Differential Privacy Preserving Dynamic Data Release Scheme Based on Jensen-Shannon Divergence

Health monitoring data or the data about infectious diseases such as COVID-19 may need to be constantly updated and dynamically released,but they may contain user's sensitive information.Thus,how to preserve the user's privacy before their release is critically important yet challenging.Differential Privacy(DP)is well-known to provide effective privacy protection,and thus the dynamic DP preserving data release was designed to publish a histogram to meet DP guarantee.Unfortunately,this scheme may result in high cumulative errors and lower the data availability.To address this problem,in this paper,we apply Jensen-Shannon(JS)divergence to design the OPTICS(Ordering Points To Identify The Clustering Structure)scheme.It uses JS divergence to measure the difference between the updated data set at the current release time and private data set at the previous release time.By comparing the difference with a threshold,only when the difference is greater than the threshold,can we apply OPTICS to publish DP protected data sets.Our experimental results show that the absolute errors and average relative errors are significantly lower than those existing works.

A Novel Robust Nonlinear Dynamic Data Reconciliation

在一个变量的孤立点将在数据和解(医生) 涂另外的大小的评价。在这篇文章，一个新奇柔韧的方法为非线性的动态数据和解被建议，到在这个方法介绍的医生的结果上减少孤立点的影响在常规最少平方的客观功能的一个惩罚功能矩阵，为正常大小为孤立点和大重量分配小重量。避免数据信息的损失，元素明智的 Mahalanobis 距离被建议作为向量明智的距离上的改进，工作构造惩罚矩阵。测量错误的关联也在这篇文章被考虑。方法由构造惩罚重量矩阵介绍柔韧的统计理论进常规最不方形的评估者并且得到不仅好坚韧性而且简单计算。一个连续搅动的坦克反应堆的模拟，验证建议算法的有效性。

Dynamic data-sharing based user recruitment in mobile crowdsensing

Mobile crowdsensing(MCS) has become an emerging paradigm to solve urban sensing problems by leveraging the ubiquitous sensing capabilities of the crowd. One critical issue in MCS is how to recruit users to fulfill more sensing tasks with budget restriction, while sharing data among tasks can be a credible way to improve the efficiency. The data-sharing based user recruitment problem under budget constraint in a realistic scenario is studied, where multiple tasks require homogeneous data but have various spatio-temporal execution ranges, meanwhile users suffer from uncertain future positions. The problem is formulated in a manner of probability by predicting user mobility, then a dynamic user recruitment algorithm is proposed to solve it. In the algorithm a greedy-adding-and-substitution(GAS) heuristic is repeatedly implemented by updating user mobility prediction in each time slot to gradually achieve the final solution. Extensive simulations are conducted using a real-world taxi trace dataset, and the results demonstrate that the approach can fulfill more tasks than existing methods.

Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

Fetal health care is vital in ensuring the health of pregnant women and the fetus.Regular check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential problems.To know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,etc.Still,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during pregnancy.Several researchers have proposed various methods for classifying the status of fetus growth.Manual processing of CTG data is time-consuming and unreliable.So,automated tools should be used to classify fetal health.This study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal health.Various strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also illustrated.This study easily provides valuable interpretations for healthcare professionals in the decision-making process.

Desired Dynamic Equation for Primary Frequency Modulation Control of Gas Turbines

Gas turbines play core roles in clean energy supply and the construction of comprehensive energy systems.The control performance of primary frequency modulation of gas turbines has a great impact on the frequency control of the power grid.However,there are some control difficulties in the primary frequency modulation control of gas turbines,such as the coupling effect of the fuel control loop and speed control loop,slow tracking speed,and so on.To relieve the abovementioned difficulties,a control strategy based on the desired dynamic equation proportional integral(DDE-PI)is proposed in this paper.Based on the parameter stability region,a parameter tuning procedure is summarized.Simulation is carried out to address the ease of use and simplicity of the proposed tuning method.Finally,DDE-PI is applied to the primary frequency modulation system of an MS6001B heavy-duty gas turbine.The simulation results indicate that the gas turbine with the proposed strategy can obtain the best control performance with a strong ability to deal with system uncertainties.The proposed method shows good engineering application potential.

Response characteristics of gas pressure under simultaneous static and dynamic load:Implication for coal and gas outburst mechanism

Coal and gas outbursts are dynamic disasters in which a large mass of gas and coal suddenly emerges in a mining space within a split second.The interaction between the gas pressure and stress environment is one of the key factors that induce coal and gas outbursts.In this study,first,the coupling relationship between the gas pressure in the coal body ahead of the working face and the dynamic load was investigated using experimental observations,numerical simulations,and mine-site investigations.It was observed that the impact rate of the dynamic load on the gas-bearing coal can significantly change the gas pressure.The faster the impact rate,the speedier the increase in gas pressure.Moreover,the gas pressure rise was faster closer to the impact interface.Subsequently,based on engineering background,we proposed three models of stress and gas pressure distribution in the coal body ahead of the working face:static load,stress disturbance,and dynamic load conditions.Finally,the gas pressure distribution and outburst mechanism were investigated.The high concentration of gas pressure appearing at the coal body ahead of the working face was caused by the dynamic load.The gas pressure first increased gradually to a peak value and then decreased with increasing distance from the working face.The increase in gas pressure plays a major role in outburst initiation by resulting in the ability to more easily reach the critical points needed for outburst initiation.Moreover,the stronger the dynamic load,the greater the outburst initiation risk.The results of this study provide practical guidance for the early warning and prevention of coal and gas outbursts.

Experimental and theoretical study on the dynamic effective stress of loaded gassy coal during gas release

In the process of mining coalbed methane(CBM),an unsteady state often arises due to the rapid extraction,release and pressure relief of CBM.In this case,the effective stress of coal changes dynamically,affecting the stability of the gassy coal seam.In this paper,gas release tests of gassy coal under conventional triaxial compression were performed,and the dynamic effective stress(DES)during gas release was obtained indirectly based on a constitutive equation and deformation of coal.The results show that the maximum increases in DES caused by the release of free gas and adsorbed gas under the stress of 1.1 MPa were 0.811 and 5.418 MPa,respectively,which seriously affected the stress state of the coal.During the gas release,the free gas pressure and the adsorbed gas volume were the parameters that directly affected the DES and showed a positive linear relationship with the DES with an intercept of zero.The DES of the coal sample increased exponentially with time,which was determined by the contents of free and adsorbed gas.Based on the experimental results and theoretical analysis,an effective stress model was obtained for loaded gassy coal during gas release.The results of verification indicated accuracy greater than 99%.

Neutronics analysis of a subcritical blanket system driven by a gas dynamic trap-based fusion neutron source for ^(99)Mo production

Gamma-emitting radionuclide ^(99m)Tc is globally used for the diagnosis of various pathological conditions owing to its ideal single-photon emission computed tomography (SPECT) characteristics.However,the short half-life of ^(99m)Tc (T_(1/2)=6 h)makes it difficult to store or transport.Thus,the production of ^(99m)Tc is tied to its parent radionuclide ^(99)Mo (T_(1/2)=66 h).The major production paths are based on accelerators and research reactors.The reactor process presents the potential for nuclear proliferation owing to its use of highly enriched uranium (HEU).Accelerator-based methods tend to use deuterium–tritium(D–T) neutron sources but are hindered by the high cost of tritium and its challenging operation.In this study,a new ^(99)Mo production design was developed based on a deuterium–deuterium (D–D) gas dynamic trap fusion neutron source (GDT-FNS) and a subcritical blanket system (SBS) assembly with a low-enriched uranium (LEU) solution.GDT-FNS can provide a relatively high-neutron intensity,which is one of the advantages of ^(99)Mo production.We provide a Monte Carlo-based neutronics analysis covering the calculation of the subcritical multiplication factor (k_(s)) of the SBS,optimization design for the reflector,shielding layer,and ^(99)Mo production capacity.Other calculations,including the neutron flux and nuclear heating distributions,are also provided for an overall evaluation of the production system.The results demonstrated that the SBS meets the nuclear critical safety design requirement (k_(s)<0.97) and maintained a high ^(99)Mo production capacity.The proposed system can generate approximately 157 Ci ^(99)Mo for a stable 24 h operation with a neutron intensity of 1×10^(14) n/s,which can meet 50%of China’s demand in 2025.

A dynamic evaluation technique for assessing gas output from coal seams during commingling production within a coalbed methane well: a case study from the Qinshui Basin

Gas drainage is carried out based on output from each coal bed throughout commingling production of coalbed methane(CBM).A reasonable drainage process should therefore initially guarantee main coal bed production and then enhance gas output from other beds.Permanent damage can result if this is not the case,especially with regard to fracture development in the main gas-producing coal bed and can greatly reduce single well output.Current theoretical models and measuring devices are inapplicable to commingled CBM drainage,however,and so large errors in predictive models cannot always be avoided.The most effective currently available method involves directly measuring gas output from each coal bed as well as determining the dominant gas-producing unit.A dynamic evaluation technique for gas output from each coal bed during commingling CBM production is therefore proposed in this study.This technique comprises a downhole measurement system combined with a theoretical calculation model.Gas output parameters(i.e.,gas-phase flow rate,temperature,pressure)are measured in this approach via a downhole measurement system;substituting these parameters into a deduced theoretical calculation model then means that gas output from each seam can be calculated to determine the main gas-producing unit.Trends in gas output from a single well or each seam can therefore be predicted.The laboratory and field test results presented here demonstrate that calculation errors in CBM outputs can be controlled within a margin of 15%and therefore conform with field use requirements.

Influence of vacuoles with gas–liquid inclusions on the thermobaric destruction conditions of natural quartz under dynamic heating in an RF-TICP torch system

In the present work,the turbulent mixing process of a polydisperse quartz particle flow with a plasma stream generated by a radio-frequency(RF)inductively coupled plasma torch was numerically studied.The thermobaric stress in the quartz particles under dynamic heating in a heterogeneous plasma flow was determined by a two-stage approximation approach.The effect of the presence of vacuoles in natural quartz on the particle thermobaric destruction conditions was studied.It was found that the equivalent thermal and baric stresses in quartz particles may significantly increase in the presence of vacuoles within a small gas volume fraction.The influence of the regime and energetic working conditions of an RF inductively coupled plasma torch system on the particle thermobaric destruction conditions was examined,and a recommendation was given to promote the degree of thermobaric destruction of quartz particles,which is of substantial importance for improving the overall enrichment efficiency of quartz concentrates.

Development and Application of a Production Data Analysis Model for a Shale Gas Production Well

This paper presents the development and application of a production data analysis software that can analyze and forecast the production performance and reservoir properties of shale gas wells.The theories used in the study were based on the analytical and empirical approaches.Its reliability has been confirmed through comparisons with a commercial software.Using transient data relating to multi-stage hydraulic fractured horizontal wells,it was confirmed that the accuracy of the modified hyperbolic method showed an error of approximately 4%compared to the actual estimated ultimate recovery(EUR).On the basis of the developed model,reliable productivity forecasts have been obtained by analyzing field production data relating to wells in Canada.The EUR was computed as 9.6 Bcf using the modified hyperbolic method.Employing the Pow Law Exponential method,the EUR would be 9.4 Bcf.The models developed in this study will allow in the future integration of new analytical and empirical theories in a relatively readily than commercial models.

Analysis of CH_(4) and H_(2) Adsorption on Heterogeneous Shale Surfaces Using aMolecular Dynamics Approach

Determining the adsorption of shale gas on complex surfaces remains a challenge in molecular simulation studies.Difficulties essentially stem from the need to create a realistic shale structure model in terms of mineral heterogeneityand multiplicity.Moreover,precise characterization of the competitive adsorption of hydrogen andmethane in shale generally requires the experimental determination of the related adsorptive capacity.In thisstudy,the adsorption of adsorbates,methane(CH_(4)),and hydrogen(H_(2))on heterogeneous shale surface modelsof Kaolinite,Orthoclase,Muscovite,Mica,C_(60),and Butane has been simulated in the frame of a moleculardynamic’s numerical technique.The results show that these behaviors are influenced by pressure and potentialenergy.On increasing the pressure from 500 to 2000 psi,the sorption effect for CH_(4)significantly increasesbut shows a decline at a certain stage(if compared to H_(2)).The research findings also indicate that raw shalehas a higher capacity to adsorb CH_(4)compared to hydrogen.However,in shale,this difference is negligible.

Obtaining 2D Soil Resistance Profiles from the Integration of Electrical Resistivity Data and Standard Penetration Test (SPT) and Light Dynamic Penetrometer (DPL) Resistance Tests—Applications in Mass Movements Studies

In Brazil and various regions globally, the initiation of landslides is frequently associated with rainfall;yet the spatial arrangement of geological structures and stratification considerably influences landslide occurrences. The multifaceted nature of these influences makes the surveillance of mass movements a highly intricate task, requiring an understanding of numerous interdependent variables. Recent years have seen an emergence in scholarly research aimed at integrating geophysical and geotechnical methodologies. The conjoint examination of geophysical and geotechnical data offers an enhanced perspective into subsurface structures. Within this work, a methodology is proposed for the synchronous analysis of electrical resistivity geophysical data and geotechnical data, specifically those extracted from the Light Dynamic Penetrometer (DPL) and Standard Penetration Test (SPT). This study involved a linear fitting process to correlate resistivity with N10/SPT N-values from DPL/SPT soundings, culminating in a 2D profile of N10/SPT N-values predicated on electrical profiles. The findings of this research furnish invaluable insights into slope stability by allowing for a two-dimensional representation of penetration resistance properties. Through the synthesis of geophysical and geotechnical data, this project aims to augment the comprehension of subsurface conditions, with potential implications for refining landslide risk evaluations. This endeavor offers insight into the formulation of more effective and precise slope management protocols and disaster prevention strategies.

Dynamic Prediction Method for Valuable Spare Parts Demand in Weaponry Equipment Based on Data Perception

Missile is an important weapon system of the army.The spare parts of missile equipment are significant effect on military operations.In order to improve the mission completion rate of missile equipment in wartime,this paper introduces data sensing method to forecast the demand of valuable spare parts of missile equipment dynamically.Firstly,the information related to valuable spare parts of missile equipment was obtained by data sensing,and the sample size was determined by Bernoulli uniform sampling probability.Secondly,according to the data quality of multi-source and multi-modal,the data requirement for dynamic demand prediction of valuable spare parts of missile equipment was obtained.Finally,according to the characteristics of the spare parts,the life of the spare parts was predicted,realizing the dynamic prediction of the demand for valuable spare parts of missile equipment.The results show that the demand of valuable spare parts of missile equipment can be predicted dynamically by using this method,the accuracy is higher than 95%,and the real-time performance is more excellent.

A Data-Oriented Method to Optimize Hydraulic Fracturing Parameters of Tight Sandstone Reservoirs

Based on the actual data collected from the tight sandstone development zone, correlation analysis using theSpearman method was conducted to determine the main factors influencing the gas production rate of tightsandstone fracturing. An integrated model combining geological engineering and numerical simulation of fracturepropagation and production was completed. Based on data analysis, the hydraulic fracture parameters wereoptimized to develop a differentiated fracturing treatment adjustment plan. The results indicate that the influenceof geological and engineering factors in the X1 and X2 development zones in the study area differs significantly.Therefore, it is challenging to adopt a uniform development strategy to achieve rapid production increase. Thedata analysis reveals that the variation in gas production rate is primarily affected by the reservoir thickness andpermeability parameters as geological factors. On the other hand, the amount of treatment fluid and proppantaddition significantly impact the gas production rate as engineering factors. Among these factors, the influence ofgeological factors is more pronounced in block X1. Therefore, the main focus should be on further optimizing thefracturing interval and adjusting the geological development well location. Given the existing well location, thereis limited potential for further optimizing fracture parameters to increase production. For block X2, the fracturingparameters should be optimized. Data screening was conducted to identify outliers in the entire dataset, and adata-driven fracturing parameter optimization method was employed to determine the basic adjustment directionfor reservoir stimulation in the target block. This approach provides insights into the influence of geological,stimulation, and completion parameters on gas production rate. Consequently, the subsequent fracturing parameteroptimization design can significantly reduce the modeling and simulation workload and guide field operations toimprove and optimize hydraulic fracturing efficiency.

Block Incremental Dense Tucker Decomposition with Application to Spatial and Temporal Analysis of Air Quality Data

How can we efficiently store and mine dynamically generated dense tensors for modeling the behavior of multidimensional dynamic data?Much of the multidimensional dynamic data in the real world is generated in the form of time-growing tensors.For example,air quality tensor data consists of multiple sensory values gathered from wide locations for a long time.Such data,accumulated over time,is redundant and consumes a lot ofmemory in its raw form.We need a way to efficiently store dynamically generated tensor data that increase over time and to model their behavior on demand between arbitrary time blocks.To this end,we propose a Block IncrementalDense Tucker Decomposition(BID-Tucker)method for efficient storage and on-demand modeling ofmultidimensional spatiotemporal data.Assuming that tensors come in unit blocks where only the time domain changes,our proposed BID-Tucker first slices the blocks into matrices and decomposes them via singular value decomposition(SVD).The SVDs of the time×space sliced matrices are stored instead of the raw tensor blocks to save space.When modeling from data is required at particular time blocks,the SVDs of corresponding time blocks are retrieved and incremented to be used for Tucker decomposition.The factor matrices and core tensor of the decomposed results can then be used for further data analysis.We compared our proposed BID-Tucker with D-Tucker,which our method extends,and vanilla Tucker decomposition.We show that our BID-Tucker is faster than both D-Tucker and vanilla Tucker decomposition and uses less memory for storage with a comparable reconstruction error.We applied our proposed BID-Tucker to model the spatial and temporal trends of air quality data collected in South Korea from 2018 to 2022.We were able to model the spatial and temporal air quality trends.We were also able to verify unusual events,such as chronic ozone alerts and large fire events.

Microscopic defects formation and dynamic mechanical response analysis of Q345 steel plate subjected to explosive load

As the basic protective element, steel plate had attracted world-wide attention because of frequent threats of explosive loads. This paper reports the relationships between microscopic defects of Q345 steel plate under the explosive load and its macroscopic dynamics simulation. Firstly, the defect characteristics of the steel plate were investigated by stereoscopic microscope(SM) and scanning electron microscope(SEM). At the macroscopic level, the defect was the formation of cave which was concentrated in the range of 0-3.0 cm from the explosion center, while at the microscopic level, the cavity and void formation were the typical damage characteristics. It also explains that the difference in defect morphology at different positions was the combining results of high temperature and high pressure. Secondly, the variation rules of mechanical properties of steel plate under explosive load were studied. The Arbitrary Lagrange-Euler(ALE) algorithm and multi-material fluid-structure coupling method were used to simulate the explosion process of steel plate. The accuracy of the method was verified by comparing the deformation of the simulation results with the experimental results, the pressure and stress at different positions on the surface of the steel plate were obtained. The simulation results indicated that the critical pressure causing the plate defects may be approximately 2.01 GPa. On this basis, it was found that the variation rules of surface pressure and microscopic defect area of the Q345 steel plate were strikingly similar, and the corresponding mathematical relationship between them was established. Compared with Monomolecular growth fitting models(MGFM) and Logistic fitting models(LFM), the relationship can be better expressed by cubic polynomial fitting model(CPFM). This paper illustrated that the explosive defect characteristics of metal plate at the microscopic level can be explored by analyzing its macroscopic dynamic mechanical response.

A LiDAR Point Clouds Dataset of Ships in a Maritime Environment

For the first time, this article introduces a LiDAR Point Clouds Dataset of Ships composed of both collected and simulated data to address the scarcity of LiDAR data in maritime applications. The collected data are acquired using specialized maritime LiDAR sensors in both inland waterways and wide-open ocean environments. The simulated data is generated by placing a ship in the LiDAR coordinate system and scanning it with a redeveloped Blensor that emulates the operation of a LiDAR sensor equipped with various laser beams. Furthermore,we also render point clouds for foggy and rainy weather conditions. To describe a realistic shipping environment, a dynamic tail wave is modeled by iterating the wave elevation of each point in a time series. Finally, networks serving small objects are migrated to ship applications by feeding our dataset. The positive effect of simulated data is described in object detection experiments, and the negative impact of tail waves as noise is verified in single-object tracking experiments. The Dataset is available at https://github.com/zqy411470859/ship_dataset.

Optimizing Memory Access Efficiency in CUDA Kernel via Data Layout Technique

Over the past decade, Graphics Processing Units (GPUs) have revolutionized high-performance computing, playing pivotal roles in advancing fields like IoT, autonomous vehicles, and exascale computing. Despite these advancements, efficiently programming GPUs remains a daunting challenge, often relying on trial-and-error optimization methods. This paper introduces an optimization technique for CUDA programs through a novel Data Layout strategy, aimed at restructuring memory data arrangement to significantly enhance data access locality. Focusing on the dynamic programming algorithm for chained matrix multiplication—a critical operation across various domains including artificial intelligence (AI), high-performance computing (HPC), and the Internet of Things (IoT)—this technique facilitates more localized access. We specifically illustrate the importance of efficient matrix multiplication in these areas, underscoring the technique’s broader applicability and its potential to address some of the most pressing computational challenges in GPU-accelerated applications. Our findings reveal a remarkable reduction in memory consumption and a substantial 50% decrease in execution time for CUDA programs utilizing this technique, thereby setting a new benchmark for optimization in GPU computing.

Adaptive Method’s Application for the Identification Systems in Dynamic Weighing

In this work,the possibility of adaptive algorithm in WIM(weight-in-motion)systems,in which fibre optic sensors are used,is shown.Appointment of dynamic weighing device consists in determining the weight and type of vehicle.In this work an algorithm for processing the input data and fiber optic sensor to create the database used in the algorithm is presented.The results of the algorithm for the identification of vehicles are given.The conclusions are made and options of increasing the accuracy of the identification algorithm are considered.