The Nanling belt in South China has considerable resources of tungsten polymetallic commodities and is one of the most important metallogenic belts in the world. Data-driven weights-of-evidence （WofE） and fuzzy logi...The Nanling belt in South China has considerable resources of tungsten polymetallic commodities and is one of the most important metallogenic belts in the world. Data-driven weights-of-evidence （WofE） and fuzzy logic models are used to evaluate the tungsten polymetallic potential of the Nanling belt. Initially, seven ore-controlling factors derived from multi-source geospatial datasets （e.g., geological, geochemical, and geophysical） are used for data integration in the two models. Two mineral potential maps are generated that efficiently predicate the locations of the deposits. The WofE map predicate 81% of the deposits within 13.6% of the study area, whereas the fuzzy logic map predicate 81.5% of the deposits within 13% of the area. The predictive maps are syntheses of spatial association rules, which provide better understanding of those factors that control the distribution of mineralization and trigger eventual exploration work in new areas. Subsequently, in order to evaluate the success rate accuracy, the receiver operating characteristic curves and area under the curves （AUCs） for the two potential maps are constructed. The results show that the AUCs for the WofE and fuzzy logic models are 0.775 7 and 0.840 6, respectively. The higher AUC value for the fuzzy logic model implies that it delineate a greater number of favorable areas compared with the WorE model. Overall, the capabilities of both models for correctly classifying areas with existing mineral deposits are satisfactory.展开更多
Memristors integrated with low operating voltage,good stability,and environmental benignity play an important role in data storage and logical circuit technology,but their fabrication still faces challenges.This study...Memristors integrated with low operating voltage,good stability,and environmental benignity play an important role in data storage and logical circuit technology,but their fabrication still faces challenges.This study reports an ultra-thin bio-memristor based on pristine environmentfriendly silk nanofibrils(SNFs).The intrinsic ionic conductivity,combined with high dielectric performance and nanoscale thickness,lowers the operation voltage down to0.1-0.2 V,and enables stable switching and retention time over 180 times and 10^(5)s,respectively.Furthermore,the SNFbased memristor device in a crossbar array achieves stable memristive performance,and thus realizes the functions of memorizing image and logic operation.By carrying out variable-temperature electrical experiments and Kelvin probe force microscopy,the space charge-limited conduction mechanism is revealed.Integrating with low operating voltage,good stability,and ultra-thin thickness makes the SNF-based memristors excellent candidates in bioelectronics.展开更多
Disk scheduling is one of the main responsibilities of Operating System. OS manages hard disk to provide best access time. All major Disk scheduling algorithms incorporate seek time as the only factor for disk schedul...Disk scheduling is one of the main responsibilities of Operating System. OS manages hard disk to provide best access time. All major Disk scheduling algorithms incorporate seek time as the only factor for disk scheduling. The second factor rotational delay is ignored by the existing algorithms. This research paper considers both factors, Seek Time and Rotational Delay to schedule the disk. Our algorithm Fuzzy Disk Scheduling (FDS) looks at the uncertainty associated with scheduling incorporating the two factors. Keeping in view a Fuzzy inference system using If-Then rules is designed to optimize the overall performance of disk drives. Finally we compared the FDS with the other scheduling algorithms.展开更多
基金supported by the Basic Research and Public Service Special Fund Project from the Institute of Geophysical and Geochemical Exploration, CAGS (No. WHS201208)the Program of Integrated Prediction of Mineral Resources in Covered Areas (No. 1212011085468)the China Geological Survey (No. 201211022)
文摘The Nanling belt in South China has considerable resources of tungsten polymetallic commodities and is one of the most important metallogenic belts in the world. Data-driven weights-of-evidence （WofE） and fuzzy logic models are used to evaluate the tungsten polymetallic potential of the Nanling belt. Initially, seven ore-controlling factors derived from multi-source geospatial datasets （e.g., geological, geochemical, and geophysical） are used for data integration in the two models. Two mineral potential maps are generated that efficiently predicate the locations of the deposits. The WofE map predicate 81% of the deposits within 13.6% of the study area, whereas the fuzzy logic map predicate 81.5% of the deposits within 13% of the area. The predictive maps are syntheses of spatial association rules, which provide better understanding of those factors that control the distribution of mineralization and trigger eventual exploration work in new areas. Subsequently, in order to evaluate the success rate accuracy, the receiver operating characteristic curves and area under the curves （AUCs） for the two potential maps are constructed. The results show that the AUCs for the WofE and fuzzy logic models are 0.775 7 and 0.840 6, respectively. The higher AUC value for the fuzzy logic model implies that it delineate a greater number of favorable areas compared with the WorE model. Overall, the capabilities of both models for correctly classifying areas with existing mineral deposits are satisfactory.
基金supported by the National Natural Science Foundation of China(51903045 and 52173031)the International Cooperation Fund of the Science and Technology Commission of Shanghai Municipality(19520744500)+3 种基金the Basic Research Project of the Science and Technology Commission of Shanghai Municipality(21JC1400100)Shanghai Rising-Star Program(22QA1400400)the Program of Shanghai Academic/Technology Research Leader(20XD1400100)the Fundamental Research Funds for the Central Universities and Graduate Student Innovation Fund of Donghua University(CUSF-DH-D-2020049)。
文摘Memristors integrated with low operating voltage,good stability,and environmental benignity play an important role in data storage and logical circuit technology,but their fabrication still faces challenges.This study reports an ultra-thin bio-memristor based on pristine environmentfriendly silk nanofibrils(SNFs).The intrinsic ionic conductivity,combined with high dielectric performance and nanoscale thickness,lowers the operation voltage down to0.1-0.2 V,and enables stable switching and retention time over 180 times and 10^(5)s,respectively.Furthermore,the SNFbased memristor device in a crossbar array achieves stable memristive performance,and thus realizes the functions of memorizing image and logic operation.By carrying out variable-temperature electrical experiments and Kelvin probe force microscopy,the space charge-limited conduction mechanism is revealed.Integrating with low operating voltage,good stability,and ultra-thin thickness makes the SNF-based memristors excellent candidates in bioelectronics.
文摘Disk scheduling is one of the main responsibilities of Operating System. OS manages hard disk to provide best access time. All major Disk scheduling algorithms incorporate seek time as the only factor for disk scheduling. The second factor rotational delay is ignored by the existing algorithms. This research paper considers both factors, Seek Time and Rotational Delay to schedule the disk. Our algorithm Fuzzy Disk Scheduling (FDS) looks at the uncertainty associated with scheduling incorporating the two factors. Keeping in view a Fuzzy inference system using If-Then rules is designed to optimize the overall performance of disk drives. Finally we compared the FDS with the other scheduling algorithms.
