This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air qua...This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM<sub>10</sub>) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM<sub>10</sub> released from the cement silos into the air. Simulations were carried out for PM<sub>10</sub> emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM<sub>10</sub> emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m<sup>3</sup>, and the highest daily emission value is 0.6 μg/m<sup>3</sup>;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m<sup>3</sup>. The highest daily emission average value was 1250.09 μg/m<sup>3</sup>;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM<sub>10</sub> pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.展开更多
This research study quantifies the PM<sub>10</sub> emission rates (g/s) from cement silos in 25 concrete batching facilities for both controlled and uncontrolled scenarios by applying the USEPA AP-42 guide...This research study quantifies the PM<sub>10</sub> emission rates (g/s) from cement silos in 25 concrete batching facilities for both controlled and uncontrolled scenarios by applying the USEPA AP-42 guidelines step-by-step approach. The study focuses on evaluating the potential environmental impact of cement dust fugitive emissions from 176 cement silos located in 25 concrete batching facilities in the M35 Mussafah industrial area of Abu Dhabi, UAE. Emission factors are crucial for quantifying the PM<sub>10</sub> emission rates (g/s) that support developing source-specific emission estimates for areawide inventories to identify major sources of pollution that provide screening sources for compliance monitoring and air dispersion modeling. This requires data to be collected involves information on production, raw material usage, energy consumption, and process-related details, this was obtained using various methods, including field visits, surveys, and interviews with facility representatives to calculate emission rates accurately. Statistical analysis was conducted on cement consumption and emission rates for controlled and uncontrolled sources of the targeted facilities. The data shows that the average cement consumption among the facilities is approximately 88,160 (MT/yr), with a wide range of variation depending on the facility size and production rate. The emission rates from controlled sources have an average of 4.752E<sup>-04</sup> (g/s), while the rates from uncontrolled sources average 0.6716 (g/s). The analysis shows a significant statistical relationship (p < 0.05) and perfect positive correlation (r = 1) between cement consumption and emission rates, indicating that as cement consumption increases, emission rates tend to increase as well. Furthermore, comparing the emission rates from controlled and uncontrolled scenarios. The data showed a significant difference between the two scenarios, highlighting the effectiveness of control measures in reducing PM<sub>10</sub> emissions. The study’s findings provide insights into the impact of cement silo emissions on air quality and the importance of implementing control measures in concrete batching facilities. The comparative analysis contributes to understanding emission sources and supports the development of pollution control strategies in the Ready-Mix industry.展开更多
To improve the productivity,the resource utilization and reduce the production cost of flexible job shops,this paper designs an improved two-layer optimization algorithm for the dual-resource scheduling optimization p...To improve the productivity,the resource utilization and reduce the production cost of flexible job shops,this paper designs an improved two-layer optimization algorithm for the dual-resource scheduling optimization problem of flexible job shop considering workpiece batching.Firstly,a mathematical model is established to minimize the maximum completion time.Secondly,an improved two-layer optimization algorithm is designed:the outer layer algorithm uses an improved PSO(Particle Swarm Optimization)to solve the workpiece batching problem,and the inner layer algorithm uses an improved GA(Genetic Algorithm)to solve the dual-resource scheduling problem.Then,a rescheduling method is designed to solve the task disturbance problem,represented by machine failures,occurring in the workshop production process.Finally,the superiority and effectiveness of the improved two-layer optimization algorithm are verified by two typical cases.The case results show that the improved two-layer optimization algorithm increases the average productivity by 7.44% compared to the ordinary two-layer optimization algorithm.By setting the different numbers of AGVs(Automated Guided Vehicles)and analyzing the impact on the production cycle of the whole order,this paper uses two indicators,the maximum completion time decreasing rate and the average AGV load time,to obtain the optimal number of AGVs,which saves the cost of production while ensuring the production efficiency.This research combines the solved problem with the real production process,which improves the productivity and reduces the production cost of the flexible job shop,and provides new ideas for the subsequent research.展开更多
Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster,where the resources can be pooled in order to maximize data center resource utilization.Due to resource competi...Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster,where the resources can be pooled in order to maximize data center resource utilization.Due to resource competition between batch jobs and online services,co-location frequently impairs the performance of online services.This study presents a quality of service(QoS)prediction-based schedulingmodel(QPSM)for co-locatedworkloads.The performance prediction of QPSM consists of two parts:the prediction of an online service’s QoS anomaly based on XGBoost and the prediction of the completion time of an offline batch job based on randomforest.On-line service QoS anomaly prediction is used to evaluate the influence of batch jobmix on on-line service performance,and batch job completion time prediction is utilized to reduce the total waiting time of batch jobs.When the same number of batch jobs are scheduled in experiments using typical test sets such as CloudSuite,the scheduling time required by QPSM is reduced by about 6 h on average compared with the first-come,first-served strategy and by about 11 h compared with the random scheduling strategy.Compared with the non-co-located situation,QPSM can improve CPU resource utilization by 12.15% and memory resource utilization by 5.7% on average.Experiments show that the QPSM scheduling strategy proposed in this study can effectively guarantee the quality of online services and further improve cluster resource utilization.展开更多
For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and all...For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.展开更多
The lethal brain tumor “Glioblastoma” has the propensity to grow over time. To improve patient outcomes, it is essential to classify GBM accurately and promptly in order to provide a focused and individualized treat...The lethal brain tumor “Glioblastoma” has the propensity to grow over time. To improve patient outcomes, it is essential to classify GBM accurately and promptly in order to provide a focused and individualized treatment plan. Despite this, deep learning methods, particularly Convolutional Neural Networks (CNNs), have demonstrated a high level of accuracy in a myriad of medical image analysis applications as a result of recent technical breakthroughs. The overall aim of the research is to investigate how CNNs can be used to classify GBMs using data from medical imaging, to improve prognosis precision and effectiveness. This research study will demonstrate a suggested methodology that makes use of the CNN architecture and is trained using a database of MRI pictures with this tumor. The constructed model will be assessed based on its overall performance. Extensive experiments and comparisons with conventional machine learning techniques and existing classification methods will also be made. It will be crucial to emphasize the possibility of early and accurate prediction in a clinical workflow because it can have a big impact on treatment planning and patient outcomes. The paramount objective is to not only address the classification challenge but also to outline a clear pathway towards enhancing prognosis precision and treatment effectiveness.展开更多
China was set to lift another batch of three taikonauts aboard Shenzhou-18 spaceship into the space in the second half of April,to replace the current crew and continue the construction work of the Tiangong space stat...China was set to lift another batch of three taikonauts aboard Shenzhou-18 spaceship into the space in the second half of April,to replace the current crew and continue the construction work of the Tiangong space station.展开更多
Synthetic dyes are substances that are relatively stable and difficult to degrade in wastewater treatment plants using normal physical,chemical or / and biological treatment. The present work explored the synergistic ...Synthetic dyes are substances that are relatively stable and difficult to degrade in wastewater treatment plants using normal physical,chemical or / and biological treatment. The present work explored the synergistic effect of non-thermal plasma( NTP) and biological wastewater treatment technologies on practical dye wastewater degradation by establishing a double dielectric barrier discharge( DDBD) system combined with a sequencing batch reactor( SBR) system. The biodegradation and degradation efficiency of the DDBD-SBR system was investigated. The investigation results indicated that the DDBD technology was effective in treating the practical dye wastewater as a pre-treatment process. After a 10-min treatment,although the total organic carbon( TOC) removal efficiency was not so significant, the decolouration and the biodegradation were improved greatly. The microbial toxicity test revealed that the sample after degradation became less toxic than the original dye,which demonstrated the treatment had a significant effect on the reduction of toxicity. In addition,the SBR technology remedied the defects of DDBD treatment and improved TOC removal efficiency noticeably. The hybrid DDBD-SBR system made full use of the advantages of the individual technologies and exhibited an efficient capability for practical dye wastewater treatment.展开更多
Some bases are presented for determining and calculating the airborne pulse doppler radar's DBS system parameters. Major problems discussed here are the limitation to the beam sharpening ratio and azimuth resoluti...Some bases are presented for determining and calculating the airborne pulse doppler radar's DBS system parameters. Major problems discussed here are the limitation to the beam sharpening ratio and azimuth resolution, and the limitation to maximum pitch an展开更多
The scheduling problem on a single batching machine with family jobs was proposed.The single batching machine can process a group of jobs simultaneously as a batch.Jobs in the same batch complete at the same time.The ...The scheduling problem on a single batching machine with family jobs was proposed.The single batching machine can process a group of jobs simultaneously as a batch.Jobs in the same batch complete at the same time.The batch size is assumed to be unbounded.Jobs that belong to different families can not be processed in the same batch.The objective function is minimizing maximum lateness.For the problem with fixed number of m families and n jobs,a polynomial time algorithm based on dynamic programming with time complexity of O(n(n/m+1)m)was presented.展开更多
Under the condition of the market competition becom in g more and more drastic, the demands of market take on some new features such as individuation, diversification, small batch, unstableness and quick delivery et c...Under the condition of the market competition becom in g more and more drastic, the demands of market take on some new features such as individuation, diversification, small batch, unstableness and quick delivery et c. The Make-to-Stock mode is usually adopted by many enterprises to improve th e balance and stableness of production process. In such enterprises, order batch , production batch and sales batch are the important factors, which affect the s atisfaction of clients, efficiency and benefit of the enterprise. It takes purch ase, production and sales into account respectively when optimizing product batc h in traditional way. However, it ignored the influences of relations between ea ch links of whole system. It is assumed that the consumption and market demand a re continuous process whereas the factual demands are batched when economic batc h is determined. So there exist some deviations between the economic batch deter mined by traditional way and that by integral optimization. Through the integral analysis of Logistics in the production system, we know that from materials are purchased, then manufactured, finally sold, the material changed in appearance and value, it still exist in different links of production system. The amount of materials occupied varies just in different status, from stock status to produc tion status, then to waiting-be-sold status, there is not any substantial chan ge in quantity until they are sold. So we must comprehensively analyze the relat ions among each link based on integral production system, to optimize the materi al batch and cut short production cycle in order to optimize the whole system. In this paper, the production system is taken as a global entity, and in which m aterials variation law and their relations of each link are analyzed; To optimiz e the whole materials flow, a new model of multi-product systems’ economic orde r batch, economic production batch and optimal sale lot multi-product syste ms’ is developed which based on the limit of capitals and stock area.展开更多
Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation compr...Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation comprises a concomitant consideration of the stage-wise separation andthe equations of material balance as well as enthalpy balance.Based upon the batch distillationpractice of NMP-water system,this paper reveals the necessity and advantage of a computerizedtreatment for this purpose.Numerical results not only explain the experimental phenomena andprovide a design scheme,but also lead to the optimization of the operation condition.展开更多
Thanks to its light weight,low power consumption,and low price,the inertial measurement units(IMUs)have been widely used in civil and military applications such as autopilot,robotics,and tactical weapons.The calibrati...Thanks to its light weight,low power consumption,and low price,the inertial measurement units(IMUs)have been widely used in civil and military applications such as autopilot,robotics,and tactical weapons.The calibration is an essential procedure before the IMU is put in use,which is generally used to estimate the error parameters such as the bias,installation error,scale factor of the IMU.Currently,the manual one-by-one calibration is still the mostly used manner,which is low in efficiency,time-consuming,and easy to introduce mis-operation.Aiming at this issue,this paper designs an automatic batch calibration method for a set of IMUs.The designed automatic calibration master controller can control the turntable and the data acquisition system at the same time.Each data acquisition front-end can complete data acquisition of eight IMUs one time.And various scenarios of experimental tests have been carried out to validate the proposed design,such as the multi-position tests,the rate tests and swaying tests.The results illustrate the reliability of each function module and the feasibility automatic batch calibration.Compared with the traditional calibration method,the proposed design can reduce errors caused by the manual calibration and greatly improve the efficiency of IMU calibration.展开更多
In parallel-batching machine scheduling, all jobs in a batch start and complete at the same time, and the processing time of the batch is the maximum processing time of any job in it. For the unbounded parallel-batchi...In parallel-batching machine scheduling, all jobs in a batch start and complete at the same time, and the processing time of the batch is the maximum processing time of any job in it. For the unbounded parallel-batching machine scheduling problem of minimizing the maximum lateness, denoted 1|p-batch|L_(max), a dynamic programming algorithm with time complexity O(n^2) is well known in the literature.Later, this algorithm is improved to be an O(n log n) algorithm. In this note, we present another O(n log n) algorithm with simplifications on data structure and implementation details.展开更多
This paper lies in the field of digital signal processing.This is a speech recognition system that identifies the different speakers based on deep learning.The invention consists of the following steps:Firstly,we coll...This paper lies in the field of digital signal processing.This is a speech recognition system that identifies the different speakers based on deep learning.The invention consists of the following steps:Firstly,we collect the voice data from different people.Secondly,the data having been selected is preprocessed by extracting their Mel Frequency Cepstral Coefficients(MFCC)and is divided into training set and test set randomly.Thirdly,we cut the training set into batches,and put them into the convolutional neural network which consists of convolutional layers,max pooling layers and fully connected layers.After repeatedly adjusting the parameters of the network such as learning rate,dropout rate and decay rate,the model will reach the optimal performance.Finally,the testing set is also cut into batches and put into the trained neural network.The final recognition accuracy rate is 70.23%.In brief,the research can automatically recognize different speakers efficiently.展开更多
Carbon footprint analysis is a method to quantify the life cycle Greenhouse Gases (GHGs) emissions and identify the measure to reduce climate change impacts. The Intergovernmental Panel on Climate Change (IPCC) has id...Carbon footprint analysis is a method to quantify the life cycle Greenhouse Gases (GHGs) emissions and identify the measure to reduce climate change impacts. The Intergovernmental Panel on Climate Change (IPCC) has identified that the global warming and climate change which is one of the most important issues in the domain of environment are caused by the excessive emission of Greenhouse Gases (GHG) mainly constituting Carbon dioxide (CO2), Methane (CH4) and Nitrous oxide (N2O). The municipal wastewater treatment plant receives wastewater for treatment and finally discharges the treated effluent. The emissions of GHG during the treatment of wastewater as well as during the treatment process of sludge and also for energy generation are known to be on-site GHG emissions. Off-site GHG emissions are generated due to transportation and disposal of sludge, off-site energy and chemical production. In Puducherry, the municipal wastewater is being treated using oxidation ponds, Upflow Anaerobic Sludge Blanket (UASB) and Sequencing Batch Reactor (SBR). Wastewater treatment using Sequencing Batch Reactor (SBR) technology is one of the state-of-the art wastewater management systems. In this technology equalization, biological treatment and secondary clarification are performed in a single reactor in a time control sequence. The emissions of GHG from the Oxidation ponds of 12.5 MLD, UASB reactor of 2.5 MLD and SBR of 17 MLD were assessed based on the IPCC guidelines and the total emissions of GHG in terms of equivalent of CO2 were compared. The performance of the SBR is more efficient and the emissions of GHG are less than the emissions in the UASB as well as in oxidation ponds. The emission of GHG in SBR is about 60% of the existing treatment systems of oxidation ponds and UASB thus a reduction of 40% GHG emission could be achieved.展开更多
Mesenchymal stromal cells(MSCs),known for their therapeutic bioactivity,find widespread application as cellular drugs for treating various diseases.MSCs obtained from patients or donors require extensive large-scale e...Mesenchymal stromal cells(MSCs),known for their therapeutic bioactivity,find widespread application as cellular drugs for treating various diseases.MSCs obtained from patients or donors require extensive large-scale expansion for clinical applications.However,the conventional method of cultivating MSCs involves several manual processes and yields inconsistent batch-to-batch quality.Consequently,it has not been scalable as a cell therapy[1].To overcome the limitations of conventional planar cell culture,van Wezel initially proposed a system for culturing cells in suspension using microcarriers and successfully proliferated rabbit embryonic skin cells and human embryonic lung cells[2].Subsequently,microcarrier technology has been employed across various pharmaceutical applications,leading to the development and commercialization of a diverse array of microcarriers with distinct physicochemical properties.展开更多
The unmanned aerial vehicle(UAV)self-organizing network is composed of multiple UAVs with autonomous capabilities according to a certain structure and scale,which can quickly and accurately complete complex tasks such...The unmanned aerial vehicle(UAV)self-organizing network is composed of multiple UAVs with autonomous capabilities according to a certain structure and scale,which can quickly and accurately complete complex tasks such as path planning,situational awareness,and information transmission.Due to the openness of the network,the UAV cluster is more vulnerable to passive eavesdropping,active interference,and other attacks,which makes the system face serious security threats.This paper proposes a Blockchain-Based Data Acquisition(BDA)scheme with privacy protection to address the data privacy and identity authentication problems in the UAV-assisted data acquisition scenario.Each UAV cluster has an aggregate unmanned aerial vehicle(AGV)that can batch-verify the acquisition reports within its administrative domain.After successful verification,AGV adds its signcrypted ciphertext to the aggregation and uploads it to the blockchain for storage.There are two chains in the blockchain that store the public key information of registered entities and the aggregated reports,respectively.The security analysis shows that theBDAconstruction can protect the privacy and authenticity of acquisition data,and effectively resist a malicious key generation center and the public-key substitution attack.It also provides unforgeability to acquisition reports under the Elliptic Curve Discrete Logarithm Problem(ECDLP)assumption.The performance analysis demonstrates that compared with other schemes,the proposed BDA construction has lower computational complexity and is more suitable for the UAV cluster network with limited computing power and storage capacity.展开更多
文摘This research assessed the environmental impact of cement silos emission on the existing concrete batching facilities in M35-Mussafah, Abu Dhabi, United Arab Emirates. These assessments were conducted using an air quality dispersion model (AERMOD) to predict the ambient concentration of Portland Cement particulate matter less than 10 microns (PM<sub>10</sub>) emitted to the atmosphere during loading and unloading activities from 176 silos located in 25 concrete batching facilities. AERMOD was applied to simulate and describe the dispersion of PM<sub>10</sub> released from the cement silos into the air. Simulations were carried out for PM<sub>10</sub> emissions on controlled and uncontrolled cement silos scenarios. Results showed an incremental negative impact on air quality and public health from uncontrolled silos emissions and estimated that the uncontrolled PM<sub>10</sub> emission sources contribute to air pollution by 528958.32 kg/Year. The modeling comparison between the controlled and uncontrolled silos shows that the highest annual average concentration from controlled cement silos is 0.065 μg/m<sup>3</sup>, and the highest daily emission value is 0.6 μg/m<sup>3</sup>;both values are negligible and will not lead to significant air quality impact in the entire study domain. However, the uncontrolled cement silos’ highest annual average concentration value is 328.08 μg/m<sup>3</sup>. The highest daily emission average value was 1250.09 μg/m<sup>3</sup>;this might cause a significant air pollution quality impact and health effects on the public and workers. The short-term and long-term average PM<sub>10</sub> pollutant concentrations at these receptors predicted by the air dispersion model are discussed for both scenarios and compared with local and international air quality standards and guidelines.
文摘This research study quantifies the PM<sub>10</sub> emission rates (g/s) from cement silos in 25 concrete batching facilities for both controlled and uncontrolled scenarios by applying the USEPA AP-42 guidelines step-by-step approach. The study focuses on evaluating the potential environmental impact of cement dust fugitive emissions from 176 cement silos located in 25 concrete batching facilities in the M35 Mussafah industrial area of Abu Dhabi, UAE. Emission factors are crucial for quantifying the PM<sub>10</sub> emission rates (g/s) that support developing source-specific emission estimates for areawide inventories to identify major sources of pollution that provide screening sources for compliance monitoring and air dispersion modeling. This requires data to be collected involves information on production, raw material usage, energy consumption, and process-related details, this was obtained using various methods, including field visits, surveys, and interviews with facility representatives to calculate emission rates accurately. Statistical analysis was conducted on cement consumption and emission rates for controlled and uncontrolled sources of the targeted facilities. The data shows that the average cement consumption among the facilities is approximately 88,160 (MT/yr), with a wide range of variation depending on the facility size and production rate. The emission rates from controlled sources have an average of 4.752E<sup>-04</sup> (g/s), while the rates from uncontrolled sources average 0.6716 (g/s). The analysis shows a significant statistical relationship (p < 0.05) and perfect positive correlation (r = 1) between cement consumption and emission rates, indicating that as cement consumption increases, emission rates tend to increase as well. Furthermore, comparing the emission rates from controlled and uncontrolled scenarios. The data showed a significant difference between the two scenarios, highlighting the effectiveness of control measures in reducing PM<sub>10</sub> emissions. The study’s findings provide insights into the impact of cement silo emissions on air quality and the importance of implementing control measures in concrete batching facilities. The comparative analysis contributes to understanding emission sources and supports the development of pollution control strategies in the Ready-Mix industry.
文摘To improve the productivity,the resource utilization and reduce the production cost of flexible job shops,this paper designs an improved two-layer optimization algorithm for the dual-resource scheduling optimization problem of flexible job shop considering workpiece batching.Firstly,a mathematical model is established to minimize the maximum completion time.Secondly,an improved two-layer optimization algorithm is designed:the outer layer algorithm uses an improved PSO(Particle Swarm Optimization)to solve the workpiece batching problem,and the inner layer algorithm uses an improved GA(Genetic Algorithm)to solve the dual-resource scheduling problem.Then,a rescheduling method is designed to solve the task disturbance problem,represented by machine failures,occurring in the workshop production process.Finally,the superiority and effectiveness of the improved two-layer optimization algorithm are verified by two typical cases.The case results show that the improved two-layer optimization algorithm increases the average productivity by 7.44% compared to the ordinary two-layer optimization algorithm.By setting the different numbers of AGVs(Automated Guided Vehicles)and analyzing the impact on the production cycle of the whole order,this paper uses two indicators,the maximum completion time decreasing rate and the average AGV load time,to obtain the optimal number of AGVs,which saves the cost of production while ensuring the production efficiency.This research combines the solved problem with the real production process,which improves the productivity and reduces the production cost of the flexible job shop,and provides new ideas for the subsequent research.
基金supported by the NationalNatural Science Foundation of China(No.61972118)the Key R&D Program of Zhejiang Province(No.2023C01028).
文摘Cloud service providers generally co-locate online services and batch jobs onto the same computer cluster,where the resources can be pooled in order to maximize data center resource utilization.Due to resource competition between batch jobs and online services,co-location frequently impairs the performance of online services.This study presents a quality of service(QoS)prediction-based schedulingmodel(QPSM)for co-locatedworkloads.The performance prediction of QPSM consists of two parts:the prediction of an online service’s QoS anomaly based on XGBoost and the prediction of the completion time of an offline batch job based on randomforest.On-line service QoS anomaly prediction is used to evaluate the influence of batch jobmix on on-line service performance,and batch job completion time prediction is utilized to reduce the total waiting time of batch jobs.When the same number of batch jobs are scheduled in experiments using typical test sets such as CloudSuite,the scheduling time required by QPSM is reduced by about 6 h on average compared with the first-come,first-served strategy and by about 11 h compared with the random scheduling strategy.Compared with the non-co-located situation,QPSM can improve CPU resource utilization by 12.15% and memory resource utilization by 5.7% on average.Experiments show that the QPSM scheduling strategy proposed in this study can effectively guarantee the quality of online services and further improve cluster resource utilization.
基金partially supported by the National Natural Science Foundation of China under grant no.62372245the Foundation of Yunnan Key Laboratory of Blockchain Application Technology under Grant 202105AG070005+1 种基金in part by the Foundation of State Key Laboratory of Public Big Datain part by the Foundation of Key Laboratory of Computational Science and Application of Hainan Province under Grant JSKX202202。
文摘For the goals of security and privacy preservation,we propose a blind batch encryption-and public ledger-based data sharing protocol that allows the integrity of sensitive data to be audited by a public ledger and allows privacy information to be preserved.Data owners can tightly manage their data with efficient revocation and only grant one-time adaptive access for the fulfillment of the requester.We prove that our protocol is semanticallly secure,blind,and secure against oblivious requesters and malicious file keepers.We also provide security analysis in the context of four typical attacks.
文摘The lethal brain tumor “Glioblastoma” has the propensity to grow over time. To improve patient outcomes, it is essential to classify GBM accurately and promptly in order to provide a focused and individualized treatment plan. Despite this, deep learning methods, particularly Convolutional Neural Networks (CNNs), have demonstrated a high level of accuracy in a myriad of medical image analysis applications as a result of recent technical breakthroughs. The overall aim of the research is to investigate how CNNs can be used to classify GBMs using data from medical imaging, to improve prognosis precision and effectiveness. This research study will demonstrate a suggested methodology that makes use of the CNN architecture and is trained using a database of MRI pictures with this tumor. The constructed model will be assessed based on its overall performance. Extensive experiments and comparisons with conventional machine learning techniques and existing classification methods will also be made. It will be crucial to emphasize the possibility of early and accurate prediction in a clinical workflow because it can have a big impact on treatment planning and patient outcomes. The paramount objective is to not only address the classification challenge but also to outline a clear pathway towards enhancing prognosis precision and treatment effectiveness.
文摘China was set to lift another batch of three taikonauts aboard Shenzhou-18 spaceship into the space in the second half of April,to replace the current crew and continue the construction work of the Tiangong space station.
基金Key Basic Research of Shanghai Science and Technology Committee,China(No.11JC1400100)National Natural Science Foundations of China(Nos.51108070,51178093)+2 种基金Shanghai Pujiang Programmethe Program for New Century Excellent Talents in University,China(No.NCET-12-0826)Fundamental Research Funds for Central Universities,China
文摘Synthetic dyes are substances that are relatively stable and difficult to degrade in wastewater treatment plants using normal physical,chemical or / and biological treatment. The present work explored the synergistic effect of non-thermal plasma( NTP) and biological wastewater treatment technologies on practical dye wastewater degradation by establishing a double dielectric barrier discharge( DDBD) system combined with a sequencing batch reactor( SBR) system. The biodegradation and degradation efficiency of the DDBD-SBR system was investigated. The investigation results indicated that the DDBD technology was effective in treating the practical dye wastewater as a pre-treatment process. After a 10-min treatment,although the total organic carbon( TOC) removal efficiency was not so significant, the decolouration and the biodegradation were improved greatly. The microbial toxicity test revealed that the sample after degradation became less toxic than the original dye,which demonstrated the treatment had a significant effect on the reduction of toxicity. In addition,the SBR technology remedied the defects of DDBD treatment and improved TOC removal efficiency noticeably. The hybrid DDBD-SBR system made full use of the advantages of the individual technologies and exhibited an efficient capability for practical dye wastewater treatment.
文摘Some bases are presented for determining and calculating the airborne pulse doppler radar's DBS system parameters. Major problems discussed here are the limitation to the beam sharpening ratio and azimuth resolution, and the limitation to maximum pitch an
基金National Natural Science Foundation of China(No.70832002)Graduate Student Innovation Fund of Fudan University,China
文摘The scheduling problem on a single batching machine with family jobs was proposed.The single batching machine can process a group of jobs simultaneously as a batch.Jobs in the same batch complete at the same time.The batch size is assumed to be unbounded.Jobs that belong to different families can not be processed in the same batch.The objective function is minimizing maximum lateness.For the problem with fixed number of m families and n jobs,a polynomial time algorithm based on dynamic programming with time complexity of O(n(n/m+1)m)was presented.
文摘Under the condition of the market competition becom in g more and more drastic, the demands of market take on some new features such as individuation, diversification, small batch, unstableness and quick delivery et c. The Make-to-Stock mode is usually adopted by many enterprises to improve th e balance and stableness of production process. In such enterprises, order batch , production batch and sales batch are the important factors, which affect the s atisfaction of clients, efficiency and benefit of the enterprise. It takes purch ase, production and sales into account respectively when optimizing product batc h in traditional way. However, it ignored the influences of relations between ea ch links of whole system. It is assumed that the consumption and market demand a re continuous process whereas the factual demands are batched when economic batc h is determined. So there exist some deviations between the economic batch deter mined by traditional way and that by integral optimization. Through the integral analysis of Logistics in the production system, we know that from materials are purchased, then manufactured, finally sold, the material changed in appearance and value, it still exist in different links of production system. The amount of materials occupied varies just in different status, from stock status to produc tion status, then to waiting-be-sold status, there is not any substantial chan ge in quantity until they are sold. So we must comprehensively analyze the relat ions among each link based on integral production system, to optimize the materi al batch and cut short production cycle in order to optimize the whole system. In this paper, the production system is taken as a global entity, and in which m aterials variation law and their relations of each link are analyzed; To optimiz e the whole materials flow, a new model of multi-product systems’ economic orde r batch, economic production batch and optimal sale lot multi-product syste ms’ is developed which based on the limit of capitals and stock area.
文摘Batch distillation,basically different from continuous distillation which is a steady stateprocess,appears to be an unsteady state process in its mathematical description.The theoreticalanalysis of its operation comprises a concomitant consideration of the stage-wise separation andthe equations of material balance as well as enthalpy balance.Based upon the batch distillationpractice of NMP-water system,this paper reveals the necessity and advantage of a computerizedtreatment for this purpose.Numerical results not only explain the experimental phenomena andprovide a design scheme,but also lead to the optimization of the operation condition.
基金This work was supported by the National Natural Science Foundation of China(No.61803203).
文摘Thanks to its light weight,low power consumption,and low price,the inertial measurement units(IMUs)have been widely used in civil and military applications such as autopilot,robotics,and tactical weapons.The calibration is an essential procedure before the IMU is put in use,which is generally used to estimate the error parameters such as the bias,installation error,scale factor of the IMU.Currently,the manual one-by-one calibration is still the mostly used manner,which is low in efficiency,time-consuming,and easy to introduce mis-operation.Aiming at this issue,this paper designs an automatic batch calibration method for a set of IMUs.The designed automatic calibration master controller can control the turntable and the data acquisition system at the same time.Each data acquisition front-end can complete data acquisition of eight IMUs one time.And various scenarios of experimental tests have been carried out to validate the proposed design,such as the multi-position tests,the rate tests and swaying tests.The results illustrate the reliability of each function module and the feasibility automatic batch calibration.Compared with the traditional calibration method,the proposed design can reduce errors caused by the manual calibration and greatly improve the efficiency of IMU calibration.
基金Supported by NSFC(11571323 11201121)+1 种基金NSFSTDOHN(162300410221)NSFEDOHN(2013GGJS-079)
文摘In parallel-batching machine scheduling, all jobs in a batch start and complete at the same time, and the processing time of the batch is the maximum processing time of any job in it. For the unbounded parallel-batching machine scheduling problem of minimizing the maximum lateness, denoted 1|p-batch|L_(max), a dynamic programming algorithm with time complexity O(n^2) is well known in the literature.Later, this algorithm is improved to be an O(n log n) algorithm. In this note, we present another O(n log n) algorithm with simplifications on data structure and implementation details.
文摘This paper lies in the field of digital signal processing.This is a speech recognition system that identifies the different speakers based on deep learning.The invention consists of the following steps:Firstly,we collect the voice data from different people.Secondly,the data having been selected is preprocessed by extracting their Mel Frequency Cepstral Coefficients(MFCC)and is divided into training set and test set randomly.Thirdly,we cut the training set into batches,and put them into the convolutional neural network which consists of convolutional layers,max pooling layers and fully connected layers.After repeatedly adjusting the parameters of the network such as learning rate,dropout rate and decay rate,the model will reach the optimal performance.Finally,the testing set is also cut into batches and put into the trained neural network.The final recognition accuracy rate is 70.23%.In brief,the research can automatically recognize different speakers efficiently.
文摘Carbon footprint analysis is a method to quantify the life cycle Greenhouse Gases (GHGs) emissions and identify the measure to reduce climate change impacts. The Intergovernmental Panel on Climate Change (IPCC) has identified that the global warming and climate change which is one of the most important issues in the domain of environment are caused by the excessive emission of Greenhouse Gases (GHG) mainly constituting Carbon dioxide (CO2), Methane (CH4) and Nitrous oxide (N2O). The municipal wastewater treatment plant receives wastewater for treatment and finally discharges the treated effluent. The emissions of GHG during the treatment of wastewater as well as during the treatment process of sludge and also for energy generation are known to be on-site GHG emissions. Off-site GHG emissions are generated due to transportation and disposal of sludge, off-site energy and chemical production. In Puducherry, the municipal wastewater is being treated using oxidation ponds, Upflow Anaerobic Sludge Blanket (UASB) and Sequencing Batch Reactor (SBR). Wastewater treatment using Sequencing Batch Reactor (SBR) technology is one of the state-of-the art wastewater management systems. In this technology equalization, biological treatment and secondary clarification are performed in a single reactor in a time control sequence. The emissions of GHG from the Oxidation ponds of 12.5 MLD, UASB reactor of 2.5 MLD and SBR of 17 MLD were assessed based on the IPCC guidelines and the total emissions of GHG in terms of equivalent of CO2 were compared. The performance of the SBR is more efficient and the emissions of GHG are less than the emissions in the UASB as well as in oxidation ponds. The emission of GHG in SBR is about 60% of the existing treatment systems of oxidation ponds and UASB thus a reduction of 40% GHG emission could be achieved.
文摘Mesenchymal stromal cells(MSCs),known for their therapeutic bioactivity,find widespread application as cellular drugs for treating various diseases.MSCs obtained from patients or donors require extensive large-scale expansion for clinical applications.However,the conventional method of cultivating MSCs involves several manual processes and yields inconsistent batch-to-batch quality.Consequently,it has not been scalable as a cell therapy[1].To overcome the limitations of conventional planar cell culture,van Wezel initially proposed a system for culturing cells in suspension using microcarriers and successfully proliferated rabbit embryonic skin cells and human embryonic lung cells[2].Subsequently,microcarrier technology has been employed across various pharmaceutical applications,leading to the development and commercialization of a diverse array of microcarriers with distinct physicochemical properties.
基金supported in part by the National Key R&D Program of China under Project 2020YFB1006004the Guangxi Natural Science Foundation under Grants 2019GXNSFFA245015 and 2019GXNSFGA245004+2 种基金the National Natural Science Foundation of China under Projects 62162017,61862012,61962012,and 62172119the Major Key Project of PCL under Grants PCL2021A09,PCL2021A02 and PCL2022A03the Innovation Project of Guangxi Graduate Education YCSW2021175.
文摘The unmanned aerial vehicle(UAV)self-organizing network is composed of multiple UAVs with autonomous capabilities according to a certain structure and scale,which can quickly and accurately complete complex tasks such as path planning,situational awareness,and information transmission.Due to the openness of the network,the UAV cluster is more vulnerable to passive eavesdropping,active interference,and other attacks,which makes the system face serious security threats.This paper proposes a Blockchain-Based Data Acquisition(BDA)scheme with privacy protection to address the data privacy and identity authentication problems in the UAV-assisted data acquisition scenario.Each UAV cluster has an aggregate unmanned aerial vehicle(AGV)that can batch-verify the acquisition reports within its administrative domain.After successful verification,AGV adds its signcrypted ciphertext to the aggregation and uploads it to the blockchain for storage.There are two chains in the blockchain that store the public key information of registered entities and the aggregated reports,respectively.The security analysis shows that theBDAconstruction can protect the privacy and authenticity of acquisition data,and effectively resist a malicious key generation center and the public-key substitution attack.It also provides unforgeability to acquisition reports under the Elliptic Curve Discrete Logarithm Problem(ECDLP)assumption.The performance analysis demonstrates that compared with other schemes,the proposed BDA construction has lower computational complexity and is more suitable for the UAV cluster network with limited computing power and storage capacity.
