The emergence of different computing methods such as cloud-,fog-,and edge-based Internet of Things(IoT)systems has provided the opportunity to develop intelligent systems for disease detection.Compared to other machin...The emergence of different computing methods such as cloud-,fog-,and edge-based Internet of Things(IoT)systems has provided the opportunity to develop intelligent systems for disease detection.Compared to other machine learning models,deep learning models have gained more attention from the research community,as they have shown better results with a large volume of data compared to shallow learning.However,no comprehensive survey has been conducted on integrated IoT-and computing-based systems that deploy deep learning for disease detection.This study evaluated different machine learning and deep learning algorithms and their hybrid and optimized algorithms for IoT-based disease detection,using the most recent papers on IoT-based disease detection systems that include computing approaches,such as cloud,edge,and fog.Their analysis focused on an IoT deep learning architecture suitable for disease detection.It also recognizes the different factors that require the attention of researchers to develop better IoT disease detection systems.This study can be helpful to researchers interested in developing better IoT-based disease detection and prediction systems based on deep learning using hybrid algorithms.展开更多
The material characteristics of a structure will change with temperature variation,and will induce stress within the structure.Currently,the optimal design for the topology of compliant mechanisms is mainly performed ...The material characteristics of a structure will change with temperature variation,and will induce stress within the structure.Currently,the optimal design for the topology of compliant mechanisms is mainly performed in single physical field.However,when compliant mechanisms work in high temperature environments,their displacement outputs are generated not only by mechanical load,but also by the temperature variation which may become the prominent factor.Therefore,the influence of temperature must be considered in the design.In this paper,a novel optimization method for multi-objective topology of thermo-mechanical compliant mechanisms is presented.First,the thermal field is analyzed with finite-element method,where the thermal strain is taken into account in the constitutive relation,and the equivalent nodal thermal load is derived with the principle of virtual work.Then the thermal load is converted into physical loads in elastic field,and the control equation of the thermo-mechanical compliant mechanism is obtained.Second,the mathematical model of the multi-objective topology optimization is built by incorporating both the flexibility and stiffness.Meanwhile,the coupling sensitivity function and the sensitivity analysis equations of thermal steady-state response are derived.Finally,optimality criteria algorithm is employed to obtain numerical solution of the multi-objective topology optimization.Numerical examples show that the compliant mechanisms have better performance and are more applicable if the temperature effect is taken into account in the design process.The presented modeling and analysis methods provide a new idea and an effective approach to topology optimization of compliant mechanisms in electrothermic coupling field and multiphysics fields.展开更多
Aerial imagery is regularly used by crop researchers,growers and farmers to monitor crops during the growing season.To extract meaningful information from large-scale aerial images collected from the field,high-throug...Aerial imagery is regularly used by crop researchers,growers and farmers to monitor crops during the growing season.To extract meaningful information from large-scale aerial images collected from the field,high-throughput phenotypic analysis solutions are required,which not only produce high-quality measures of key crop traits,but also support professionals to make prompt and reliable crop management decisions.Here,we report AirSurf,an automated and open-source analytic platform that combines modern computer vision,up-to-date machine learning,and modular software engineering in order to measure yield-related phenotypes from ultra-large aerial imagery.To quantify millions of in-field lettuces acquired by fixed-wing light aircrafts equipped with normalised difference vegetation index(NDVI)sensors,we customised AirSurf by combining computer vision algorithms and a deep-learning classifier trained with over 100,000 labelled lettuce signals.The tailored platform,AirSurf-Lettuce,is capable of scoring and categorising iceberg lettuces with high accuracy(>98%).Furthermore,novel analysis functions have been developed to map lettuce size distribution across the field,based on which associated global positioning system(GPS)tagged harvest regions have been identified to enable growers and farmers to conduct precision agricultural practises in order to improve the actual yield as well as crop marketability before the harvest.展开更多
We assessed nutrient characteristics, distributions and fractions within the disturbed and undisturbed sediments at four sampling sites within the mainstream of Haihe River. The river sediments contained mostly sand ...We assessed nutrient characteristics, distributions and fractions within the disturbed and undisturbed sediments at four sampling sites within the mainstream of Haihe River. The river sediments contained mostly sand （ 60%）. The fraction of clay was 3%. Total nitrogen （TN） and total phosphorus （TP） concentrations ranged from 729 to 1922 mg/kg and from 692 to 1388 mg/kg, respectively. Nutrient concentrations within the sediments usually decreased with increasing depth. The TN and TP concentrations within the fine sand were higher than for that within silt. Sediment phosphorus fractions were between 2.99% and 3.37% Ex-P （exchangeable phosphorus）, 7.89% and 13.71% Fe/Al-P （Fe, Al oxides bound phosphorus）, 61.32% and 70.14% Ca-P （calcium-bound phosphorus）, and 17.03% and 22.04% Org-P （organic phosphorus）. Nitrogen and phosphorus release from sediment could lead to the presence of 21.02 mg N/L and 3.10 mg P/L within the water column. A river restoration project should address the sediment nutrient stock.展开更多
With the development of online social networks,a special group of online users named organized posters(or Internet water army,Internet paid posters in some literatures) have fl ooded the social network communities. Th...With the development of online social networks,a special group of online users named organized posters(or Internet water army,Internet paid posters in some literatures) have fl ooded the social network communities. They are organized in groups to post with specific purposes and sometimes even confuse or mislead normal users.In this paper,we study the individual and group characteristics of organized posters. A classifier is constructed based on the individual and group characteristics to detect them. Extensive experimental results on three real datasets demonstrate that our method based on individual and group characteristics using SVM model(IGCSVM) is effective in detecting organized posters and better than existing methods. We take a first look at finding the promoters based on the detected organized posters of our IGCSVM method. Our experiments show that it is effective in detecting promoters.展开更多
Nowadays,with the widespread application of the Internet of Things(IoT),mobile devices are renovating our lives.The data generated by mobile devices has reached a massive level.The traditional centralized processing i...Nowadays,with the widespread application of the Internet of Things(IoT),mobile devices are renovating our lives.The data generated by mobile devices has reached a massive level.The traditional centralized processing is not suitable for processing the data due to limited computing power and transmission load.Mobile Edge Computing(MEC)has been proposed to solve these problems.Because of limited computation ability and battery capacity,tasks can be executed in the MEC server.However,how to schedule those tasks becomes a challenge,and is the main topic of this piece.In this paper,we design an efficient intelligent algorithm to jointly optimize energy cost and computing resource allocation in MEC.In view of the advantages of deep learning,we propose a Deep Learning-Based Traffic Scheduling Approach(DLTSA).We translate the scheduling problem into a classification problem.Evaluation demonstrates that our DLTSA approach can reduce energy cost and have better performance compared to traditional scheduling algorithms.展开更多
The complex composition of herbal metabolites necessitates the development of powerful analytical techniques aimed to identify the bioactive components.The seeds of Descurainia sophia(SDS)are utilized in China as a co...The complex composition of herbal metabolites necessitates the development of powerful analytical techniques aimed to identify the bioactive components.The seeds of Descurainia sophia(SDS)are utilized in China as a cough and asthma relieving agent.Herein,a dimension-enhanced integral approach,by combining ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry(UHPLC/IMQTOF-MS)and intelligent peak annotation,was developed to rapidly characterize the multicomponents from SDS.Good chromatographic separation was achieved within 38 min on a UPLC CSH C18(2.1×100 mm,1.7μm)column which was eluted by 0.1%formic acid in water(water phase)and acetonitrile(organic phase).Collision-induced dissociation-MS^(2)data were acquired by the data-independent high-definition MS^(E)(HDMS^(E))in both the negative and positive electrospray ionization modes.A major components knockout strategy was applied to improve the characterization of those minor ingredients by enhancing the injection volume.Moreover,a self-built chemistry library was established,which could be matched by the UNIFI software enabling automatic peak annotation of the obtained HDMS^(E)data.As a result of applying the intelligent peak annotation workflows and further confirmation process,a total of 53 compounds were identified or tentatively characterized from the SDS,including 29 flavonoids,one uridine derivative,four glucosides,one lignin,one phenolic compound,and 17 others.Notably,four-dimensional information related to the structure(e.g.,retention time,collision cross section,MS^(1)and MS^(2)data)was obtained for each component by the developed integral approach,and the results would greatly benefit the quality control of SDS.展开更多
The widespread and growing interest in the Internet of Things(IoT)may be attributed to its usefulness in many different fields.Physical settings are probed for data,which is then transferred via linked networks.There ...The widespread and growing interest in the Internet of Things(IoT)may be attributed to its usefulness in many different fields.Physical settings are probed for data,which is then transferred via linked networks.There are several hurdles to overcome when putting IoT into practice,from managing server infrastructure to coordinating the use of tiny sensors.When it comes to deploying IoT,everyone agrees that security is the biggest issue.This is due to the fact that a large number of IoT devices exist in the physicalworld and thatmany of themhave constrained resources such as electricity,memory,processing power,and square footage.This research intends to analyse resource-constrained IoT devices,including RFID tags,sensors,and smart cards,and the issues involved with protecting them in such restricted circumstances.Using lightweight cryptography,the information sent between these gadgets may be secured.In order to provide a holistic picture,this research evaluates and contrasts well-known algorithms based on their implementation cost,hardware/software efficiency,and attack resistance features.We also emphasised how essential lightweight encryption is for striking a good cost-to-performance-to-security ratio.展开更多
Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when deal...Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.展开更多
This paper presents the preclinical evaluation of a novel immobilization system for patients undergoing external beam radiation treatment of head and neck tumors. An immobilization mask is manufactured directly from a...This paper presents the preclinical evaluation of a novel immobilization system for patients undergoing external beam radiation treatment of head and neck tumors. An immobilization mask is manufactured directly from a 3-D model, built using the CT data routinely acquired for treatment planning so there is no need to take plaster of Paris moulds. Research suggests that many patients find the mould room visit distressing and so rapid prototyping could potentially improve the overall patient experience. Evaluation of a computer model of the immobilization system using an anthropomorphic phantom shows that >99% of vertices are within a tolerance of ±0.2 mm. Hausdorff distance was used to analyze CT slices obtained by rescanning the phantom with a printed mask in position. These results show that for >80% of the slices the median “worse-case” tolerance is approximately 4 mm. These measurements suggest that printed masks can achieve similar levels of immobilization to those of systems currently in clinical use.展开更多
Distributed denial of service (DDoS) attacks continues to grow as a threat to organizations worldwide. From the first known attack in 1999 to the highly publicized Operation Ababil, the DDoS attacks have a history of ...Distributed denial of service (DDoS) attacks continues to grow as a threat to organizations worldwide. From the first known attack in 1999 to the highly publicized Operation Ababil, the DDoS attacks have a history of flooding the victim network with an enormous number of packets, hence exhausting the resources and preventing the legitimate users to access them. After having standard DDoS defense mechanism, still attackers are able to launch an attack. These inadequate defense mechanisms need to be improved and integrated with other solutions. The purpose of this paper is to study the characteristics of DDoS attacks, various models involved in attacks and to provide a timeline of defense mechanism with their improvements to combat DDoS attacks. In addition to this, a novel scheme is proposed to detect DDoS attack efficiently by using MapReduce programming model.展开更多
This study is to illustrate alpine vegetation dynamics in Qinghai-Tibetan Plateau of China from simulated filed experimental climate change, vegetation community dynamic simulation integrated with scenarios of global ...This study is to illustrate alpine vegetation dynamics in Qinghai-Tibetan Plateau of China from simulated filed experimental climate change, vegetation community dynamic simulation integrated with scenarios of global temperature increase of 1 to 3°C, and simulated regional alpine vegetation distribution changes in responses to global warming. Our warming treatment increased air temperatures by 5°C on average and soil temperatures were elevated by 3°C at 5 cm depth. Above- ground biomass of grasses responded rapidly to the warmer conditions whereby biomass was 25% greater than that of controls after only 5 wk of experimental warming. This increase was accompanied by a simultaneous decrease in forb biomass, resulting in almost no net change in community biomass after 5 wk. Under warmed conditions, peak community bio-mass was extended into October due in part to continued growth of grasses and the postponement of senescence. The Vegetation Dynamic Simulation Model calculates a probability surface for each vegetation type, and then combines all vegetation types into a composite map, determined by the maximum likelihood that each vegetation type should distribute to each raster unit. With scenarios of global temperature increase of 1°C to 3°C, the vegetation types such as Dry Kobresia Meadow and Dry Potentilla Shrub that are adapted to warm and dry conditions tend to become more dominant in the study area.展开更多
The integration of the two fast-developing scientific research areas Semantic Web and Web Mining is known as Semantic Web Mining. The huge increase in the amount of Semantic Web data became a perfect target for many r...The integration of the two fast-developing scientific research areas Semantic Web and Web Mining is known as Semantic Web Mining. The huge increase in the amount of Semantic Web data became a perfect target for many researchers to apply Data Mining techniques on it. This paper gives a detailed state-of-the-art survey of on-going research in this new area. It shows the positive effects of Semantic Web Mining, the obstacles faced by researchers and propose number of approaches to deal with the very complex and heterogeneous information and knowledge which are produced by the technologies of Semantic Web.展开更多
Background In the past few years,augmented reality(AR)has rapidly advanced and has been applied in different fields.One of the successful AR applications is the immersive and interactive serious games,which can be use...Background In the past few years,augmented reality(AR)has rapidly advanced and has been applied in different fields.One of the successful AR applications is the immersive and interactive serious games,which can be used for education and learning purposes.Methods In this project,a prototype of an AR serious game is developed and demonstrated.Gamers utilize a head-mounted device and a vibrotactile feedback jacket to explore and interact with the AR serious game.Fourteen vibration actuators are embedded in the vibrotactile feedback jacket to generate immersive AR experience.These vibration actuators are triggered in accordance with the designed game scripts.Various vibration patterns and intensity levels are synthesized in different game scenes.This article presents the details of the entire software development of the AR serious game,including game scripts,game scenes with AR effects design,signal processing flow,behavior design,and communication configuration.Graphics computations are processed using the graphics processing unit in the system.Results/Conclusions The performance of the AR serious game prototype is evaluated and analyzed.The computation loads and resource utilization of normal game scenes and heavy computation scenes are compared.With 14 vibration actuators placed at different body positions,various vibration patterns and intensity levels can be generated by the vibrotactile feedback jacket,providing different real-world feedback.The prototype of this AR serious game can be valuable in building large-scale AR or virtual reality educational and entertainment games.Possible future improvements of the proposed prototype are also discussed in this article.展开更多
Smart environment is being used in many areas to deliver more services to individuals in a physical space, such as a hospital. In the UK, the National Health Service(NHS) provides free and high quality healthcare serv...Smart environment is being used in many areas to deliver more services to individuals in a physical space, such as a hospital. In the UK, the National Health Service(NHS) provides free and high quality healthcare service for all residents. Smart hospital environment is able to support NHS and provide more convenience. Patient flow scheduling is a crucial section in a smart hospital environment. Smart hospital environment aims to provide a smart environment in the hospital to facilitate individual experience and improve the quality of healthcare service.First of all, this paper investigates a real world patient flow scenario of a hospital in the UK and models a general scheduling scheme based on the scenario using a compositional formal approach, i.e. performance evaluation process algebra(PEPA). This scheduling scheme uses an easy-implemented solution(the grouping scheme) to reduce the waiting queue in the hospital. Secondly, fluid flow analysis is used for the performance analysis by generating a set of ordinary differential equations(ODEs) in terms of the PEPA model.展开更多
Cloud computing is a novel computing paradigm that utilizes remote cloud resources to achieve a high-performance computation.Cloud provides infrastructure,platform and software as different on-demand services.China ha...Cloud computing is a novel computing paradigm that utilizes remote cloud resources to achieve a high-performance computation.Cloud provides infrastructure,platform and software as different on-demand services.China has made remarkable progress in cloudbased products and operating system technology.The government,enterprises and research institutions are all active in the development of cloud computing-related projects.Despite the progress,many important展开更多
This paper considers the geometric design of crab-like walkers and climbers, without decoupling leg design from overall machine design. Crab-like machines represent an important sub-class of multi-legged robots, bein...This paper considers the geometric design of crab-like walkers and climbers, without decoupling leg design from overall machine design. Crab-like machines represent an important sub-class of multi-legged robots, being particularly well suited to crossing difficult terrains. Firstly, the kinematic configurations and constraints are described, which determine the machine’s kinematic characteristics. The influence of the design parameters on the kinematic workspace is discussed. Finally, a two stage design methodology is presented, comprising kinematic design and design optimisation, the latter being based on the use of design maps rather than numerical optimisation. The performance measures considered during design optimisation include kinematic, static and quasi-static measures.展开更多
In the present scenario of rapid growth in cloud computing models,several companies and users started to share their data on cloud servers.However,when the model is not completely trusted,the data owners face several ...In the present scenario of rapid growth in cloud computing models,several companies and users started to share their data on cloud servers.However,when the model is not completely trusted,the data owners face several security-related problems,such as user privacy breaches,data disclosure,data corruption,and so on,during the process of data outsourcing.For addressing and handling the security-related issues on Cloud,several models were proposed.With that concern,this paper develops a Privacy-Preserved Data Security Approach(PP-DSA)to provide the data security and data integrity for the out-sourcing data in Cloud Environment.Privacy preservation is ensured in this work with the Efficient Authentication Technique(EAT)using the Group Signature method that is applied with Third-Party Auditor(TPA).The role of the auditor is to secure the data and guarantee shared data integrity.Additionally,the Cloud Service Provider(CSP)and Data User(DU)can also be the attackers that are to be handled with the EAT.Here,the major objective of the work is to enhance cloud security and thereby,increase Quality of Service(QoS).The results are evaluated based on the model effectiveness,security,and reliability and show that the proposed model provides better results than existing works.展开更多
A metamaterial absorber is computed numerically and measured experimentally in a 150-THz^300-THz range.The measured absorber achieves high absorption rate for both transverse electric（TE） and transverse magnetic（TM...A metamaterial absorber is computed numerically and measured experimentally in a 150-THz^300-THz range.The measured absorber achieves high absorption rate for both transverse electric（TE） and transverse magnetic（TM） polarizations at large angles of incidence.An absorption sensor scheme is proposed based on the measured absorber and the variations of surrounding media.Different surrounding media are applied to the surface of the absorption sensor（including air,water,and glucose solution）.Measured results show that high figure of merit（FOM） values are obtained for different surrounding media.The proposed sensor does not depend on the substrate,which means that it can be transplanted to different sensing platforms conveniently.展开更多
文摘The emergence of different computing methods such as cloud-,fog-,and edge-based Internet of Things(IoT)systems has provided the opportunity to develop intelligent systems for disease detection.Compared to other machine learning models,deep learning models have gained more attention from the research community,as they have shown better results with a large volume of data compared to shallow learning.However,no comprehensive survey has been conducted on integrated IoT-and computing-based systems that deploy deep learning for disease detection.This study evaluated different machine learning and deep learning algorithms and their hybrid and optimized algorithms for IoT-based disease detection,using the most recent papers on IoT-based disease detection systems that include computing approaches,such as cloud,edge,and fog.Their analysis focused on an IoT deep learning architecture suitable for disease detection.It also recognizes the different factors that require the attention of researchers to develop better IoT disease detection systems.This study can be helpful to researchers interested in developing better IoT-based disease detection and prediction systems based on deep learning using hybrid algorithms.
基金supported by National Science Foundation for Distinguished Young Scholars of China (Grant No. 50825504)United Fund of National Natural Science Foundation of China and Guangdong Province (Grant No. U0934004)+1 种基金National Hi-tech Research and Development Program of National China (863 Program, Grant No. 2009AA04Z204)Fundamental Research Funds for the Central Universities (Grant No. D2102380)
文摘The material characteristics of a structure will change with temperature variation,and will induce stress within the structure.Currently,the optimal design for the topology of compliant mechanisms is mainly performed in single physical field.However,when compliant mechanisms work in high temperature environments,their displacement outputs are generated not only by mechanical load,but also by the temperature variation which may become the prominent factor.Therefore,the influence of temperature must be considered in the design.In this paper,a novel optimization method for multi-objective topology of thermo-mechanical compliant mechanisms is presented.First,the thermal field is analyzed with finite-element method,where the thermal strain is taken into account in the constitutive relation,and the equivalent nodal thermal load is derived with the principle of virtual work.Then the thermal load is converted into physical loads in elastic field,and the control equation of the thermo-mechanical compliant mechanism is obtained.Second,the mathematical model of the multi-objective topology optimization is built by incorporating both the flexibility and stiffness.Meanwhile,the coupling sensitivity function and the sensitivity analysis equations of thermal steady-state response are derived.Finally,optimality criteria algorithm is employed to obtain numerical solution of the multi-objective topology optimization.Numerical examples show that the compliant mechanisms have better performance and are more applicable if the temperature effect is taken into account in the design process.The presented modeling and analysis methods provide a new idea and an effective approach to topology optimization of compliant mechanisms in electrothermic coupling field and multiphysics fields.
基金the support of NVIDIA Corporation with the award of the Quadro GPU used for this research.J.Z.was partially funded by UKRI Biotechnology and Biological Sciences Research Council’s(BBSRC)Designing Future Wheat Cross-institute Strategic Programme(BB/P016855/1)to Graham Moore,BBS/E/T/000PR9785 to J.Z.J.B.were partially supported by the Core Strategic Programme Grant(BB/CSP17270/1)at the Earlham Institute+1 种基金A.G.B.and C.A.were also partially supported by G’s Growers’s industrial fund awarded to J.Z.A.B.was partially supported by the Newton UK-China Agri-Tech Network+Grant(GP131JZ1G)awarded to J.Z.
文摘Aerial imagery is regularly used by crop researchers,growers and farmers to monitor crops during the growing season.To extract meaningful information from large-scale aerial images collected from the field,high-throughput phenotypic analysis solutions are required,which not only produce high-quality measures of key crop traits,but also support professionals to make prompt and reliable crop management decisions.Here,we report AirSurf,an automated and open-source analytic platform that combines modern computer vision,up-to-date machine learning,and modular software engineering in order to measure yield-related phenotypes from ultra-large aerial imagery.To quantify millions of in-field lettuces acquired by fixed-wing light aircrafts equipped with normalised difference vegetation index(NDVI)sensors,we customised AirSurf by combining computer vision algorithms and a deep-learning classifier trained with over 100,000 labelled lettuce signals.The tailored platform,AirSurf-Lettuce,is capable of scoring and categorising iceberg lettuces with high accuracy(>98%).Furthermore,novel analysis functions have been developed to map lettuce size distribution across the field,based on which associated global positioning system(GPS)tagged harvest regions have been identified to enable growers and farmers to conduct precision agricultural practises in order to improve the actual yield as well as crop marketability before the harvest.
基金supported by the National Natural Sci- ence Foundation of China (No. 51079068)the Natural Science Foundation of Tianjin (No. 09ZCGYSF00400, 08FDZDSF03402)+1 种基金the National Key-Projects of Water Pollution Control and Prevention (No. 2008ZX07314-005- 001, 2009ZX07209-001)funded by The Royal Society
文摘We assessed nutrient characteristics, distributions and fractions within the disturbed and undisturbed sediments at four sampling sites within the mainstream of Haihe River. The river sediments contained mostly sand （ 60%）. The fraction of clay was 3%. Total nitrogen （TN） and total phosphorus （TP） concentrations ranged from 729 to 1922 mg/kg and from 692 to 1388 mg/kg, respectively. Nutrient concentrations within the sediments usually decreased with increasing depth. The TN and TP concentrations within the fine sand were higher than for that within silt. Sediment phosphorus fractions were between 2.99% and 3.37% Ex-P （exchangeable phosphorus）, 7.89% and 13.71% Fe/Al-P （Fe, Al oxides bound phosphorus）, 61.32% and 70.14% Ca-P （calcium-bound phosphorus）, and 17.03% and 22.04% Org-P （organic phosphorus）. Nitrogen and phosphorus release from sediment could lead to the presence of 21.02 mg N/L and 3.10 mg P/L within the water column. A river restoration project should address the sediment nutrient stock.
基金supported by 973 Program of China(Grant No.2013CB329601, 2013CB329602,2013CB329604)NSFC of China(Grant No.60933005,91124002)+1 种基金863 Program of China(Grant No.2012AA01A401, 2012AA01A402)National Key Technology RD Program of China(Grant No.2012BAH38B04, 2012BAH38B06)
文摘With the development of online social networks,a special group of online users named organized posters(or Internet water army,Internet paid posters in some literatures) have fl ooded the social network communities. They are organized in groups to post with specific purposes and sometimes even confuse or mislead normal users.In this paper,we study the individual and group characteristics of organized posters. A classifier is constructed based on the individual and group characteristics to detect them. Extensive experimental results on three real datasets demonstrate that our method based on individual and group characteristics using SVM model(IGCSVM) is effective in detecting organized posters and better than existing methods. We take a first look at finding the promoters based on the detected organized posters of our IGCSVM method. Our experiments show that it is effective in detecting promoters.
基金supported in part by the National Natural Science Foun-dation of China(61902029)R&D Program of Beijing Municipal Education Commission(No.KM202011232015)Project for Acceleration of University Classi cation Development(Nos.5112211036,5112211037,5112211038).
文摘Nowadays,with the widespread application of the Internet of Things(IoT),mobile devices are renovating our lives.The data generated by mobile devices has reached a massive level.The traditional centralized processing is not suitable for processing the data due to limited computing power and transmission load.Mobile Edge Computing(MEC)has been proposed to solve these problems.Because of limited computation ability and battery capacity,tasks can be executed in the MEC server.However,how to schedule those tasks becomes a challenge,and is the main topic of this piece.In this paper,we design an efficient intelligent algorithm to jointly optimize energy cost and computing resource allocation in MEC.In view of the advantages of deep learning,we propose a Deep Learning-Based Traffic Scheduling Approach(DLTSA).We translate the scheduling problem into a classification problem.Evaluation demonstrates that our DLTSA approach can reduce energy cost and have better performance compared to traditional scheduling algorithms.
基金This work was financially supported by the National Key Research and Development Program of China(Grant No.2018YFC1704500)Tianjin Committee of Science and Technology of China(Grant No.21ZYJDJC00080)National Natural Science Foundation of China(Grant No.81872996).
文摘The complex composition of herbal metabolites necessitates the development of powerful analytical techniques aimed to identify the bioactive components.The seeds of Descurainia sophia(SDS)are utilized in China as a cough and asthma relieving agent.Herein,a dimension-enhanced integral approach,by combining ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry(UHPLC/IMQTOF-MS)and intelligent peak annotation,was developed to rapidly characterize the multicomponents from SDS.Good chromatographic separation was achieved within 38 min on a UPLC CSH C18(2.1×100 mm,1.7μm)column which was eluted by 0.1%formic acid in water(water phase)and acetonitrile(organic phase).Collision-induced dissociation-MS^(2)data were acquired by the data-independent high-definition MS^(E)(HDMS^(E))in both the negative and positive electrospray ionization modes.A major components knockout strategy was applied to improve the characterization of those minor ingredients by enhancing the injection volume.Moreover,a self-built chemistry library was established,which could be matched by the UNIFI software enabling automatic peak annotation of the obtained HDMS^(E)data.As a result of applying the intelligent peak annotation workflows and further confirmation process,a total of 53 compounds were identified or tentatively characterized from the SDS,including 29 flavonoids,one uridine derivative,four glucosides,one lignin,one phenolic compound,and 17 others.Notably,four-dimensional information related to the structure(e.g.,retention time,collision cross section,MS^(1)and MS^(2)data)was obtained for each component by the developed integral approach,and the results would greatly benefit the quality control of SDS.
基金supported by project TRANSACT funded under H2020-EU.2.1.1.-INDUSTRIAL LEADERSHIP-Leadership in Enabling and Industrial Technologies-Information and Communication Technologies(Grant Agreement ID:101007260).
文摘The widespread and growing interest in the Internet of Things(IoT)may be attributed to its usefulness in many different fields.Physical settings are probed for data,which is then transferred via linked networks.There are several hurdles to overcome when putting IoT into practice,from managing server infrastructure to coordinating the use of tiny sensors.When it comes to deploying IoT,everyone agrees that security is the biggest issue.This is due to the fact that a large number of IoT devices exist in the physicalworld and thatmany of themhave constrained resources such as electricity,memory,processing power,and square footage.This research intends to analyse resource-constrained IoT devices,including RFID tags,sensors,and smart cards,and the issues involved with protecting them in such restricted circumstances.Using lightweight cryptography,the information sent between these gadgets may be secured.In order to provide a holistic picture,this research evaluates and contrasts well-known algorithms based on their implementation cost,hardware/software efficiency,and attack resistance features.We also emphasised how essential lightweight encryption is for striking a good cost-to-performance-to-security ratio.
文摘Diagnosing various diseases such as glaucoma,age-related macular degeneration,cardiovascular conditions,and diabetic retinopathy involves segmenting retinal blood vessels.The task is particularly challenging when dealing with color fundus images due to issues like non-uniformillumination,low contrast,and variations in vessel appearance,especially in the presence of different pathologies.Furthermore,the speed of the retinal vessel segmentation system is of utmost importance.With the surge of now available big data,the speed of the algorithm becomes increasingly important,carrying almost equivalent weightage to the accuracy of the algorithm.To address these challenges,we present a novel approach for retinal vessel segmentation,leveraging efficient and robust techniques based on multiscale line detection and mathematical morphology.Our algorithm’s performance is evaluated on two publicly available datasets,namely the Digital Retinal Images for Vessel Extraction dataset(DRIVE)and the Structure Analysis of Retina(STARE)dataset.The experimental results demonstrate the effectiveness of our method,withmean accuracy values of 0.9467 forDRIVE and 0.9535 for STARE datasets,aswell as sensitivity values of 0.6952 forDRIVE and 0.6809 for STARE datasets.Notably,our algorithmexhibits competitive performance with state-of-the-art methods.Importantly,it operates at an average speed of 3.73 s per image for DRIVE and 3.75 s for STARE datasets.It is worth noting that these results were achieved using Matlab scripts containing multiple loops.This suggests that the processing time can be further reduced by replacing loops with vectorization.Thus the proposed algorithm can be deployed in real time applications.In summary,our proposed system strikes a fine balance between swift computation and accuracy that is on par with the best available methods in the field.
文摘This paper presents the preclinical evaluation of a novel immobilization system for patients undergoing external beam radiation treatment of head and neck tumors. An immobilization mask is manufactured directly from a 3-D model, built using the CT data routinely acquired for treatment planning so there is no need to take plaster of Paris moulds. Research suggests that many patients find the mould room visit distressing and so rapid prototyping could potentially improve the overall patient experience. Evaluation of a computer model of the immobilization system using an anthropomorphic phantom shows that >99% of vertices are within a tolerance of ±0.2 mm. Hausdorff distance was used to analyze CT slices obtained by rescanning the phantom with a printed mask in position. These results show that for >80% of the slices the median “worse-case” tolerance is approximately 4 mm. These measurements suggest that printed masks can achieve similar levels of immobilization to those of systems currently in clinical use.
文摘Distributed denial of service (DDoS) attacks continues to grow as a threat to organizations worldwide. From the first known attack in 1999 to the highly publicized Operation Ababil, the DDoS attacks have a history of flooding the victim network with an enormous number of packets, hence exhausting the resources and preventing the legitimate users to access them. After having standard DDoS defense mechanism, still attackers are able to launch an attack. These inadequate defense mechanisms need to be improved and integrated with other solutions. The purpose of this paper is to study the characteristics of DDoS attacks, various models involved in attacks and to provide a timeline of defense mechanism with their improvements to combat DDoS attacks. In addition to this, a novel scheme is proposed to detect DDoS attack efficiently by using MapReduce programming model.
文摘This study is to illustrate alpine vegetation dynamics in Qinghai-Tibetan Plateau of China from simulated filed experimental climate change, vegetation community dynamic simulation integrated with scenarios of global temperature increase of 1 to 3°C, and simulated regional alpine vegetation distribution changes in responses to global warming. Our warming treatment increased air temperatures by 5°C on average and soil temperatures were elevated by 3°C at 5 cm depth. Above- ground biomass of grasses responded rapidly to the warmer conditions whereby biomass was 25% greater than that of controls after only 5 wk of experimental warming. This increase was accompanied by a simultaneous decrease in forb biomass, resulting in almost no net change in community biomass after 5 wk. Under warmed conditions, peak community bio-mass was extended into October due in part to continued growth of grasses and the postponement of senescence. The Vegetation Dynamic Simulation Model calculates a probability surface for each vegetation type, and then combines all vegetation types into a composite map, determined by the maximum likelihood that each vegetation type should distribute to each raster unit. With scenarios of global temperature increase of 1°C to 3°C, the vegetation types such as Dry Kobresia Meadow and Dry Potentilla Shrub that are adapted to warm and dry conditions tend to become more dominant in the study area.
文摘The integration of the two fast-developing scientific research areas Semantic Web and Web Mining is known as Semantic Web Mining. The huge increase in the amount of Semantic Web data became a perfect target for many researchers to apply Data Mining techniques on it. This paper gives a detailed state-of-the-art survey of on-going research in this new area. It shows the positive effects of Semantic Web Mining, the obstacles faced by researchers and propose number of approaches to deal with the very complex and heterogeneous information and knowledge which are produced by the technologies of Semantic Web.
文摘Background In the past few years,augmented reality(AR)has rapidly advanced and has been applied in different fields.One of the successful AR applications is the immersive and interactive serious games,which can be used for education and learning purposes.Methods In this project,a prototype of an AR serious game is developed and demonstrated.Gamers utilize a head-mounted device and a vibrotactile feedback jacket to explore and interact with the AR serious game.Fourteen vibration actuators are embedded in the vibrotactile feedback jacket to generate immersive AR experience.These vibration actuators are triggered in accordance with the designed game scripts.Various vibration patterns and intensity levels are synthesized in different game scenes.This article presents the details of the entire software development of the AR serious game,including game scripts,game scenes with AR effects design,signal processing flow,behavior design,and communication configuration.Graphics computations are processed using the graphics processing unit in the system.Results/Conclusions The performance of the AR serious game prototype is evaluated and analyzed.The computation loads and resource utilization of normal game scenes and heavy computation scenes are compared.With 14 vibration actuators placed at different body positions,various vibration patterns and intensity levels can be generated by the vibrotactile feedback jacket,providing different real-world feedback.The prototype of this AR serious game can be valuable in building large-scale AR or virtual reality educational and entertainment games.Possible future improvements of the proposed prototype are also discussed in this article.
基金the National Natural Science Foundation of China(Nos.61502206 and 61472343)the Natural Science Foundation of Jiangsu Province(Nos.BK20160543 and BK20150523)the Open Project of Key Laboratory of Jiangsu Province(No.BM20082061507)
文摘Smart environment is being used in many areas to deliver more services to individuals in a physical space, such as a hospital. In the UK, the National Health Service(NHS) provides free and high quality healthcare service for all residents. Smart hospital environment is able to support NHS and provide more convenience. Patient flow scheduling is a crucial section in a smart hospital environment. Smart hospital environment aims to provide a smart environment in the hospital to facilitate individual experience and improve the quality of healthcare service.First of all, this paper investigates a real world patient flow scenario of a hospital in the UK and models a general scheduling scheme based on the scenario using a compositional formal approach, i.e. performance evaluation process algebra(PEPA). This scheduling scheme uses an easy-implemented solution(the grouping scheme) to reduce the waiting queue in the hospital. Secondly, fluid flow analysis is used for the performance analysis by generating a set of ordinary differential equations(ODEs) in terms of the PEPA model.
文摘Cloud computing is a novel computing paradigm that utilizes remote cloud resources to achieve a high-performance computation.Cloud provides infrastructure,platform and software as different on-demand services.China has made remarkable progress in cloudbased products and operating system technology.The government,enterprises and research institutions are all active in the development of cloud computing-related projects.Despite the progress,many important
文摘This paper considers the geometric design of crab-like walkers and climbers, without decoupling leg design from overall machine design. Crab-like machines represent an important sub-class of multi-legged robots, being particularly well suited to crossing difficult terrains. Firstly, the kinematic configurations and constraints are described, which determine the machine’s kinematic characteristics. The influence of the design parameters on the kinematic workspace is discussed. Finally, a two stage design methodology is presented, comprising kinematic design and design optimisation, the latter being based on the use of design maps rather than numerical optimisation. The performance measures considered during design optimisation include kinematic, static and quasi-static measures.
文摘In the present scenario of rapid growth in cloud computing models,several companies and users started to share their data on cloud servers.However,when the model is not completely trusted,the data owners face several security-related problems,such as user privacy breaches,data disclosure,data corruption,and so on,during the process of data outsourcing.For addressing and handling the security-related issues on Cloud,several models were proposed.With that concern,this paper develops a Privacy-Preserved Data Security Approach(PP-DSA)to provide the data security and data integrity for the out-sourcing data in Cloud Environment.Privacy preservation is ensured in this work with the Efficient Authentication Technique(EAT)using the Group Signature method that is applied with Third-Party Auditor(TPA).The role of the auditor is to secure the data and guarantee shared data integrity.Additionally,the Cloud Service Provider(CSP)and Data User(DU)can also be the attackers that are to be handled with the EAT.Here,the major objective of the work is to enhance cloud security and thereby,increase Quality of Service(QoS).The results are evaluated based on the model effectiveness,security,and reliability and show that the proposed model provides better results than existing works.
基金Project supported by the National Natural Science Foundation of China(Grant No.11547196)the Key Projects of Sichuan Provincial Department of Education,China(Grant No.15ZA0224)+1 种基金the Project of Sichuan Provincial Key Laboratory of Artificial Intelligence,China(Grant No.2014RYJ01)the Key Plan Projects of Science and Technology of Zigong,China(Grant No.2016CXM05)
文摘A metamaterial absorber is computed numerically and measured experimentally in a 150-THz^300-THz range.The measured absorber achieves high absorption rate for both transverse electric（TE） and transverse magnetic（TM） polarizations at large angles of incidence.An absorption sensor scheme is proposed based on the measured absorber and the variations of surrounding media.Different surrounding media are applied to the surface of the absorption sensor（including air,water,and glucose solution）.Measured results show that high figure of merit（FOM） values are obtained for different surrounding media.The proposed sensor does not depend on the substrate,which means that it can be transplanted to different sensing platforms conveniently.
