Inhibition of 11βHSD1 （11-beta-hydroxysteroid dehydrogenase 1） is a promising strategy in drug treatment of diabetes. Several 11βHSDI inhibitors have been proposed; however, their selectivity to 11βHSD1 over its ...Inhibition of 11βHSD1 （11-beta-hydroxysteroid dehydrogenase 1） is a promising strategy in drug treatment of diabetes. Several 11βHSDI inhibitors have been proposed; however, their selectivity to 11βHSD1 over its isozyme 11βHSD2 （11-beta-hydroxysteroid dehydrogenase 2） has not been fully reported. The authors sought to provide a short list of top potent and selective compounds along with their detailed binding modes and pharmacophore models, Molecular docking was used for initial screening of a set of 23 potent inhibitors reported by previous experimental studies. After that, selected promising entries were reassessed by molecular dynamics simulations, followed by hydrogen bond analysis. Pharmacophore models of all drug candidates and binding modes of some selected drugs were analyzed. Among the 23 compounds, only four inhibitors were identified as potent and selective drug candidates. Binding energies, 3D pharmacophores and binding modes of the four compounds with 11βHSDI are also discussed in detail in this study.展开更多
This study examined the impact of tropical cyclone (TC) landfalls on the spatiotemporal variations in the rainfall over South China for the period 1957–2005. The target region was selected to show the noteworthy cont...This study examined the impact of tropical cyclone (TC) landfalls on the spatiotemporal variations in the rainfall over South China for the period 1957–2005. The target region was selected to show the noteworthy contribution of TC landfalls to the total rainfall during the typhoon season (July–October). Two prevailing spatial variations in the rainfall were obtained from an EOF analysis. The first EOF mode displays singlesign variability over South China with an explained variance of 23.4%. The associated time series of this mode fluctuates on a decadal timescale and was found to be correlated with TC genesis in the South China Sea. The second EOF mode shows a seesaw pattern between Hainan Island/Guangdong Province and the remaining regions with an explained variance of 11.4%. This seesaw pattern results from an anti-correlation in seasonal TC landfalls between the two regions, which was found in previous studies. This is related to the strengthening (weakening) of the upper tropospheric jets and the corresponding development of a massive anticyclonic (cyclonic) circulation over East Asia. The EOF analysis was also conducted using just the data for rainfall caused by landfalling TCs. This revealed that the first EOF mode using just the TC-induced rainfall is nearly identical to the second mode from the total rainfall. The obvious seesaw pattern of the first mode when employing just the TC-induced rainfall in the EOF analysis implies that this pattern has larger temporal variability than the single-signed pattern (i.e., the first EOF mode using the total rainfall) in terms of TC landfalls. This study suggests that TC landfalls over South China and the accompanying rainfall significantly modulate the spatial variation of the typhoon season rainfall there.展开更多
Deep Learning(DL)is a subfield of machine learning that significantly impacts extracting new knowledge.By using DL,the extraction of advanced data representations and knowledge can be made possible.Highly effective DL...Deep Learning(DL)is a subfield of machine learning that significantly impacts extracting new knowledge.By using DL,the extraction of advanced data representations and knowledge can be made possible.Highly effective DL techniques help to find more hidden knowledge.Deep learning has a promising future due to its great performance and accuracy.We need to understand the fundamentals and the state‐of‐the‐art of DL to leverage it effectively.A survey on DL ways,advantages,drawbacks,architectures,and methods to have a straightforward and clear understanding of it from different views is explained in the paper.Moreover,the existing related methods are compared with each other,and the application of DL is described in some applications,such as medical image analysis,handwriting recognition,and so on.展开更多
Hourly outgoing longwave radiation （OLR） from the geostationary satellite Communication Oceanography Meteorological Satellite （COMS） has been retrieved since June 2010.The COMS OLR retrieval algorithms are based o...Hourly outgoing longwave radiation （OLR） from the geostationary satellite Communication Oceanography Meteorological Satellite （COMS） has been retrieved since June 2010.The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels.This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm （OLR12.0 using the 12.0 μm channel） and three multiple-channel algorithms （OLR10.8＋12.0 using the 10.8 and 12.0 pm channels; OLR6.7＋10.8 using the 6.7 and 10.8 μm channels; and OLRAll using the 6.7,10.8,and 12.0 μm channels）.The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth＇s Radiant Energy System （CERES） over the full COMS field of view [roughly （50°S-50°N,70°-170°E）] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5-7 W m-2,which indicates good agreement with CERES OLR over the vast domain.OLR6.7＋10.8 and OLRAll have much smaller errors （～ 6 W m-2） than OLR12.0 and OLR10.8＋12.0 （～ 8 W m-2）.Moreover,the small errors of OLR6.7＋10.8 and OLRAll are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration.These results indicate a noteworthy role of the 6.7 μm water vapor absorption channel in improving the accuracy of the OLRs.The dependence of the accuracy of COMS OLRs on various surface,atmospheric,and observational conditions is also discussed.展开更多
Mainstream line is significant for the Yellow River situation forecasting and flood control.An effective statistical feature extraction method is proposed in this paper.In this method, a between-class scattering matri...Mainstream line is significant for the Yellow River situation forecasting and flood control.An effective statistical feature extraction method is proposed in this paper.In this method, a between-class scattering matrix based projection algorithm is performed to maximize between-class differences, obtaining effective component for classification;then high-order statistics are utilized as the features to describe the mainstream line in the principal component obtained.Experiments are performed to verify the applicability of the algorithm.The results both on synthesized and real scenes indicate that this approach could extract the mainstream line of the Yellow River automatically, and has a high precision in mainstream line detection.展开更多
Most existing blockchain schemes are based on the design concept“openness and transparency”to realize data security,which usually require transaction data to be presented in the form of plaintext.However,it inevitab...Most existing blockchain schemes are based on the design concept“openness and transparency”to realize data security,which usually require transaction data to be presented in the form of plaintext.However,it inevitably brings the issues with respect to data privacy and operating performance.In this paper,we proposed a novel blockchain scheme called Cipherchain,which can process and maintain transaction data in the form of ciphertext while the characteristics of immutability and auditability are guaranteed.Specifically in our scheme,transactions can be encrypted locally based on a searchable encryption scheme called multi-user public key encryption with conjunctive keyword search(mPECK),and can be accessed by multiple specific participants after appended to the globally consistent distributed ledger.By introducing execution-consensus-update paradigm of transaction flow,Cipherchain cannot only make it possible for transaction data to exist in the form of ciphertext,but also guarantee the overall system performance not greatly affected by cryptographic operations and other local execution work.In addition,Cipherchain is a promising scheme to realize the technology combination of“blockchain+cloud computing”and“permissioned blockchain+public blockchain”.展开更多
COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world.Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce t...COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world.Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce the number of new cases.In this study,we apply the decomposition and ensemble model to forecast COVID-19 confirmed cases,deaths,and recoveries in Pakistan for the upcoming month until the end of July.For the decomposition of data,the Ensemble Empirical Mode Decomposition(EEMD)technique is applied.EEMD decomposes the data into small components,called Intrinsic Mode Functions(IMFs).For individual IMFs modelling,we use the Autoregressive Integrated Moving Average(ARIMA)model.The data used in this study is obtained from the official website of Pakistan that is publicly available and designated for COVID-19 outbreak with daily updates.Our analyses reveal that the number of recoveries,new cases,and deaths are increasing in Pakistan exponentially.Based on the selected EEMD-ARIMA model,the new confirmed cases are expected to rise from 213,470 to 311,454 by 31 July 2020,which is an increase of almost 1.46 times with a 95%prediction interval of 246,529 to 376,379.The 95%prediction interval for recovery is 162,414 to 224,579,with an increase of almost two times in total from 100802 to 193495 by 31 July 2020.On the other hand,the deaths are expected to increase from 4395 to 6751,which is almost 1.54 times,with a 95%prediction interval of 5617 to 7885.Thus,the COVID-19 forecasting results of Pakistan are alarming for the next month until 31 July 2020.They also confirm that the EEMD-ARIMA model is useful for the short-term forecasting of COVID-19,and that it is capable of keeping track of the real COVID-19 data in nearly all scenarios.The decomposition and ensemble strategy can be useful to help decision-makers in developing short-term strategies about the current number of disease occurrences until an appropriate vaccine is developed.展开更多
A distributed conceptual model(FRASC(Flow Routed Accumulation Simulation in a Catchment))has been developed,in which a rainfall-runoff module is modified from an original lumped conceptual model(Xinanjiang)via a GIS(G...A distributed conceptual model(FRASC(Flow Routed Accumulation Simulation in a Catchment))has been developed,in which a rainfall-runoff module is modified from an original lumped conceptual model(Xinanjiang)via a GIS(Geographic Information System)-aided approach and a water allocation module contains reservoirs,water users and hydropower plants.The model is relatively easy to use and can easily obtain input data,but still has the ability to generate hydrological information at many points within a catchment.The model application to the Be River basin is evaluated and shows to be reliable in terms of close agreements between simulated and observed series.Daily natural flow rates for 36 years are simulated at 7,981 grid cells within a studied area of 7,650 km^2.Based on this simulated database,design discharges are predicted in various probabilities.Finally,the research determines that the water transfer capacity from the Be River basin to the Saigon River basin reaches 14%,18% and 23% of a planned value of 75 m^3/s during the dry period in a wet year(P10%),average year(P50%)and dry year(P90%),respectively.展开更多
The problem of determining a minimum-area ellipse through three non-collinear points is discussed in this paper. We give the proof and construction of the minimum-area ellipse through three non-collinear points from t...The problem of determining a minimum-area ellipse through three non-collinear points is discussed in this paper. We give the proof and construction of the minimum-area ellipse through three non-collinear points from the geometric point of view, and present a new method of determining knots. This method replaces the chord length, which is closer to the arc length of the mini- mum-area ellipse with arc length, and avoids the occurrence of ＇oscillation＇ and ＇loops＇. We compare the new method with the uni- form method, chord length method and the centripetal method. The comparison is performed on the quality of cubic spline curves using these methods. In most cases, the result of our method is better than others.展开更多
This paper investigates the adaptability of Maximum Power Point Tracking (MPPT) algorithms in single-stage three-phase photovoltaic (PV) systems connected to the grid of Congo-Brazzaville and compares the attributes o...This paper investigates the adaptability of Maximum Power Point Tracking (MPPT) algorithms in single-stage three-phase photovoltaic (PV) systems connected to the grid of Congo-Brazzaville and compares the attributes of various conventional, significance and novelty of controller system of the proposed of method and improved Incremental Conductance algorithms, Perturbation and Observation Techniques, and other Maximum Power Point Tracking (MPPT) algorithms in normal and partial shading conditions. Performance evaluation techniques are discussed on the basis of the dynamic parameters of the PV system although the control of this structure is relatively advanced technology but the conversion efficiency is difficult to improve due to increase in transformation series. The single stage topology has a simple topology with high reliability and efficiency because of high power consumption, but control algorithm is more complex because of its power convert main circuit a new strategy is being developed. This paper describes a method for maximum power point tracking (MPPT) in the single-stage and three single-phase PV grid-connected system. In the paper, the nonlinear output characteristics of the PV including I-V & P-V are obtained in changed solar insulations or temperature based on MATLAB, and the MPPT algorithm which is based on the P & O algorithm method, compared with Incremental Conductance, is also described, a dimensioning of the impedance adapter for better stabilization. A comparison SPWM and SVPWM control methods in the case of a grid connection applied to the electrical grid of Republic of Congo and their influences on the dynamic performance of the system and their impact in reducing the harmonic rate for better injection into the grid. The simulation model of three single-phase PV grid-connected system is built, and simulation results show the MPPT algorithm has excellent dynamic and static performances, which verifies the Incremental Conductance is effective for MPPT in the single-stage and three single-phase PV grid-connected system.展开更多
Background:Whole-slide image(WSI)is foundational for artificial intelligence in tumor diagnosis,treatment planning,and prognosis prediction.Efficient management of WSI labels is crucial for clinical digitalization;how...Background:Whole-slide image(WSI)is foundational for artificial intelligence in tumor diagnosis,treatment planning,and prognosis prediction.Efficient management of WSI labels is crucial for clinical digitalization;however,manual or semiautomatic methods limit scalability.Enhancing automatic pathological label recognition is critical to advancing digital pathology,improving efficiency,and drive precision oncology.Methods:We developed Auto LDP,a method for automatic labeling of digital pathology,which identifies textual information used for labeling slides.The method includes four steps:identifying text position using the CRAFT model,recognizing text content using the ParSeq model,identifying slice type using the ConvNext classifier,and combining relevant information to generate a new name.The naming format is divided into four parts:pathology ID,wax block ID,staining type,and slice type.We used the accuracy and processing time to validate our method using two validation sets.Results:The AutoLDP system was 20 times faster than manual labeling.The files per minute in the solid-state drives of CRAFT t ParSeq were the highest among all methods at 136.95 in validation set 1 and 170.95 in validation set 2.We compared the proposed model with several commonly used text detection and recognition models including ABinet,CRNN,TRBA,and Vitstr.The results show that we achieved an accuracy of 97.60%in just 87.62 s in validation set 1 with 200 cases,which was significantly better than that of the other models.In addition,the accuracy reached 96.98% in validation set 2 with 13,667 cases,confirming the generalization ability of the model.Conclusion:In this study,we proposed a new model,AutoLDP,automates the extraction and recognition of key information from WSI,enabling standardized naming,and significantly improving labeling efficiency.This innovation supports the digital transformation of pathology and advances precision medicine.展开更多
With the increasing number of smart devices and the development of machine learning technology,the value of users’personal data is becoming more and more important.Based on the premise of protecting users’personal p...With the increasing number of smart devices and the development of machine learning technology,the value of users’personal data is becoming more and more important.Based on the premise of protecting users’personal privacy data,federated learning(FL)uses data stored on edge devices to realize training tasks by contributing training model parameters without revealing the original data.However,since FL can still leak the user’s original data by exchanging gradient information.The existing privacy protection strategy will increase the uplink time due to encryption measures.It is a huge challenge in terms of communication.When there are a large number of devices,the privacy protection cost of the system is higher.Based on these issues,we propose a privacy-preserving scheme of user-based group collaborative federated learning(GrCol-PPFL).Our scheme primarily divides participants into several groups and each group communicates in a chained transmission mechanism.All groups work in parallel at the same time.The server distributes a random parameter with the same dimension as the model parameter for each participant as a mask for the model parameter.We use the public datasets of modified national institute of standards and technology database(MNIST)to test the model accuracy.The experimental results show that GrCol-PPFL not only ensures the accuracy of themodel,but also ensures the security of the user’s original data when users collude with each other.Finally,through numerical experiments,we show that by changing the number of groups,we can find the optimal number of groups that reduces the uplink consumption time.展开更多
Traditional scheduling algorithms for avionics communication have the shortcoming of messages accumulation,the efficiency and reliability of the service can be improved by combining the distributed integrated modular ...Traditional scheduling algorithms for avionics communication have the shortcoming of messages accumulation,the efficiency and reliability of the service can be improved by combining the distributed integrated modular avionics(DIMA)system with a time trigger mechanism.To further improve the utilization of system resources,the static scheduling algorithm of time triggered service is studied.By making the time trigger message schedule dispersedly,the stabilities of both the available time slots for the event triggered messages and the system will be improved.An improved two-dimensional bin packing algorithm is also presented to achieve the above-mentioned purpose with an extra benefit of better delay performance.展开更多
According to X-ray image texture tire characteristics and abnormal distribution of the gray area, this paper studies a real-time defect detection method about the sidewall of tire. On the basis of the texture distribu...According to X-ray image texture tire characteristics and abnormal distribution of the gray area, this paper studies a real-time defect detection method about the sidewall of tire. On the basis of the texture distribution characteristics of X-ray tire, we extract the cord information of the tire image by maximizing the distance of the categories after the gray value correction, then we use the morphology method and statistics method to process the image so that we can get the location and the size of impurities. We can classify the tires into different grades by the information. Compared with other methods, our method has the advantage that meets the needs of tire industry.展开更多
Federated learning(FL)has emerged to break data-silo and protect clients’privacy in the field of artificial intelligence.However,deep leakage from gradient(DLG)attack can fully reconstruct clients’data from the subm...Federated learning(FL)has emerged to break data-silo and protect clients’privacy in the field of artificial intelligence.However,deep leakage from gradient(DLG)attack can fully reconstruct clients’data from the submitted gradient,which threatens the fundamental privacy of FL.Although cryptology and differential privacy prevent privacy leakage from gradient,they bring negative effect on communication overhead or model performance.Moreover,the original distribution of local gradient has been changed in these schemes,which makes it difficult to defend against adversarial attack.In this paper,we propose a novel federated learning framework with model decomposition,aggregation and assembling(FedDAA),along with a training algorithm,to train federated model,where local gradient is decomposed into multiple blocks and sent to different proxy servers to complete aggregation.To bring better privacy protection performance to FedDAA,an indicator is designed based on image structural similarity to measure privacy leakage under DLG attack and an optimization method is given to protect privacy with the least proxy servers.In addition,we give defense schemes against adversarial attack in FedDAA and design an algorithm to verify the correctness of aggregated results.Experimental results demonstrate that FedDAA can reduce the structural similarity between the reconstructed image and the original image to 0.014 and remain model convergence accuracy as 0.952,thus having the best privacy protection performance and model training effect.More importantly,defense schemes against adversarial attack are compatible with privacy protection in FedDAA and the defense effects are not weaker than those in the traditional FL.Moreover,verification algorithm of aggregation results brings about negligible overhead to FedDAA.展开更多
In DVB-IPDC system, due to the constraints of handheld devices and the broadcast nature of wireless network, packet loss is inevitable. ECDR-NC proposed is a retransmission encoding packet selection algorithm based on...In DVB-IPDC system, due to the constraints of handheld devices and the broadcast nature of wireless network, packet loss is inevitable. ECDR-NC proposed is a retransmission encoding packet selection algorithm based on the dynamic information updating, which can find the current most effective complete decoding packet. ECDR-NC can not only avoid the redundant encoding packets due to the overlapping among encoding packets, but also reduce the computational complexity compared with the traditional encoding schemes. Furthermore, the retransmission upper bound of ECDR-NC is fully controlled. In time-sensitive applications, to maximize the aggregate number of recovery packets while minimizing the total number of discarded packets due to the time limit according to the priority preference, the adaptive priority scheme EPNC is formulized, and the weighted relation graph is constructed to find the maximum-weighted encoding packets sequence according to the decoding gains. In the same network environment, the performances comparisons between PNC and EPNC show that EPNC is more efficient and more rational, and the average discarded packets ratios ofEPNC can be reduced about 18%~27%. The main contributions of this paper are an effective retransmission encoding packet selection algorithm ECDR-NC proposed, and a new adaptive priority recovery scheme EPNC introduced into DVB-IPDC system.展开更多
Coin-flipping protocols allow mutually distrustful parties to generate a random bit with uniform distribution.Minimizing bias and keeping fairness are two key requirements in designing such protocols.However,the best ...Coin-flipping protocols allow mutually distrustful parties to generate a random bit with uniform distribution.Minimizing bias and keeping fairness are two key requirements in designing such protocols.However,the best previously known fair coin-flipping protocol only guarantees with bias Ο（1 /r）.In the paper,we introduce a new approach for fair coin-flipping protocol construction by using Garay et al’s ＂resource fairness＂ technique and propose a resource-fair two-party coin-flipping protocol according to the standard real/ideal simulation paradigm.Compared with the other coin-flipping protocols,our protocol enjoys an important advantage that its bias is 0.展开更多
Dynamic geometry software, as a piece of computer-assisted instruction(CAI) software, is closely and deeply associated with mathematics, and is widely applied to mathematics teaching activities in primary and secondar...Dynamic geometry software, as a piece of computer-assisted instruction(CAI) software, is closely and deeply associated with mathematics, and is widely applied to mathematics teaching activities in primary and secondary schools. Meanwhile, web technology also has become an important technology for assisting education and teaching. This paper expounds a web-based dynamic geometry software development process, and analyses specific requirements regarding graphical application programming interface(API) required by dynamic geometry software. With experiments and comparison on the two different hypertext markup language(HTML)5 graphical API technologies, i.e., scalable vector graphics(SVG) and Canvas, on different apparatuses and browsers, we draw the conclusion that it is more suitable to adopt Canvas as the graphical API technology for the web-based dynamic geometry software, thus further proposed the principles and methods for an object-oriented Canvas design. The dynamic geometry software based on the newly-designed Canvas has technical advantages and educational value, well incorporating aesthetic education into mathematics education.展开更多
Internet of Medical Things(IoMT)plays an essential role in collecting and managing personal medical data.In recent years,blockchain technology has put power in traditional IoMT systems for data sharing between differe...Internet of Medical Things(IoMT)plays an essential role in collecting and managing personal medical data.In recent years,blockchain technology has put power in traditional IoMT systems for data sharing between different medical institutions and improved the utilization of medical data.However,some problems in the information transfer process between wireless medical devices and mobile medical apps,such as information leakage and privacy disclosure.This paper first designs a cross-device key agreement model for blockchain-enabled IoMT.This model can establish a key agreement mechanism for secure medical data sharing.Meanwhile,a certificateless authenticated key agreement(KA)protocol has been proposed to strengthen the information transfer security in the cross-device key agreement model.The proposed KA protocol only requires one exchange of messages between the two parties,which can improve the protocol execution efficiency.Then,any unauthorized tampering of the transmitted signed message sent by the sender can be detected by the receiver,so this can guarantee the success of the establishment of a session key between the strange entities.The blockchain ledger can ensure that the medical data cannot be tampered with,and the certificateless mechanism can weaken the key escrow problem.Moreover,the security proof and performance analysis are given,which show that the proposed model and KA protocol are more secure and efficient than other schemes in similar literature.展开更多
文摘Inhibition of 11βHSD1 （11-beta-hydroxysteroid dehydrogenase 1） is a promising strategy in drug treatment of diabetes. Several 11βHSDI inhibitors have been proposed; however, their selectivity to 11βHSD1 over its isozyme 11βHSD2 （11-beta-hydroxysteroid dehydrogenase 2） has not been fully reported. The authors sought to provide a short list of top potent and selective compounds along with their detailed binding modes and pharmacophore models, Molecular docking was used for initial screening of a set of 23 potent inhibitors reported by previous experimental studies. After that, selected promising entries were reassessed by molecular dynamics simulations, followed by hydrogen bond analysis. Pharmacophore models of all drug candidates and binding modes of some selected drugs were analyzed. Among the 23 compounds, only four inhibitors were identified as potent and selective drug candidates. Binding energies, 3D pharmacophores and binding modes of the four compounds with 11βHSDI are also discussed in detail in this study.
基金funded by the Korea Meteorological Administration Research and Development Program under grant CATER 2006-4204supported by the BK21 project of the Korean government
文摘This study examined the impact of tropical cyclone (TC) landfalls on the spatiotemporal variations in the rainfall over South China for the period 1957–2005. The target region was selected to show the noteworthy contribution of TC landfalls to the total rainfall during the typhoon season (July–October). Two prevailing spatial variations in the rainfall were obtained from an EOF analysis. The first EOF mode displays singlesign variability over South China with an explained variance of 23.4%. The associated time series of this mode fluctuates on a decadal timescale and was found to be correlated with TC genesis in the South China Sea. The second EOF mode shows a seesaw pattern between Hainan Island/Guangdong Province and the remaining regions with an explained variance of 11.4%. This seesaw pattern results from an anti-correlation in seasonal TC landfalls between the two regions, which was found in previous studies. This is related to the strengthening (weakening) of the upper tropospheric jets and the corresponding development of a massive anticyclonic (cyclonic) circulation over East Asia. The EOF analysis was also conducted using just the data for rainfall caused by landfalling TCs. This revealed that the first EOF mode using just the TC-induced rainfall is nearly identical to the second mode from the total rainfall. The obvious seesaw pattern of the first mode when employing just the TC-induced rainfall in the EOF analysis implies that this pattern has larger temporal variability than the single-signed pattern (i.e., the first EOF mode using the total rainfall) in terms of TC landfalls. This study suggests that TC landfalls over South China and the accompanying rainfall significantly modulate the spatial variation of the typhoon season rainfall there.
文摘Deep Learning(DL)is a subfield of machine learning that significantly impacts extracting new knowledge.By using DL,the extraction of advanced data representations and knowledge can be made possible.Highly effective DL techniques help to find more hidden knowledge.Deep learning has a promising future due to its great performance and accuracy.We need to understand the fundamentals and the state‐of‐the‐art of DL to leverage it effectively.A survey on DL ways,advantages,drawbacks,architectures,and methods to have a straightforward and clear understanding of it from different views is explained in the paper.Moreover,the existing related methods are compared with each other,and the application of DL is described in some applications,such as medical image analysis,handwriting recognition,and so on.
基金supported by the Korea Meteorological Administration Research and Development Program (Grant No. CATER 2012-2040)
文摘Hourly outgoing longwave radiation （OLR） from the geostationary satellite Communication Oceanography Meteorological Satellite （COMS） has been retrieved since June 2010.The COMS OLR retrieval algorithms are based on regression analyses of radiative transfer simulations for spectral functions of COMS infrared channels.This study documents the accuracies of OLRs for future climate applications by making an intercomparison of four OLRs from one single-channel algorithm （OLR12.0 using the 12.0 μm channel） and three multiple-channel algorithms （OLR10.8＋12.0 using the 10.8 and 12.0 pm channels; OLR6.7＋10.8 using the 6.7 and 10.8 μm channels; and OLRAll using the 6.7,10.8,and 12.0 μm channels）.The COMS OLRs from these algorithms were validated with direct measurements of OLR from a broadband radiometer of the Clouds and Earth＇s Radiant Energy System （CERES） over the full COMS field of view [roughly （50°S-50°N,70°-170°E）] during April 2011.Validation results show that the root-mean-square errors of COMS OLRs are 5-7 W m-2,which indicates good agreement with CERES OLR over the vast domain.OLR6.7＋10.8 and OLRAll have much smaller errors （～ 6 W m-2） than OLR12.0 and OLR10.8＋12.0 （～ 8 W m-2）.Moreover,the small errors of OLR6.7＋10.8 and OLRAll are systematic and can be readily reduced through additional mean bias correction and/or radiance calibration.These results indicate a noteworthy role of the 6.7 μm water vapor absorption channel in improving the accuracy of the OLRs.The dependence of the accuracy of COMS OLRs on various surface,atmospheric,and observational conditions is also discussed.
基金supported by the Flood Control Foundation of Yellow River Conservancy Commissionthe 2007 Key Supporting Project on Undergraduate Graduation Thesis of North-western Polytechnical University.
文摘Mainstream line is significant for the Yellow River situation forecasting and flood control.An effective statistical feature extraction method is proposed in this paper.In this method, a between-class scattering matrix based projection algorithm is performed to maximize between-class differences, obtaining effective component for classification;then high-order statistics are utilized as the features to describe the mainstream line in the principal component obtained.Experiments are performed to verify the applicability of the algorithm.The results both on synthesized and real scenes indicate that this approach could extract the mainstream line of the Yellow River automatically, and has a high precision in mainstream line detection.
基金This work is supported by the NSFC(Grant Nos.61671087,61962009,61003287)the Fok Ying Tong Education Foundation(Grant No.131067)+4 种基金the Major Scientific and Technological Special Project of Guizhou Province(Grant No.20183001)the Foundation of State Key Laboratory of Public Big Data(Grant No.2018BDKFJJ018)CCF-Tencent Open Fund WeBank Special Funding(CCF-WebankRAGR20180104)the High-quality and Cutting-edge Disciplines Construction Project for Universities in Beijing(Internet Information,Communication University of China)the Fundamental Research Funds for the Central Universities,and the Fundamental Research Funds for the Central Universities No.2019XD-A02.
文摘Most existing blockchain schemes are based on the design concept“openness and transparency”to realize data security,which usually require transaction data to be presented in the form of plaintext.However,it inevitably brings the issues with respect to data privacy and operating performance.In this paper,we proposed a novel blockchain scheme called Cipherchain,which can process and maintain transaction data in the form of ciphertext while the characteristics of immutability and auditability are guaranteed.Specifically in our scheme,transactions can be encrypted locally based on a searchable encryption scheme called multi-user public key encryption with conjunctive keyword search(mPECK),and can be accessed by multiple specific participants after appended to the globally consistent distributed ledger.By introducing execution-consensus-update paradigm of transaction flow,Cipherchain cannot only make it possible for transaction data to exist in the form of ciphertext,but also guarantee the overall system performance not greatly affected by cryptographic operations and other local execution work.In addition,Cipherchain is a promising scheme to realize the technology combination of“blockchain+cloud computing”and“permissioned blockchain+public blockchain”.
文摘COVID-19 has caused severe health complications and produced a substantial adverse economic impact around the world.Forecasting the trend of COVID-19 infections could help in executing policies to effectively reduce the number of new cases.In this study,we apply the decomposition and ensemble model to forecast COVID-19 confirmed cases,deaths,and recoveries in Pakistan for the upcoming month until the end of July.For the decomposition of data,the Ensemble Empirical Mode Decomposition(EEMD)technique is applied.EEMD decomposes the data into small components,called Intrinsic Mode Functions(IMFs).For individual IMFs modelling,we use the Autoregressive Integrated Moving Average(ARIMA)model.The data used in this study is obtained from the official website of Pakistan that is publicly available and designated for COVID-19 outbreak with daily updates.Our analyses reveal that the number of recoveries,new cases,and deaths are increasing in Pakistan exponentially.Based on the selected EEMD-ARIMA model,the new confirmed cases are expected to rise from 213,470 to 311,454 by 31 July 2020,which is an increase of almost 1.46 times with a 95%prediction interval of 246,529 to 376,379.The 95%prediction interval for recovery is 162,414 to 224,579,with an increase of almost two times in total from 100802 to 193495 by 31 July 2020.On the other hand,the deaths are expected to increase from 4395 to 6751,which is almost 1.54 times,with a 95%prediction interval of 5617 to 7885.Thus,the COVID-19 forecasting results of Pakistan are alarming for the next month until 31 July 2020.They also confirm that the EEMD-ARIMA model is useful for the short-term forecasting of COVID-19,and that it is capable of keeping track of the real COVID-19 data in nearly all scenarios.The decomposition and ensemble strategy can be useful to help decision-makers in developing short-term strategies about the current number of disease occurrences until an appropriate vaccine is developed.
基金funded by the Ho Chi Minh City Department of Science and TechnologyICST(Institute for Computational Science and Technology),grant number 24/2017/HD-KHCNTT signed on September 21,2017kind assistance with data collection and research process was supported by the Dau Tieng-Phuoc HoaIrrigation Engineering Integrated Complex,and Institute for Science and Technology Innovation.
文摘A distributed conceptual model(FRASC(Flow Routed Accumulation Simulation in a Catchment))has been developed,in which a rainfall-runoff module is modified from an original lumped conceptual model(Xinanjiang)via a GIS(Geographic Information System)-aided approach and a water allocation module contains reservoirs,water users and hydropower plants.The model is relatively easy to use and can easily obtain input data,but still has the ability to generate hydrological information at many points within a catchment.The model application to the Be River basin is evaluated and shows to be reliable in terms of close agreements between simulated and observed series.Daily natural flow rates for 36 years are simulated at 7,981 grid cells within a studied area of 7,650 km^2.Based on this simulated database,design discharges are predicted in various probabilities.Finally,the research determines that the water transfer capacity from the Be River basin to the Saigon River basin reaches 14%,18% and 23% of a planned value of 75 m^3/s during the dry period in a wet year(P10%),average year(P50%)and dry year(P90%),respectively.
基金Supported by the National Research Foundation for the Doctoral Program of Higher Education of China(20110131130004)Independent Innovation Foundation of Shandong University,IIFSDU(2012TB013)Ji’nan Science and Technology Development Project(No.201202015)
文摘The problem of determining a minimum-area ellipse through three non-collinear points is discussed in this paper. We give the proof and construction of the minimum-area ellipse through three non-collinear points from the geometric point of view, and present a new method of determining knots. This method replaces the chord length, which is closer to the arc length of the mini- mum-area ellipse with arc length, and avoids the occurrence of ＇oscillation＇ and ＇loops＇. We compare the new method with the uni- form method, chord length method and the centripetal method. The comparison is performed on the quality of cubic spline curves using these methods. In most cases, the result of our method is better than others.
文摘This paper investigates the adaptability of Maximum Power Point Tracking (MPPT) algorithms in single-stage three-phase photovoltaic (PV) systems connected to the grid of Congo-Brazzaville and compares the attributes of various conventional, significance and novelty of controller system of the proposed of method and improved Incremental Conductance algorithms, Perturbation and Observation Techniques, and other Maximum Power Point Tracking (MPPT) algorithms in normal and partial shading conditions. Performance evaluation techniques are discussed on the basis of the dynamic parameters of the PV system although the control of this structure is relatively advanced technology but the conversion efficiency is difficult to improve due to increase in transformation series. The single stage topology has a simple topology with high reliability and efficiency because of high power consumption, but control algorithm is more complex because of its power convert main circuit a new strategy is being developed. This paper describes a method for maximum power point tracking (MPPT) in the single-stage and three single-phase PV grid-connected system. In the paper, the nonlinear output characteristics of the PV including I-V & P-V are obtained in changed solar insulations or temperature based on MATLAB, and the MPPT algorithm which is based on the P & O algorithm method, compared with Incremental Conductance, is also described, a dimensioning of the impedance adapter for better stabilization. A comparison SPWM and SVPWM control methods in the case of a grid connection applied to the electrical grid of Republic of Congo and their influences on the dynamic performance of the system and their impact in reducing the harmonic rate for better injection into the grid. The simulation model of three single-phase PV grid-connected system is built, and simulation results show the MPPT algorithm has excellent dynamic and static performances, which verifies the Incremental Conductance is effective for MPPT in the single-stage and three single-phase PV grid-connected system.
基金supported by the National Natural Science Foundation of China(No.82202267,82202095,82372042,82272084)Regional Innovation and Development Joint Fund of National Natural Science Foundation of China(No.U22A20345,U23A20478)+5 种基金National Science Fund for Distinguished Young Scholars of China(No.81925023)Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application(No.2022B1212010011)Guangxi Natural Science Foundation(No.2024GXNSFFA010014)Science and Technology Projects in Guangzhou(No.2024A04J4977)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011339)High-level Hospital Construction Project(No.DFJHBF202105).
文摘Background:Whole-slide image(WSI)is foundational for artificial intelligence in tumor diagnosis,treatment planning,and prognosis prediction.Efficient management of WSI labels is crucial for clinical digitalization;however,manual or semiautomatic methods limit scalability.Enhancing automatic pathological label recognition is critical to advancing digital pathology,improving efficiency,and drive precision oncology.Methods:We developed Auto LDP,a method for automatic labeling of digital pathology,which identifies textual information used for labeling slides.The method includes four steps:identifying text position using the CRAFT model,recognizing text content using the ParSeq model,identifying slice type using the ConvNext classifier,and combining relevant information to generate a new name.The naming format is divided into four parts:pathology ID,wax block ID,staining type,and slice type.We used the accuracy and processing time to validate our method using two validation sets.Results:The AutoLDP system was 20 times faster than manual labeling.The files per minute in the solid-state drives of CRAFT t ParSeq were the highest among all methods at 136.95 in validation set 1 and 170.95 in validation set 2.We compared the proposed model with several commonly used text detection and recognition models including ABinet,CRNN,TRBA,and Vitstr.The results show that we achieved an accuracy of 97.60%in just 87.62 s in validation set 1 with 200 cases,which was significantly better than that of the other models.In addition,the accuracy reached 96.98% in validation set 2 with 13,667 cases,confirming the generalization ability of the model.Conclusion:In this study,we proposed a new model,AutoLDP,automates the extraction and recognition of key information from WSI,enabling standardized naming,and significantly improving labeling efficiency.This innovation supports the digital transformation of pathology and advances precision medicine.
基金supported by the Major science and technology project of Hainan Province(Grant No.ZDKJ2020012)National Natural Science Foundation of China(Grant No.62162024 and 62162022)Key Projects in Hainan Province(Grant ZDYF2021GXJS003 and Grant ZDYF2020040).
文摘With the increasing number of smart devices and the development of machine learning technology,the value of users’personal data is becoming more and more important.Based on the premise of protecting users’personal privacy data,federated learning(FL)uses data stored on edge devices to realize training tasks by contributing training model parameters without revealing the original data.However,since FL can still leak the user’s original data by exchanging gradient information.The existing privacy protection strategy will increase the uplink time due to encryption measures.It is a huge challenge in terms of communication.When there are a large number of devices,the privacy protection cost of the system is higher.Based on these issues,we propose a privacy-preserving scheme of user-based group collaborative federated learning(GrCol-PPFL).Our scheme primarily divides participants into several groups and each group communicates in a chained transmission mechanism.All groups work in parallel at the same time.The server distributes a random parameter with the same dimension as the model parameter for each participant as a mask for the model parameter.We use the public datasets of modified national institute of standards and technology database(MNIST)to test the model accuracy.The experimental results show that GrCol-PPFL not only ensures the accuracy of themodel,but also ensures the security of the user’s original data when users collude with each other.Finally,through numerical experiments,we show that by changing the number of groups,we can find the optimal number of groups that reduces the uplink consumption time.
基金Supported by Joint Fundation for Equipment Pre-research of Aerospace Science and Technology
文摘Traditional scheduling algorithms for avionics communication have the shortcoming of messages accumulation,the efficiency and reliability of the service can be improved by combining the distributed integrated modular avionics(DIMA)system with a time trigger mechanism.To further improve the utilization of system resources,the static scheduling algorithm of time triggered service is studied.By making the time trigger message schedule dispersedly,the stabilities of both the available time slots for the event triggered messages and the system will be improved.An improved two-dimensional bin packing algorithm is also presented to achieve the above-mentioned purpose with an extra benefit of better delay performance.
基金Supported by Shandong Province Natural Science Foundation(No.ZR2011FL028)
文摘According to X-ray image texture tire characteristics and abnormal distribution of the gray area, this paper studies a real-time defect detection method about the sidewall of tire. On the basis of the texture distribution characteristics of X-ray tire, we extract the cord information of the tire image by maximizing the distance of the categories after the gray value correction, then we use the morphology method and statistics method to process the image so that we can get the location and the size of impurities. We can classify the tires into different grades by the information. Compared with other methods, our method has the advantage that meets the needs of tire industry.
基金supported by the National Natural Science Foundation of China (Grand Nos.62072128,11901579,11801564)the Natural Science Foundation of Shaanxi (2022JQ-046,2021JQ-335,2021JM-216).
文摘Federated learning(FL)has emerged to break data-silo and protect clients’privacy in the field of artificial intelligence.However,deep leakage from gradient(DLG)attack can fully reconstruct clients’data from the submitted gradient,which threatens the fundamental privacy of FL.Although cryptology and differential privacy prevent privacy leakage from gradient,they bring negative effect on communication overhead or model performance.Moreover,the original distribution of local gradient has been changed in these schemes,which makes it difficult to defend against adversarial attack.In this paper,we propose a novel federated learning framework with model decomposition,aggregation and assembling(FedDAA),along with a training algorithm,to train federated model,where local gradient is decomposed into multiple blocks and sent to different proxy servers to complete aggregation.To bring better privacy protection performance to FedDAA,an indicator is designed based on image structural similarity to measure privacy leakage under DLG attack and an optimization method is given to protect privacy with the least proxy servers.In addition,we give defense schemes against adversarial attack in FedDAA and design an algorithm to verify the correctness of aggregated results.Experimental results demonstrate that FedDAA can reduce the structural similarity between the reconstructed image and the original image to 0.014 and remain model convergence accuracy as 0.952,thus having the best privacy protection performance and model training effect.More importantly,defense schemes against adversarial attack are compatible with privacy protection in FedDAA and the defense effects are not weaker than those in the traditional FL.Moreover,verification algorithm of aggregation results brings about negligible overhead to FedDAA.
基金supported by the National High Technology Research and Development Program of China(863 Program )(Grant No: 2015AA01A705)the National Basic Research Program of China (Grant No:2012CB316100)+1 种基金Key Grant Project of Chinese Ministry of Education (Grant No:311031 100)Young Innovative Research Team of Sichuan Province (Grant No:2011JTD0007)
文摘In DVB-IPDC system, due to the constraints of handheld devices and the broadcast nature of wireless network, packet loss is inevitable. ECDR-NC proposed is a retransmission encoding packet selection algorithm based on the dynamic information updating, which can find the current most effective complete decoding packet. ECDR-NC can not only avoid the redundant encoding packets due to the overlapping among encoding packets, but also reduce the computational complexity compared with the traditional encoding schemes. Furthermore, the retransmission upper bound of ECDR-NC is fully controlled. In time-sensitive applications, to maximize the aggregate number of recovery packets while minimizing the total number of discarded packets due to the time limit according to the priority preference, the adaptive priority scheme EPNC is formulized, and the weighted relation graph is constructed to find the maximum-weighted encoding packets sequence according to the decoding gains. In the same network environment, the performances comparisons between PNC and EPNC show that EPNC is more efficient and more rational, and the average discarded packets ratios ofEPNC can be reduced about 18%~27%. The main contributions of this paper are an effective retransmission encoding packet selection algorithm ECDR-NC proposed, and a new adaptive priority recovery scheme EPNC introduced into DVB-IPDC system.
基金Supported by the National Natural Science Foundation of China(60903196)
文摘Coin-flipping protocols allow mutually distrustful parties to generate a random bit with uniform distribution.Minimizing bias and keeping fairness are two key requirements in designing such protocols.However,the best previously known fair coin-flipping protocol only guarantees with bias Ο（1 /r）.In the paper,we introduce a new approach for fair coin-flipping protocol construction by using Garay et al’s ＂resource fairness＂ technique and propose a resource-fair two-party coin-flipping protocol according to the standard real/ideal simulation paradigm.Compared with the other coin-flipping protocols,our protocol enjoys an important advantage that its bias is 0.
基金supported by the Sichuan Science and Technology Program(2018GZDZX0041)the National Key R&D Program of China(2018YFB1005100,2018YFB1005104)Specialized Fund for Science and Technology Platform and Talent Team Project of Guizhou Province(Qian Ke He Ping TaiRen Cai[2016]5609)。
文摘Dynamic geometry software, as a piece of computer-assisted instruction(CAI) software, is closely and deeply associated with mathematics, and is widely applied to mathematics teaching activities in primary and secondary schools. Meanwhile, web technology also has become an important technology for assisting education and teaching. This paper expounds a web-based dynamic geometry software development process, and analyses specific requirements regarding graphical application programming interface(API) required by dynamic geometry software. With experiments and comparison on the two different hypertext markup language(HTML)5 graphical API technologies, i.e., scalable vector graphics(SVG) and Canvas, on different apparatuses and browsers, we draw the conclusion that it is more suitable to adopt Canvas as the graphical API technology for the web-based dynamic geometry software, thus further proposed the principles and methods for an object-oriented Canvas design. The dynamic geometry software based on the newly-designed Canvas has technical advantages and educational value, well incorporating aesthetic education into mathematics education.
基金supported by the National Natural Science Foundation of China under Grant 92046001,61962009,the JSPS KAKENHI Grant Numbers JP19K20250,JP20H04174,JP22K11989Leading Initiative for Excellent Young Researchers (LEADER),MEXT,Japan,and JST,PRESTO Grant Number JPMJPR21P3+1 种基金Japan.Mianxiong Dong is the corresponding author,the Doctor Scientific Research Fund of Zhengzhou University of Light Industry under Grant 2021BSJJ033Key Scientific Research Project of Colleges and Universities in Henan Province (CN)under Grant No.22A413010.
文摘Internet of Medical Things(IoMT)plays an essential role in collecting and managing personal medical data.In recent years,blockchain technology has put power in traditional IoMT systems for data sharing between different medical institutions and improved the utilization of medical data.However,some problems in the information transfer process between wireless medical devices and mobile medical apps,such as information leakage and privacy disclosure.This paper first designs a cross-device key agreement model for blockchain-enabled IoMT.This model can establish a key agreement mechanism for secure medical data sharing.Meanwhile,a certificateless authenticated key agreement(KA)protocol has been proposed to strengthen the information transfer security in the cross-device key agreement model.The proposed KA protocol only requires one exchange of messages between the two parties,which can improve the protocol execution efficiency.Then,any unauthorized tampering of the transmitted signed message sent by the sender can be detected by the receiver,so this can guarantee the success of the establishment of a session key between the strange entities.The blockchain ledger can ensure that the medical data cannot be tampered with,and the certificateless mechanism can weaken the key escrow problem.Moreover,the security proof and performance analysis are given,which show that the proposed model and KA protocol are more secure and efficient than other schemes in similar literature.
