting domain since the eighties when back-propagation(BP)learning algorithm for multilayer feed-forward architecture was introduced to solve nonlinear problems.It is used extensively to solve complex nonalgorithmic problems such as prediction,pattern recognition and clustering.However,in the context of a holistic study,there may be a need to integrate ANN with other models developed in various paradigms to solve a problem.In this paper,we suggest discrete event system specification(DEVS)be used as a model of computation(MoC)to make ANN models interoperable with other models(since all discrete event models can be expressed in DEVS,and continuous models can be approximated by DEVS).By combining ANN and DEVS,we can model the complex configuration of ANNs and express its internal workings.Therefore,we are extending the DEVS-based ANN proposed by Toma et al.[A new DEVS-based generic art-ficial neural network modeling approach,The 23rd European Modeling and Simulation Symp.(Simulation in Industry),Rome,Italy,2011]for comparing multiple configuration parameters and learning algorithms and also to do prediction.The DEVS models are described using the high level language for system specification(HiLLS),[Ma¨ıga et al.,A new approach to modeling dynamic structure systems,The 29th European Modeling and Simulation Symp.(Simulation in Industry),Leicester,United Kingdom,2015]a graphical modeling language for clarity.The developed platform is a tool to transform ANN models into DEVS computational models,making them more reusable and more interoperable in the context of larger multi-perspective modeling and simulation(MAS).
文摘We propose a MATLAB implementation of the P1 finite element method for the numerical solutions of the Poisson problem and the linear elasticity problem in two-dimensional(2D)and three-dimensional(3D).The code consists of vectorized(and short)assembling functions for the matrices(mass and stiffness)and the right-hand sides.Since for the P1 finite element,the element mass matrix and right-hand side are simple,the implementation uses only the MATLAB function sparse on the elements volume.For the stiffness matrix,to obtain a MATLAB implementation close to the standard form,cell-arrays are used to store the gradients of the element basis functions.The assembling procedure can then use matrix/vector products on small size cell-arrays.Numerical experiments show that our implementation is fast,scalable with respect to time,and outperforms existing vectorized MATLAB FEM codes.
