Off-chip replacement （capacity and conflict） and coherent read misses in a distributed shared memory system cause execution to stall for hundreds of cycles. These off-chip replacement and coherent read misses are re...Off-chip replacement （capacity and conflict） and coherent read misses in a distributed shared memory system cause execution to stall for hundreds of cycles. These off-chip replacement and coherent read misses are recurring and forming sequences of two or more misses called streams. Prior streaming techniques ignored reordering of misses and not-recently-accessed streams while streaming data. In this paper, we present stream prefetcher design that can deal with both problems. Our stream prefetcher design utilizes stream waiting rooms to store not-recently-accessed streams. Stream waiting rooms help remove more off-chip misses. Using trace based simulation% our stream prefetcher design can remove 8% to 66% （on average 40%） and 17% to 63% （on average 39%） replacement and coherent read misses, respectively. Using cycle-accurate full-system simulation, our design gives speedups from 1.00 to 1.17 of princeton application repository for shared-memory computers （PARSEC） workloads running on a distributed shared memory system with the exception of dedup and swaptions workloads.展开更多
Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient manner.Identifying different types of brain tumors,including gliomas,meningiomas,p...Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient manner.Identifying different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI images.Current approaches predominantly rely on traditional machine learning and basic deep learning methods for image classification.These methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI images.Utilizing the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor classification.Our approach highlights a major advancement in employing sophisticated machine learning techniques within Computer Science and Engineering,showcasing a highly accurate framework with significant potential for healthcare technologies.The model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification report.This successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current methods.The integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider application.This research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.展开更多
Network failures are unavoidable and occur frequently.When the network fails,intra-domain routing protocols deploying on the Internet need to undergo a long convergence process.During this period,a large number of mes...Network failures are unavoidable and occur frequently.When the network fails,intra-domain routing protocols deploying on the Internet need to undergo a long convergence process.During this period,a large number of messages are discarded,which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers(ISP).Therefore,improving the availability of intra-domain routing is a trending research question to be solved.Industry usually employs routing protection algorithms to improve intra-domain routing availability.However,existing routing protection schemes compute as many backup paths as possible to reduce message loss due to network failures,which increases the cost of the network and impedes the methods deployed in practice.To address the issues,this study proposes an efficient routing protection algorithm based on optimized network topology(ERPBONT).ERPBONT adopts the optimized network topology to calculate a backup path with the minimum path coincidence degree with the shortest path for all source purposes.Firstly,the backup path with the minimum path coincidence with the shortest path is described as an integer programming problem.Then the simulated annealing algorithm ERPBONT is used to find the optimal solution.Finally,the algorithm is tested on the simulated topology and the real topology.The experimental results show that ERPBONT effectively reduces the path coincidence between the shortest path and the backup path,and significantly improves the routing availability.展开更多
Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressi...Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressing these shortcomings,thiswork presents a robust 15-level PackedUCell(PUC)inverter topology designed for renewable energy and grid-connected applications.The proposed systemintegrates a sensor less proportional-resonant(PR)controller with an advanced carrier-based pulse width modulation scheme.This approach efficiently balances capacitor voltage,minimizes steady-state error,and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation.Additionally,a novel switching algorithm simplifies the design and implementation,further lowering voltage stress across switches.Extensive simulation results validate the performance under various resistive and resistive-inductive load conditions,demonstrating compliance with IEEE-519 THD standards and robust operation under dynamic changes.The proposed sensorless PR-controlled 15-PUC inverter thus offers a compelling,cost-effective solution for efficient power conversion in next-generation renewable energy systems.展开更多
in this paper the algorithms for self-stabilizing communication protocols are studied.First some concepts and a formal method for describing theproposed algorithms are described,then an improved algorithm for achievin...in this paper the algorithms for self-stabilizing communication protocols are studied.First some concepts and a formal method for describing theproposed algorithms are described,then an improved algorithm for achieving globalstates is presented.The study shows that the improved algorithm can be appliedto obtain the global states in the case of a loss of cooperation of the different processes in the protocol,which can be used as a recovery point that will be used bythe following recovery procedure.Thus,the improved algorithm can be used toself-stabilize a communication protocol.Meanwhile,a recovery algorithm for selfstabilizing communication protocols is presented.After a failure is detected,allProcesses can eventually know the error.The recovery algorithm uses the contextualinformation exchanged during the progress of the protocol and recorded on the stablememory.The proof of correctness and analysis of complexity for these algorithmshave been made.The availability and efficiency of the algorithms have been verifiedby illustrating the example protocols.Finally,some conclusions and remarks aregiven.展开更多
Traffic classification is critical to effective network management. However, more and more pro- prietary, encrypted, and dynamic protocols make traditional traffic classification methods less effective. A Message and ...Traffic classification is critical to effective network management. However, more and more pro- prietary, encrypted, and dynamic protocols make traditional traffic classification methods less effective. A Message and Command Correlation （MCC） method was developed to identify interactive protocols （such as P2P file sharing protocols and Instant Messaging （IM） protocols） by session analyses. Unlike traditional packet-based classification approaches, this method exploits application session information by clustering packets into application messages which are used for further classification. The efficacy and accuracy of the MCC method was evaluated with real world traffic, including P2P file sharing protocols Thunder and Bit- Torrent, and IM protocols QQ and GTalk. The tests show that the false positive rate is less than 3% and the false negative rate is below 8%, and that MCC only needs to check 8.7% of the packets or 0.9% of the traffic. Therefore, this approach has great potential for accurately and quickly discovering new types of interactive application protocols.展开更多
基金supported by Higher Education Commission(Pakistan)National High Technology Research and Development Program of China(863 Program)(No.2008AA01A201)+1 种基金Natural Science Foundation of China(Nos.60833004 and 60970002)TNList Cross-discipline Foundation
文摘Off-chip replacement （capacity and conflict） and coherent read misses in a distributed shared memory system cause execution to stall for hundreds of cycles. These off-chip replacement and coherent read misses are recurring and forming sequences of two or more misses called streams. Prior streaming techniques ignored reordering of misses and not-recently-accessed streams while streaming data. In this paper, we present stream prefetcher design that can deal with both problems. Our stream prefetcher design utilizes stream waiting rooms to store not-recently-accessed streams. Stream waiting rooms help remove more off-chip misses. Using trace based simulation% our stream prefetcher design can remove 8% to 66% （on average 40%） and 17% to 63% （on average 39%） replacement and coherent read misses, respectively. Using cycle-accurate full-system simulation, our design gives speedups from 1.00 to 1.17 of princeton application repository for shared-memory computers （PARSEC） workloads running on a distributed shared memory system with the exception of dedup and swaptions workloads.
基金supported by the Researchers Supporting Program at King Saud University.Researchers Supporting Project number(RSPD2024R867),King Saud University,Riyadh,Saudi Arabia.
文摘Brain tumor is a global issue due to which several people suffer,and its early diagnosis can help in the treatment in a more efficient manner.Identifying different types of brain tumors,including gliomas,meningiomas,pituitary tumors,as well as confirming the absence of tumors,poses a significant challenge using MRI images.Current approaches predominantly rely on traditional machine learning and basic deep learning methods for image classification.These methods often rely on manual feature extraction and basic convolutional neural networks(CNNs).The limitations include inadequate accuracy,poor generalization of new data,and limited ability to manage the high variability in MRI images.Utilizing the EfficientNetB3 architecture,this study presents a groundbreaking approach in the computational engineering domain,enhancing MRI-based brain tumor classification.Our approach highlights a major advancement in employing sophisticated machine learning techniques within Computer Science and Engineering,showcasing a highly accurate framework with significant potential for healthcare technologies.The model achieves an outstanding 99%accuracy,exhibiting balanced precision,recall,and F1-scores across all tumor types,as detailed in the classification report.This successful implementation demonstrates the model’s potential as an essential tool for diagnosing and classifying brain tumors,marking a notable improvement over current methods.The integration of such advanced computational techniques in medical diagnostics can significantly enhance accuracy and efficiency,paving the way for wider application.This research highlights the revolutionary impact of deep learning technologies in improving diagnostic processes and patient outcomes in neuro-oncology.
基金This work is supported by the Hainan Provincial Natural Science Foundation of China(620RC562)the Natural Science Foundation of Shanxi Province(Grant Nos.20210302123444,20210302123455)+5 种基金the China University industry university research innovation fund(No.2021FNA02009)the Open Project Program of the Key Laboratory of Embedded System and Service Computing of Ministry of Education(Tongji University)ESSCKF 2021-04the National Natural Science Foundation of China(Grant Nos.61702315,61802092)the Applied Basic Research Plan of Shanxi Province(No.201901D211168)the Program of Hainan Association for Science and Technology Plans to Youth R&D Innovation(QCXM201910)the Key R&D Program(International Science and Technology Cooperation Project)of Shanxi Province China(No.201903D421003).
文摘Network failures are unavoidable and occur frequently.When the network fails,intra-domain routing protocols deploying on the Internet need to undergo a long convergence process.During this period,a large number of messages are discarded,which results in a decline in the user experience and severely affects the quality of service of Internet Service Providers(ISP).Therefore,improving the availability of intra-domain routing is a trending research question to be solved.Industry usually employs routing protection algorithms to improve intra-domain routing availability.However,existing routing protection schemes compute as many backup paths as possible to reduce message loss due to network failures,which increases the cost of the network and impedes the methods deployed in practice.To address the issues,this study proposes an efficient routing protection algorithm based on optimized network topology(ERPBONT).ERPBONT adopts the optimized network topology to calculate a backup path with the minimum path coincidence degree with the shortest path for all source purposes.Firstly,the backup path with the minimum path coincidence with the shortest path is described as an integer programming problem.Then the simulated annealing algorithm ERPBONT is used to find the optimal solution.Finally,the algorithm is tested on the simulated topology and the real topology.The experimental results show that ERPBONT effectively reduces the path coincidence between the shortest path and the backup path,and significantly improves the routing availability.
文摘Conventional multilevel inverters often suffer from high harmonic distortion and increased design complexity due to the need for numerous power semiconductor components,particularly at elevated voltage levels.Addressing these shortcomings,thiswork presents a robust 15-level PackedUCell(PUC)inverter topology designed for renewable energy and grid-connected applications.The proposed systemintegrates a sensor less proportional-resonant(PR)controller with an advanced carrier-based pulse width modulation scheme.This approach efficiently balances capacitor voltage,minimizes steady-state error,and strongly suppresses both zero and third-order harmonics resulting in reduced total harmonic distortion and enhanced voltage regulation.Additionally,a novel switching algorithm simplifies the design and implementation,further lowering voltage stress across switches.Extensive simulation results validate the performance under various resistive and resistive-inductive load conditions,demonstrating compliance with IEEE-519 THD standards and robust operation under dynamic changes.The proposed sensorless PR-controlled 15-PUC inverter thus offers a compelling,cost-effective solution for efficient power conversion in next-generation renewable energy systems.
基金supported by National Natural Science Foundation of China and NSF of Hubei Province
文摘in this paper the algorithms for self-stabilizing communication protocols are studied.First some concepts and a formal method for describing theproposed algorithms are described,then an improved algorithm for achieving globalstates is presented.The study shows that the improved algorithm can be appliedto obtain the global states in the case of a loss of cooperation of the different processes in the protocol,which can be used as a recovery point that will be used bythe following recovery procedure.Thus,the improved algorithm can be used toself-stabilize a communication protocol.Meanwhile,a recovery algorithm for selfstabilizing communication protocols is presented.After a failure is detected,allProcesses can eventually know the error.The recovery algorithm uses the contextualinformation exchanged during the progress of the protocol and recorded on the stablememory.The proof of correctness and analysis of complexity for these algorithmshave been made.The availability and efficiency of the algorithms have been verifiedby illustrating the example protocols.Finally,some conclusions and remarks aregiven.
基金Supported by the National Natural Science Foundation of China (Nos. 60833004 and 60970002)Prof. Yingfei Dong's current research is supported in part by US NSF (Nos. CNS-1041739, CNS-1120902, CNS-1018971, and CNS-1127875)
文摘Traffic classification is critical to effective network management. However, more and more pro- prietary, encrypted, and dynamic protocols make traditional traffic classification methods less effective. A Message and Command Correlation （MCC） method was developed to identify interactive protocols （such as P2P file sharing protocols and Instant Messaging （IM） protocols） by session analyses. Unlike traditional packet-based classification approaches, this method exploits application session information by clustering packets into application messages which are used for further classification. The efficacy and accuracy of the MCC method was evaluated with real world traffic, including P2P file sharing protocols Thunder and Bit- Torrent, and IM protocols QQ and GTalk. The tests show that the false positive rate is less than 3% and the false negative rate is below 8%, and that MCC only needs to check 8.7% of the packets or 0.9% of the traffic. Therefore, this approach has great potential for accurately and quickly discovering new types of interactive application protocols.
