A refractory gold concentrate with 19% arsenic was treated by a mixed moderately thermophiles in an airlift bioreactor through an adaptation protocol. The moderately thermophiles could respond well to 20%(w/v) pulp de...A refractory gold concentrate with 19% arsenic was treated by a mixed moderately thermophiles in an airlift bioreactor through an adaptation protocol. The moderately thermophiles could respond well to 20%(w/v) pulp density with less than 10% loss of productivity, and resist arsenic up to 15 g/L. There were a lot of jarosite, arsenolite and sulfur, but not scorodite and ferric arsenate in the bioleached residue. Jarosite passivation and lower sulfur-oxidizing activity of the cells due to the toxicity of the high concentrations of soluble arsenic and iron ions at low p H value should mainly response for the incomplete extraction at high pulp density. The initial bacterial community did not change in nature except for new found P aeruginosa ANSC, but sulfur-oxidizing microorganisms have been dominant microorganisms after a long time of adaptation. Pseudomonas aeruginosa originating from the gold concentrate should be closely relative to the metabolism of the organic matters contained in the refractory gold concentrate.展开更多
Yes, we perceive that the environment in which comp an ies operate, is changing at higher speeds then before. Globalisation, higher inn ovation rates, customisation, more intense competition, technological developmen ...Yes, we perceive that the environment in which comp an ies operate, is changing at higher speeds then before. Globalisation, higher inn ovation rates, customisation, more intense competition, technological developmen ts account for these changes effecting the way industrial companies operate and eventually their structures and processes. Companies have to adapt themselves to these changes. The question arose whether the approach of the Section Industria l Organisation and Management that it has practised for redesign of processes an d organisational structures also withholds in this era of continuous change. Sec ondly, firms are also looking for contingencies in processes and structures to i mprove their chances for survival. These two questions into the processes and st ructures within the firm that it needs to support adaptation to the ever-changi ng environment direct this research. Industrial companies will have to increase to their Complexity Handling Capabili ty, the ability to cope with changes in its environment and imposed complexity p ouring in from the environment. To do so, they might decrease their internal com plexity through redefining their organisations and product structure. The effect of these measurements seems limited; more might be won by learning to increase its base of capabilities. The increase of capabilities holds parallels to the de velopment of species in biology and paleontology for which two models exist: the punctuated equilibrium and the phyletic gradualism. The punctuated equilibr ium supposes that periods of turmoil are interchanged by periods of fermentation giving rise to new variants and products (for companies). The phyletic graduali sm relies on the development of characteristics in species that are initially ha rd to detect but will lead at the end to new species. Whatever might be true for biology and palaeontology, these two models appear as a possibility for cla ssifying the theories of organisational change. Also, these theories put forward insights in the development of organisations that stretch beyond the classical insights on the adaptation of organisations based on one-time interventions ass uming balance between demands from the environment and internal structure. Little research has been done so far in this field of adaptation of companies to the dynamics of the environment. Most literature does not address the internal processes and structures necessary for coping with change. This paper will prese nt initial findings of case studies of graduation theses that took place to generate data on the validity of the evolutionary models. This way the research should not only lead to a theoretical framework but also to practical implicatio ns for industrial companies.展开更多
Mitigation and adaptation are two principle strategies for managing human-induced climate change. Agriculture plays a duet role in climate change. It has been a major source of greenhouse gases to the atmosphere. It i...Mitigation and adaptation are two principle strategies for managing human-induced climate change. Agriculture plays a duet role in climate change. It has been a major source of greenhouse gases to the atmosphere. It is also one of the sectors most vulnerable to the risks and impacts of global climate change. This paper first indentified the mitigative and adaptative options and potential in agriculture, then addressed the integrated analysis of mitigation and adaptation and its benefits for agriculture. Finally, it discussed the implications to Chinese agriculture in dealing with the global climate change.展开更多
Climate change is one of the most significant environment issues in the whole world today. And it is one of the most complex challenges of the humanities faced in the 21st century. Climate Change is impacted on our gl...Climate change is one of the most significant environment issues in the whole world today. And it is one of the most complex challenges of the humanities faced in the 21st century. Climate Change is impacted on our global; nobody can avoid the influence of climate change. The local adaptation strategies on climate change are very important to contribute the mitigation and poverty stricken situation, both in China and in the world. We chose a typical China＇s province as a case to analyze the impact of climate change on the region （such as agricultural, natural ecosystems, water resources, as well as local people healthy condition）, and how the local government and local residences face the impact of the climate change influence, and summarized several strategies on climate change of the area in a sustainable development way.展开更多
It would be well to note that in the absence of clear data about the formation of adaptation systems,or mechanisms of their occurrence,all that is recognized is the realization of the micro evolutionary processes.Ther...It would be well to note that in the absence of clear data about the formation of adaptation systems,or mechanisms of their occurrence,all that is recognized is the realization of the micro evolutionary processes.There is no well-defined connection between information exchange and formation展开更多
The problem on stabilization for the system with distributed delays is researched. The distributed time-delay under consideration is assumed to be a constant time-delay, but not known exactly. A design method is propo...The problem on stabilization for the system with distributed delays is researched. The distributed time-delay under consideration is assumed to be a constant time-delay, but not known exactly. A design method is proposed for a memory proportional and integral （PI） feedback controller with adaptation to distributed time-delay. The feedback controller with memory simultaneously contains the current state and the past distributed information of the addressed systems. The design for adaptation law to distributed delay is very concise. The controller can be derived by solving a set of linear matrix inequalities （LMIs）. Two numerical examples are given to illustrate the effectiveness of the design method.展开更多
One of the challenges the world is facing today is global climate change and its associated impacts. Uganda is a climate sensitive country with over 90% of the population dependent on climate sensitive sectors.Gradual...One of the challenges the world is facing today is global climate change and its associated impacts. Uganda is a climate sensitive country with over 90% of the population dependent on climate sensitive sectors.Gradual and sudden variations in climatic parameters will therefore render the livelihoods of Ugandans very vulnerable.A number of approaches to enhance the resilience of communities to展开更多
The explanation and simulation of the natural and artificial intelligence are the central goals of the studies of Neuroscience, Psychology, Artificial Intelligence and Cognitive Science. This paper first gives an intr...The explanation and simulation of the natural and artificial intelligence are the central goals of the studies of Neuroscience, Psychology, Artificial Intelligence and Cognitive Science. This paper first gives an introduction to the core topics and approaches in the study. Then, GAF--a general adaptive framework for neural system is proposed. Interdisciplinary discussions around the adaptation of the human nervous system are presented. Rules describing the theory of adaptation of the nervous system are provided.展开更多
Different receptors have evolved in organisms to sense different stimuli in their surroundings.The interaction among the receptors can significantly increase sensory sensitivity and adaptation precision.To study the i...Different receptors have evolved in organisms to sense different stimuli in their surroundings.The interaction among the receptors can significantly increase sensory sensitivity and adaptation precision.To study the influence of interaction among different types of chemoreceptors on the adaptation rate in the bacterial chemotaxis signaling network,we systematically compared the adaptation time between the wild-type strain expressing mixed types of receptors and the mutant strain expressing only Tar receptors(namely,the Tar-only strain)under stepwise addition of different concentrations of L-aspartate using FRET(Förster resonance energy transfer)and bead assays.We find that the wild type exhibits faster adaptation than the mutant under the same concentration of saturated stimulus.In contrast,the wild type exhibits slower adaptation than the mutant under unsaturated stimuli that induce the same magnitude of response,and this is independent of the level of receptor expression.The same result is obtained for the network relaxation time by monitoring the steady-state rotational signal of the flagellar motors.By simulating bacterial chemotaxis with different adaptation rates in a stable gradient of chemoattractants,we confirm that the interaction of different types of receptors can effectively promote chemotaxis of Escherichia coli under a stable spatial gradient of attractants while ensuring minimum noise in the cell position distribution.展开更多
The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fau...The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different conditions.To address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault diagnosis.Specifically,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two domains.To improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault categories.In addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test result.The proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.展开更多
四川大学计算机学院学生团队在大规模语言模型参数高效微调系统研究方向取得重要进展,其研究成果“mLoRA:Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs”在国际数据库学术会议VLDB 2025 Rese...四川大学计算机学院学生团队在大规模语言模型参数高效微调系统研究方向取得重要进展,其研究成果“mLoRA:Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs”在国际数据库学术会议VLDB 2025 Research Track正式发表。VLDB(International Conference on Very Large Data Bases)是数据库领域的重要国际学术会议之一,涵盖数据库管理系统、数据密集型系统与大规模数据处理等方向。该工作已在多个国内外互联网企业的实际生产环境中部署应用,并获得一项中国发明专利和一项美国发明专利的受理。展开更多
We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponen...We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.展开更多
In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantl...In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantly degrades image quality.Traditional denoising methods,typically based on filter techniques,often face challenges related to inefficiency and limited adaptability.To address these limitations,this study proposes a novel SAR image denoising algorithm based on an enhanced residual network architecture,with the objective of enhancing the utility of SAR imagery in complex electromagnetic environments.The proposed algorithm integrates residual network modules,which directly process the noisy input images to generate denoised outputs.This approach not only reduces computational complexity but also mitigates the difficulties associated with model training.By combining the Transformer module with the residual block,the algorithm enhances the network's ability to extract global features,offering superior feature extraction capabilities compared to CNN-based residual modules.Additionally,the algorithm employs the adaptive activation function Meta-ACON,which dynamically adjusts the activation patterns of neurons,thereby improving the network's feature extraction efficiency.The effectiveness of the proposed denoising method is empirically validated using real SAR images from the RSOD dataset.The proposed algorithm exhibits remarkable performance in terms of EPI,SSIM,and ENL,while achieving a substantial enhancement in PSNR when compared to traditional and deep learning-based algorithms.The PSNR performance is enhanced by over twofold.Moreover,the evaluation of the MSTAR SAR dataset substantiates the algorithm's robustness and applicability in SAR denoising tasks,with a PSNR of 25.2021 being attained.These findings underscore the efficacy of the proposed algorithm in mitigating speckle noise while preserving critical features in SAR imagery,thereby enhancing its quality and usability in practical scenarios.展开更多
Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise re...Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational resource.This is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain size.In this work,a variable-domain-size adaptive mesh enlargement(vAME)method is developed based on the proposed adaptive mesh enlargement(AME)method for modeling multi-explosives explosion problems.The vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions,rather than in all directions as in AME method.A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of accuracy.An estimate of speedup ratio is analyzed for further efficiency comparison.Several large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave,reflected wave,and Mach wave.Additionally,the vAME method is employed to validate the accuracy,as well as to investigate the performance of the fluid field and shock wave propagation,considering explosive quantities ranging from 1 to 5 while maintaining a constant total mass.The results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical simulations.The vAME method yields a competitive efficiency,increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method,respectively.It indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with significant differences in computational domain size.展开更多
Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncerta...Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.展开更多
In complex environments such as high dynamics and weak signals,a satellite signal compensation method based on prefabricated trajectory assistance and an improved adaptive Kalman filter is proposed for a 155 mm differ...In complex environments such as high dynamics and weak signals,a satellite signal compensation method based on prefabricated trajectory assistance and an improved adaptive Kalman filter is proposed for a 155 mm differential rotating rear-body control-guided projectile to address the situation of satellite signal flickering and loss in projectile navigation systems due to environmental limitations.First,establish the system state and measurement equation when receiving satellite signals normally.Second,a seven-degree-of-freedom external ballistic model is constructed,and the ideal trajectory output from the ballistic model is used to provide the virtual motion state of the projectile,which is input into a filter as a substitute observation when satellite signals are lost.Finally,an adaptive Kalman filter(AKF)is designed,the proposed adaptive Kalman filter can accurately adjust the estimation error covariance matrix and Kalman gain in real-time based on information covariance mismatch.The simulation results show that compared to the classical Kalman filter,it can reduce the average positioning error by more than 38.21%in the case of short-term and full-range loss of satellite signals,providing a new idea for the integrated navigation of projectiles with incomplete information under the condition of satellite signal loss.展开更多
Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the phy...Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.展开更多
基金Project(2010CB630903)supported by the National Basic Research Program of ChinaProject(31200382)supported by the Chinese Science Foundation for Distinguished Group,China
文摘A refractory gold concentrate with 19% arsenic was treated by a mixed moderately thermophiles in an airlift bioreactor through an adaptation protocol. The moderately thermophiles could respond well to 20%(w/v) pulp density with less than 10% loss of productivity, and resist arsenic up to 15 g/L. There were a lot of jarosite, arsenolite and sulfur, but not scorodite and ferric arsenate in the bioleached residue. Jarosite passivation and lower sulfur-oxidizing activity of the cells due to the toxicity of the high concentrations of soluble arsenic and iron ions at low p H value should mainly response for the incomplete extraction at high pulp density. The initial bacterial community did not change in nature except for new found P aeruginosa ANSC, but sulfur-oxidizing microorganisms have been dominant microorganisms after a long time of adaptation. Pseudomonas aeruginosa originating from the gold concentrate should be closely relative to the metabolism of the organic matters contained in the refractory gold concentrate.
文摘Yes, we perceive that the environment in which comp an ies operate, is changing at higher speeds then before. Globalisation, higher inn ovation rates, customisation, more intense competition, technological developmen ts account for these changes effecting the way industrial companies operate and eventually their structures and processes. Companies have to adapt themselves to these changes. The question arose whether the approach of the Section Industria l Organisation and Management that it has practised for redesign of processes an d organisational structures also withholds in this era of continuous change. Sec ondly, firms are also looking for contingencies in processes and structures to i mprove their chances for survival. These two questions into the processes and st ructures within the firm that it needs to support adaptation to the ever-changi ng environment direct this research. Industrial companies will have to increase to their Complexity Handling Capabili ty, the ability to cope with changes in its environment and imposed complexity p ouring in from the environment. To do so, they might decrease their internal com plexity through redefining their organisations and product structure. The effect of these measurements seems limited; more might be won by learning to increase its base of capabilities. The increase of capabilities holds parallels to the de velopment of species in biology and paleontology for which two models exist: the punctuated equilibrium and the phyletic gradualism. The punctuated equilibr ium supposes that periods of turmoil are interchanged by periods of fermentation giving rise to new variants and products (for companies). The phyletic graduali sm relies on the development of characteristics in species that are initially ha rd to detect but will lead at the end to new species. Whatever might be true for biology and palaeontology, these two models appear as a possibility for cla ssifying the theories of organisational change. Also, these theories put forward insights in the development of organisations that stretch beyond the classical insights on the adaptation of organisations based on one-time interventions ass uming balance between demands from the environment and internal structure. Little research has been done so far in this field of adaptation of companies to the dynamics of the environment. Most literature does not address the internal processes and structures necessary for coping with change. This paper will prese nt initial findings of case studies of graduation theses that took place to generate data on the validity of the evolutionary models. This way the research should not only lead to a theoretical framework but also to practical implicatio ns for industrial companies.
文摘Mitigation and adaptation are two principle strategies for managing human-induced climate change. Agriculture plays a duet role in climate change. It has been a major source of greenhouse gases to the atmosphere. It is also one of the sectors most vulnerable to the risks and impacts of global climate change. This paper first indentified the mitigative and adaptative options and potential in agriculture, then addressed the integrated analysis of mitigation and adaptation and its benefits for agriculture. Finally, it discussed the implications to Chinese agriculture in dealing with the global climate change.
文摘Climate change is one of the most significant environment issues in the whole world today. And it is one of the most complex challenges of the humanities faced in the 21st century. Climate Change is impacted on our global; nobody can avoid the influence of climate change. The local adaptation strategies on climate change are very important to contribute the mitigation and poverty stricken situation, both in China and in the world. We chose a typical China＇s province as a case to analyze the impact of climate change on the region （such as agricultural, natural ecosystems, water resources, as well as local people healthy condition）, and how the local government and local residences face the impact of the climate change influence, and summarized several strategies on climate change of the area in a sustainable development way.
文摘It would be well to note that in the absence of clear data about the formation of adaptation systems,or mechanisms of their occurrence,all that is recognized is the realization of the micro evolutionary processes.There is no well-defined connection between information exchange and formation
基金supported by the National Natural Science Foundation of China (60804017 60835001+3 种基金 60904020 60974120)the Foundation of Doctor (20070286039 20070286001)
文摘The problem on stabilization for the system with distributed delays is researched. The distributed time-delay under consideration is assumed to be a constant time-delay, but not known exactly. A design method is proposed for a memory proportional and integral （PI） feedback controller with adaptation to distributed time-delay. The feedback controller with memory simultaneously contains the current state and the past distributed information of the addressed systems. The design for adaptation law to distributed delay is very concise. The controller can be derived by solving a set of linear matrix inequalities （LMIs）. Two numerical examples are given to illustrate the effectiveness of the design method.
文摘One of the challenges the world is facing today is global climate change and its associated impacts. Uganda is a climate sensitive country with over 90% of the population dependent on climate sensitive sectors.Gradual and sudden variations in climatic parameters will therefore render the livelihoods of Ugandans very vulnerable.A number of approaches to enhance the resilience of communities to
基金This work is partly supported by China 863 Project Foundation
文摘The explanation and simulation of the natural and artificial intelligence are the central goals of the studies of Neuroscience, Psychology, Artificial Intelligence and Cognitive Science. This paper first gives an introduction to the core topics and approaches in the study. Then, GAF--a general adaptive framework for neural system is proposed. Interdisciplinary discussions around the adaptation of the human nervous system are presented. Rules describing the theory of adaptation of the nervous system are provided.
基金supported by the Natural Science Foundation of Anhui Province(2008085QA31).
文摘Different receptors have evolved in organisms to sense different stimuli in their surroundings.The interaction among the receptors can significantly increase sensory sensitivity and adaptation precision.To study the influence of interaction among different types of chemoreceptors on the adaptation rate in the bacterial chemotaxis signaling network,we systematically compared the adaptation time between the wild-type strain expressing mixed types of receptors and the mutant strain expressing only Tar receptors(namely,the Tar-only strain)under stepwise addition of different concentrations of L-aspartate using FRET(Förster resonance energy transfer)and bead assays.We find that the wild type exhibits faster adaptation than the mutant under the same concentration of saturated stimulus.In contrast,the wild type exhibits slower adaptation than the mutant under unsaturated stimuli that induce the same magnitude of response,and this is independent of the level of receptor expression.The same result is obtained for the network relaxation time by monitoring the steady-state rotational signal of the flagellar motors.By simulating bacterial chemotaxis with different adaptation rates in a stable gradient of chemoattractants,we confirm that the interaction of different types of receptors can effectively promote chemotaxis of Escherichia coli under a stable spatial gradient of attractants while ensuring minimum noise in the cell position distribution.
文摘The ammunition loading system manipulator is susceptible to gear failure due to high-frequency,heavyload reciprocating motions and the absence of protective gear components.After a fault occurs,the distribution of fault characteristics under different loads is markedly inconsistent,and data is hard to label,which makes it difficult for the traditional diagnosis method based on single-condition training to generalize to different conditions.To address these issues,the paper proposes a novel transfer discriminant neural network(TDNN)for gear fault diagnosis.Specifically,an optimized joint distribution adaptive mechanism(OJDA)is designed to solve the distribution alignment problem between two domains.To improve the classification effect within the domain and the feature recognition capability for a few labeled data,metric learning is introduced to distinguish features from different fault categories.In addition,TDNN adopts a new pseudo-label training strategy to achieve label replacement by comparing the maximum probability of the pseudo-label with the test result.The proposed TDNN is verified in the experimental data set of the artillery manipulator device,and the diagnosis can achieve 99.5%,significantly outperforming other traditional adaptation methods.
文摘四川大学计算机学院学生团队在大规模语言模型参数高效微调系统研究方向取得重要进展,其研究成果“mLoRA:Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs”在国际数据库学术会议VLDB 2025 Research Track正式发表。VLDB(International Conference on Very Large Data Bases)是数据库领域的重要国际学术会议之一,涵盖数据库管理系统、数据密集型系统与大规模数据处理等方向。该工作已在多个国内外互联网企业的实际生产环境中部署应用,并获得一项中国发明专利和一项美国发明专利的受理。
基金supported by the National Natural Science Foundation of China(Grant No.11971486)。
文摘We consider a single server constant retrial queue,in which a state-dependent service policy is used to control the service rate.Customer arrival follows Poisson process,while service time and retrial time are exponential distributions.Whenever the server is available,it admits the retrial customers into service based on a first-come first-served rule.The service rate adjusts in real-time based on the retrial queue length.An iterative algorithm is proposed to numerically solve the personal optimal problem in the fully observable scenario.Furthermore,we investigate the impact of parameters on the social optimal threshold.The effectiveness of the results is illustrated by two examples.
文摘In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantly degrades image quality.Traditional denoising methods,typically based on filter techniques,often face challenges related to inefficiency and limited adaptability.To address these limitations,this study proposes a novel SAR image denoising algorithm based on an enhanced residual network architecture,with the objective of enhancing the utility of SAR imagery in complex electromagnetic environments.The proposed algorithm integrates residual network modules,which directly process the noisy input images to generate denoised outputs.This approach not only reduces computational complexity but also mitigates the difficulties associated with model training.By combining the Transformer module with the residual block,the algorithm enhances the network's ability to extract global features,offering superior feature extraction capabilities compared to CNN-based residual modules.Additionally,the algorithm employs the adaptive activation function Meta-ACON,which dynamically adjusts the activation patterns of neurons,thereby improving the network's feature extraction efficiency.The effectiveness of the proposed denoising method is empirically validated using real SAR images from the RSOD dataset.The proposed algorithm exhibits remarkable performance in terms of EPI,SSIM,and ENL,while achieving a substantial enhancement in PSNR when compared to traditional and deep learning-based algorithms.The PSNR performance is enhanced by over twofold.Moreover,the evaluation of the MSTAR SAR dataset substantiates the algorithm's robustness and applicability in SAR denoising tasks,with a PSNR of 25.2021 being attained.These findings underscore the efficacy of the proposed algorithm in mitigating speckle noise while preserving critical features in SAR imagery,thereby enhancing its quality and usability in practical scenarios.
基金supported by the National Natural Science Foundation of China(Grant Nos.12302435 and 12221002)。
文摘Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of areas.The utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational resource.This is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain size.In this work,a variable-domain-size adaptive mesh enlargement(vAME)method is developed based on the proposed adaptive mesh enlargement(AME)method for modeling multi-explosives explosion problems.The vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions,rather than in all directions as in AME method.A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of accuracy.An estimate of speedup ratio is analyzed for further efficiency comparison.Several large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave,reflected wave,and Mach wave.Additionally,the vAME method is employed to validate the accuracy,as well as to investigate the performance of the fluid field and shock wave propagation,considering explosive quantities ranging from 1 to 5 while maintaining a constant total mass.The results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical simulations.The vAME method yields a competitive efficiency,increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method,respectively.It indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with significant differences in computational domain size.
基金National Natural Science Foundation of China(62373102)Jiangsu Natural Science Foundation(BK20221455)Anhui Provincial Key Research and Development Project(2022i01020013)。
文摘Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.
基金funded by the National Natural Science Foundation of China (Grant No. 62471048)Open Fund Project of Beijing Key Laboratory of High Dynamic Navigation TechnologyKey Laboratory Fund Project of Modern Measurement and Control Technology, Ministry of Education
文摘In complex environments such as high dynamics and weak signals,a satellite signal compensation method based on prefabricated trajectory assistance and an improved adaptive Kalman filter is proposed for a 155 mm differential rotating rear-body control-guided projectile to address the situation of satellite signal flickering and loss in projectile navigation systems due to environmental limitations.First,establish the system state and measurement equation when receiving satellite signals normally.Second,a seven-degree-of-freedom external ballistic model is constructed,and the ideal trajectory output from the ballistic model is used to provide the virtual motion state of the projectile,which is input into a filter as a substitute observation when satellite signals are lost.Finally,an adaptive Kalman filter(AKF)is designed,the proposed adaptive Kalman filter can accurately adjust the estimation error covariance matrix and Kalman gain in real-time based on information covariance mismatch.The simulation results show that compared to the classical Kalman filter,it can reduce the average positioning error by more than 38.21%in the case of short-term and full-range loss of satellite signals,providing a new idea for the integrated navigation of projectiles with incomplete information under the condition of satellite signal loss.
基金supported by the National Natural Science Foundation of China under Grant 62301051.
文摘Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.
