Large-scale spatial data visualization method based on augmented reality

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.

Flexible Fixture Design for the Top and End Surface Processing of NP2_NP4 Cylinder Heads

This paper focuses on the design of fixtures for NP2 and NP4 cylinder heads on a horizontal machining center of flexible machining automatic lines.It began with an analysis of the diagrams of part processing and working procedure which formed the basis for the design of the processing technology scheme,a selection of suitable machine tools,and the setting of processing parameters.Fixtures tailored to the chosen machine tools were then designed to meet the processing requirements.Additional aspects of the project included the design of part drawings,calculation of working time quota,design of auxiliary guides,support clamping,and hydraulic circuits,all aimed at fulfilling practical production requirements.

Forecasting promising technology using analysis of patent information:Focused on next generation mobile communications

In order to forecast promising technologies in the field of next generation mobile communication, various patent indicators were analyzed such as citation per patent, patent family information, patent share, increase rate, and patent activity. These indicators were quantified into several indexes and then integrated into an evaluation score to provide promising technologies. As a result of the suggested patent analysis, four technologies out of twenty two in details classification were selected, which showed outstanding technology competitiveness, high patent share and increasing rates as well as high recent-patent-ratios and triad-patent-family-ratios. Each of the selected technologies scored more than 10 points in total, and the following four technologies were suggested as promising ones in the field of next generation mobile communication: 1) 3GPP based mobile communication, 2) beyond 4G mobile communication, 3) IEEE 802.16 based mobile communication, which are in medium classification of broadband mobile communication system, and 4) testing/certification system of mobile communication, which is in medium classification of mobile communication testing/certification system.

Electrodynamic Tethered Deorbit System Dynamics and Performance Analysis

Electrodynamic tethered deorbit technology is a novel way to remove abandoned spacecrafts like upper stages or unusable satellites. This paper investigates and analyses the deorbit performance and mission applicability of the electrodynamic tethered system. To do so, the electrodynamic tethered deorbit dynamics with multi-perturbation is firstly formulated, where the Earth magnetic field, the atmospheric drag, and the Earth oblateness effect are considered. Then, the key system parameters, including payload mass, tether length and tether type, are analyzed by numerical simulations to investigate their influences on the deorbit performance and to give the setting principles for choosing system parameters. Based on this and given an appropriate group of system parameters, numerical simulations are undertaken to study the impact of the mission parameters, including orbit height and orbit inclination, and thus to investigate the mission applicability of the electrodynamic tethered deorbit technology.

GSM-WLL Technology and Its Market Analysis

1 GSM-WLL Technology1.1 GSM-WLL System ArchitectureAWLL (Wireless Local Loop)is a radioaccess system for users to access PSTN(Public Switched Telephone Network).It isa substitute for conventional wiredaccess.The GSM-WLL system makes use ofGSM technologies to achieve WLL.As shown in Figure 1,a GSM-WLL system

A review of intelligent ore sorting technology and equipment development

Under the background of increasingly scarce ore worldwide and increasingly fierce market competition,developing the mining industry could be strongly restricted.Intelligent ore sorting equipment not only improves ore use and enhances the economic benefits of enterprises but also increases the ore grade and lessens the grinding cost and tailings production.However,long-term research on intelligent ore sorting equipment found that the factors affecting sorting efficiency mainly include ore information identification technology,equipment sorting actuator,and information processing algorithm.The high precision,strong anti-interference capability,and high speed of these factors guarantee the separation efficiency of intelligent ore sorting equipment.Color ore sorter,X-ray ore transmission sorter,dual-energy X-ray transmission ore sorter,X-ray fluorescence ore sorter,and near-infrared ore sorter have been successfully developed in accordance with the different characteristics of minerals while ensuring the accuracy of equipment sorting and improving the equipment sorting efficiency.With the continuous improvement of mine automation level,the application of online element rapid analysis technology with high speed,high precision,and strong anti-interference capability in intelligent ore sorting equipment will become an inevitable trend of equipment development in the future.Laser-induced breakdown spectroscopy,transientγneutron activation analysis,online Fourier transform infrared spectroscopy,and nuclear magnetic resonance techniques will promote the development of ore sorting equipment.In addition,the improvement and joint application of additional high-speed and high-precision operation algorithms(such as peak area,principal component analysis,artificial neural network,partial least squares,and Monte Carlo library least squares methods)are an essential part of the development of intelligent ore sorting equipment in the future.

An Overview of Big Data Industry in China

The year of 2011 is considered the first year of big data market in China.Compared with the global scale,China's big data growth will be faster than the global average growth rate,and China will usher in the rapid expansion of big data market in the next few years.This paper presents the overall big data development in China in terms of market scale and development stages,enterprise development in the industry chain,the technology standards,and industrial applications.The paper points out the issues and challenges facing big data development in China and proposes to make polices and create support approaches for big data transactions and personal privacy protection.

Impact of Removal of City Gas Subsidies on Chinese Urban Residents

The current cost-plus natural gas pricing mechanism makes the gas price too low,resulting in a lot of consumer-side subsidies and over-consumed natural gas.This paper applies the price-gap approach and input-output analysis technology to quantitatively analyze both the direct and indirect effects on urban residents under the condition that natural gas subsidies are cancelled in China in 2007.It is shown that the gas price will increase by 33.3%-41.6%,and the residential consumption expenditure by 0.26%-0.33%.The low-income groups are mostly affected,so different subsidies should be implemented to make subsidies more efficient.

CO2 emission driving forces and corresponding mitigation strategies under low-carbon economy mode:evidence from China's Beijing-Tianjin-Hebei region

On account of the background of China's "new normal" characterized by slower economic growth, this paper analyses the low-carbon economy status quo in the Beijing-Tianjin-Hebei region and empirically investigates the relationship between carbon dioxide(CO_2) emissions and its various factors for China's Beijing-Tianjin-Hebei region using panel data econometric technique. We find evidence of existence of Environmental Kuznets Curve. Results also show that economic scale, industrial structure, and urbanization rate are crucial factors to promote CO_2emissions. However, technological progress, especially the domestic independent research and development, plays a key role in C0_2 emissions abatement. Next, we further analyze the correlation between each subregion and various factors according to Grey Relation Analysis. Thereby,our findings provide important implications for policymakers in air pollution control and C0_2 emissions reduction for this region.

Differential Expression of Genes in HepG2 Cells Caused by UC001kfo RNAi as Shown by RNA-seq

The differential expression of genes in HepG2 cells caused by UC001 kfo RNAi was investigated using RNA-seq. HepG2 cells were infected by Lenti-sh UC001 kfo lentivirus particles. The expression of UC001 kfo m RNA in the HepG2-sh UC001 kfo cell line was detected by real-time PCR. RNA-seq technology was used to identify the difference in the expression of genes regulated by lnc RNA UC001 kfo in the HepG2 cell line. Gene ontology and signaling pathway analysis were performed to reveal the biological functions of the genes encoding of significantly different m RNAs. The results showed that m RNAs were differentially expressed between the HepG2-sh UC001 kfo cell line and the HepG2 cell line. The UC001 kfo m RNA was significantly down-regulated in the stable cell line HepG2-sh UC001kfo（P〈0.001）. Additionally, we found 19 signaling pathways or functional classifications encompassing 30 genes that played a role in cancer characteristics, cell adhesion, invasion and migration. The results also showed that the expression of many genes associated with cancer cell invasion and metastasis was decreased with the down-regulation of the lnc RNA UC001 kfo. Lnc RNA UC001 kfo may play a role in regulating cancer cell invasion and metastasis. It was suggested that m RNAs were differentially expressed in the HepG2 cell line after the down-regulation of lnc RNA-UC001 kfo. Some took part in the extracellular matrix, cell adhesion, motility, growth, and localization. The genes encoding of differentially expressed m RNAs may participate in cell invasion and metastasis.

A Morphology-Driven Method for Measuring Technology Complementarity:Empirical Study Involving Alzheimer’s Disease

Purpose:Measuring the exact technology complementarity between different institutions is necessary to obtain complementary technology resources for R&D cooperation.Design/methodology/approach:This study constructs a morphology-driven method for measuring technology complementarity,taking medical field as an example.First,we calculate semantic similarities between subjects(S and S)and action-objects(AO and AO)based on the Metathesaurus,forming clusters of S and AO based on a semantic similarity matrix.Second,we identify key technology issues and methods based on clusters of S and AO.Third,a technology morphology matrix of several dimensions is constructed using morphology analysis,and the matrix is filled with subjects-action-objects(SAO)structures according to corresponding key technology issues and methods for different institutions.Finally,the technology morphology matrix is used to measure the technology complementarity between different institutions based on SAO.Findings:The improved technology complementarity method based on SAO is more of a supplementary and refined framework for the traditional IPC method.Research limitations:In future studies we will reprocess and identify the SAO structures which were not in the technology morphology matrix,and find other methods to characterize key technical issues and methods.Furthermore,we will add the comparison between proposed method and traditional and mostly used complementarity measurement method based on industry chain and industry code.Practical implications:This study takes medical field as an example.The morphology-driven method for measuring technology complementarity can be migrated and applied for any given field.Originality/value:From the perspective of complementary technology resources,this study develops and tests a more accurate morphology-driven method for technology complementarity measurement.

Optical Measurements to Reveal Roles of Slightly Crosslinked Poly (dimethyldiallylammonium chloride) s in Fixing Anionic Dyes on Cotton Fabric

The roles of slightly crosslinked poly( dimethyldiallylammonium chloride) s( PDMDAACs) in fixing anionic dyes on cotton fabric were verified more precisely by optical analysis technologies,to achieve the new theoretical guides for the widely applications. Firstly,one method of optical CIELAB color difference analysis was designed to exactly measure the values of dyefixing performances, so that the suitable molecular weights and structures of the slightly crosslinked PDMDAACs could be precisely confirmed to play a role in the development of their dye-fixing performances. Secondly,the FT-IR absorption shift of the dye on dyed cotton sample fixed by slightly crosslinked PDMDAACs was nearly in agreement with that of forming water-insoluble color lakes,indicating that the expected color lakes could be formed on dyed cotton fabric,and would play a role in further development of the fastness of dyes on cotton fabric. Thirdly,the FT-IR spectra of fixed undyed cotton samples and that of fixed dyed cotton samples both showed the absorptions of slightly crosslinked PDMDAACs,further revealing that the slightly crosslinked PDMDAACs could be penetrated into cotton fabric and be convenient to interact with dyes when fixing. However,those absorptions of the slightly crosslinked PDMDAACs fixed on cotton samples would be absent after being adequately washed to a constant weight,suggesting that the fixing interactions of the slightly crosslinked PDMDAAC and cotton fabric were very weak.

A tentative study on security management based on dangerous goods road transportation

The paper conducts analysis on the causes of dangerous goods road transportation accidents by applying analytic technique of security system science - Event Tree Analysis （ETA）. By computing minimum cut and minimal path set of event tree and the important level of elementary event, the paper elicits the results that the factors of causing road transportation accident are multiple and its hazard is great while the paper also elicits the sorting of structural important level of elementary event. The paper offers the security countermeasures for dangerous goods road transportation which plays a vital role in safeguarding dangerous goods road transportation security.

AI Inventions: The Best Mode Requirement, Is It up for Redefinition, Minimizing Potential Innovation Bias and Optimizing Visual Aids?

From the author, there are not less than a dozen of rather significant recent publications in scientific editions anticipating some aspects of importance to innovation such as “bigger data”, AI, IP, and frontier technology with a central massive contribution in 2020 on AI, IP, and EI. Nonetheless, the IP associated with AI remains still barely covered in scientific publications. Especially patent discussion tends to be rather a legal matter. Another trilogy, 2013, “Business Strategy-IP Strategy-R&D Strategy: An All-in-One Business Model” proposed by the author, marked the advent, and customized implementation of a new strategy level. After the two trilogies’ volumes, the AI-IP “accessibility” chapter was a logical step brought to the attention of a larger public by the author. The time now to bring to light another chapter, namely the IP eligibility of AI innovation steps in ad hoc inventions. The main objectives of this short, principally illustrated communication, are to: 1) Revise the best mode requirement status, i.e. the best way to enable the reproducibility of claimed matter, reviewing its need for improvement when AI is involved. And proposing a unique sequence of evolution inspired by IP’s current and evolving practices. 2) Give a new dimension to visual aids to help the Best Mode description, demystify AI complexity, and underline frontier traits that may hinder a confident adoption or well-argued rejection. 3) Further illustrations take into account the fact that IoT, AI, and 3D can be simpler than perceived. 4) Finally ATA©, Adjacent Technology Analysis, is timely refreshed in a unique challenging, indeed tumultuous, environment. 5) Bias, such as semantic ones is consistently monitored. 6) Overall leaving space for innovative pleasurable interpretation. The emphasis is on educational, illustrative and demonstrative value.

Automatic discovery of stateful variables in network protocol software based on replay analysis

Network protocol software is usually characterized by complicated functions and a vast state space.In this type of program,a massive number of stateful variables that are used to represent the evolution of the states and store some information about the sessions are prone to potentialflaws caused by violations of protocol specification requirements and program logic.Discovering such variables is significant in discovering and exploiting vulnerabilities in protocol software,and still needs massive manual verifications.In this paper,we propose a novel method that could automatically discover the use of stateful variables in network protocol software.The core idea is that a stateful variable features information of the communication entities and the software states,so it will exist in the form of a global or static variable during program execution.Based on recording and replaying a protocol program’s execution,varieties of variables in the life cycle can be tracked with the technique of dynamic instrument.We draw up some rules from multiple dimensions by taking full advantage of the existing vulnerability knowledge to determine whether the data stored in critical memory areas have stateful characteristics.We also implement a prototype system that can discover stateful variables automatically and then perform it on nine programs in Pro FuzzBench and two complex real-world software programs.With the help of available open-source code,the evaluation results show that the average true positive rate(TPR)can reach 82%and the average precision can be approximately up to 96%.

Discussion on Municipal Road Design Optimization based on BIM Technology

In order to improve the implementability of municipal road design,the rational application of BIM Technology in the process of road design is a common method in current road engineering design units.The advantages of BIM Technology,such as visualization,simulation,coordination and optimization,are increasingly recognized by the industry.In this paper,the author draws on many years of practical experience to introduce the advantages of BIM Technology,as well as how to apply BIM Technology to optimize municipal road design work and to discuss some views,in the hopes of assisting in the further improvement of the level of municipal road constructions in China.

Assessing Coarctation of the Aorta With Fetal Heart Quantification Technology

Objective:To use fetal heart quantification(fetal HQ)technology to compare the coarctation of the aorta(CoA)and normal fetal heart structure and systolic function and to assess whether there are abnormalities in the fetal heart structure and systolic function associated with CoA.Methods:This prospective cohort study was conducted from May 2020 to December 2022 and involved 18–40-week-old singleton pregnancies and 30 fetuses diagnosed with CoA using fetal echocardiography at the General Hospital of Ningxia Medical University and Peking University First Hospital Ningxia Women’s andChildren’s Hospital,China.The control group contained 60 normal fetuses.The following parameters were recorded and analyzed statistically:four-chamber view(4CV)end-diastolic long diameter,4CV epicardial–contralateral epicardial transverse maximum diameter,4CV global sphericity index(GSI),left ventricular(LV)and right ventricular(RV)24-segment end-diastolic diameter(EDD),24-segment sphericity index(SI),LV-fractional area change(LV-FAC),LV-longitudinal strain(LV-LS),RV-fractional area change(RV-FAC),RV-longitudinal strain(RV-LS),and LV and RV 24-segment transverse fractional shortening(FS).Measurement data were compared between the two groups using an independent sample t test,with P<0.05 indicating statistically significant differences.Moreover,the correlation between gestational age and GSI,LV-FAC,LV-LS,RV-FAC,and RV-LS was assessed.Results:Within and between observer comparisons of the parameters associated with major cardiac function revealed an intragroup correlation coefficient of>0.9,indicating high consistency,and a coefficient of variable of<1%,indicating low variability.Correlation analysis revealed no obvious correlation between gestational age and GSI,LV-FAC,LV-LS,RV-FAC,and RV-LS.A comparison of the fourchamber morphological structural parameters of the hearts in the two groups revealed that when compared with the control group,the 4CV end-diastolic long diameter was shortened in fetuses in the CoA group and the epicardial–contralateral epicardial transverse maximum diameter was wider,while the GSI was lower(P<0.05).A comparison of the LV and RV morphological structure parameters between the two groups revealed that when compared with the control group,the LV’s 24-segment EDD was smaller in the CoA group,the RV’s 24-segment EDD was greater in the control group,the SI of the LV’s segments 16–24 was greater than in the control group,and the SI of the RV’s segments 7–24 was less than in the control group(all P<0.05).When comparedwith fetuses in the control group,the LV’s segments16–24 were greater in the CoA group,whereas the RV’s segment 6–24 was smaller(P<0.05).When comparedwith the control group,LV-FAC,RV-FAC,and LS were lower in the CoA group(P<0.05).The FS of the LV segments 1–24 and the FS of the RV segments 1–16 were smaller in the CoA group than in the normal group(P<0.05).Conclusion:Fetal HQ,a new simple technique that offers rapid analysis and high repeatability,can quantitatively evaluate structural and systolic function changes in fetuses with CoA.

Automatic detection of ruminant cows’ mouth area during rumination based on machine vision and video analysis technology

In order to realize the automatic monitoring of ruminant activities of cows,an automatic detection method for the mouth area of ruminant cows based on machine vision technology was studied.Optical flow was used to calculate the relative motion speed of each pixel in the video frame images.The candidate mouth region with large motion ranges was extracted,and a series of processing methods,such as grayscale processing,threshold segmentation,pixel point expansion and adjacent region merging,were carried out to extract the real area of cows’mouth.To verify the accuracy of the proposed method,six videos with a total length of 96 min were selected for this research.The results showed that the highest accuracy was 87.80%,the average accuracy was 76.46%and the average running time of the algorithm was 6.39 s.All the results showed that this method can be used to detect the mouth area automatically,which lays the foundation for automatic monitoring of cows’ruminant behavior.

Multi-channel microfluidic chip-mass spectrometry platform for cell analysis

In this review, we highlight the latest development of multi-channel microfluidic chip-mass spectrometry（chip-MS） in cell analysis and metabolite detection. Following a brief introduction about history and development of multi-channel microchip and MS combination, we will elaborate the key issues of constructing chip-MS platform interface. Then exciting progresses made in this field should be reviewed with well exemplified works, including chip-MS technology for cell introduction, pretreatment of cell secretions and cell metabolite analysis. We will also describe the development of integrated total analysis systems proposed by our group. We hope this brief review will inspire interested readers and provide knowledge about chip-MS platform in the bioanalysis field, particularly in cell analysis and metabolite identifying applications.

A disk failure prediction model for multiple issues

Disk failure prediction methods have been useful in handing a single issue,e.g.,heterogeneous disks,model aging,and minority samples.However,because these issues often exist simultaneously,prediction models that can handle only one will result in prediction bias in reality.Existing disk failure prediction methods simply fuse various models,lacking discussion of training data preparation and learning patterns when facing multiple issues,although the solutions to different issues often conflict with each other.As a result,we first explore the training data preparation for multiple issues via a data partitioning pattern,i.e.,our proposed multi-property data partitioning(MDP).Then,we consider learning with the partitioned data for multiple issues as learning multiple tasks,and introduce the model-agnostic meta-learning(MAML)framework to achieve the learning.Based on these improvements,we propose a novel disk failure prediction model named MDP-MAML.MDP addresses the challenges of uneven partitioning and difficulty in partitioning by time,and MAML addresses the challenge of learning with multiple domains and minor samples for multiple issues.In addition,MDP-MAML can assimilate emerging issues for learning and prediction.On the datasets reported by two real-world data centers,compared to state-of-the-art methods,MDP-MAML can improve the area under the curve(AUC)and false detection rate(FDR)from 0.85 to0.89 and from 0.85 to 0.91,respectively,while reducing false alarm rate(FAR)from 4.88%to 2.85%.