Elbow precision machining technology by abrasive flow based on direct Monte Carlo method

The investigation was carried out on the technical problems of finishing the inner surface of elbow parts and the action mechanism of particles in elbow precision machining by abrasive flow.This work was analyzed and researched by combining theory,numerical and experimental methods.The direct simulation Monte Carlo(DSMC)method and the finite element analysis method were combined to reveal the random collision of particles during the precision machining of abrasive flow.Under different inlet velocity,volume fraction and abrasive particle size,the dynamic pressure and turbulence flow energy of abrasive flow in elbow were analyzed,and the machining mechanism of particles on the wall and the influence of different machining parameters on the precision machining quality of abrasive flow were obtained.The test results show the order of the influence of different parameters on the quality of abrasive flow precision machining and establish the optimal process parameters.The results of the surface morphology before and after the precision machining of the inner surface of the elbow are discussed,and the surface roughness Ra value is reduced from 1.125μm to 0.295μm after the precision machining of the abrasive flow.The application of DSMC method provides special insights for the development of abrasive flow technology.

Research of Digital Manufacturing Technology Application on Ultra-precision Optical Workpiece Machining

Digital manufacturing technology can be used in optical field to solve many problems caused by traditional machining. According to the characters of digital manufacturing and the practical applications of ultra-precision machining,the process of digital ultra-precision machining and its technical contents were presented in this paper. In the conclusions,it was stated that the digitalization of ultra-precision machining will be an economical and efficient way for the production of new sorts of optical workpieces.

345 GHz Band-Pass Filter Using Ultra-Precision Machining Technology

This paper presents a terahertz（THz）band-pass filter using ultra-precision machining technology based on Chebyshev filter prototype.This iris inductive window coupled waveguide filter was designed by using 8 resonant cavities with a center frequency of 345 GHz and a 7% bandwidth.The final design fulfills the desired specifications and presents the minimum insertion loss of 1.55 d B and the return loss of less than 15 d B at 345 GHz.The stop-band rejection is50 d B off the center frequency about 30 GHz,which means it has a good performance of high stop-band suppression.Compared with the recent development of THz filters,this filter possesses the characteristic of simple structure and is easy to machining.

Ethical Principles and Governance Technology Development of AI in China

Ethics and governance are vital to the healthy and sustainable development of artificial intelligence(AI).With the long-term goal of keeping AI beneficial to human society,governments,research organizations,and companies in China have published ethical guidelines and principles for AI,and have launched projects to develop AI governance technologies.This paper presents a survey of these efforts and highlights the preliminary outcomes in China.It also describes the major research challenges in AI governance research and discusses future research directions.

Rock mass structural recognition from drill monitoring technology in underground mining using discontinuity index and machine learning techniques

A procedure to recognize individual discontinuities in rock mass from measurement while drilling(MWD)technology is developed,using the binary pattern of structural rock characteristics obtained from in-hole images for calibration.Data from two underground operations with different drilling technology and different rock mass characteristics are considered,which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis.Two approaches are followed for site-specific structural model building:a discontinuity index(DI)built from variations in MWD parameters,and a machine learning(ML)classifier as function of the drilling parameters and their variability.The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs.Differences between the parameters involved in the models for each site,and differences in their weights,highlight the site-dependence of the resulting models.The ML approach offers better performance than the classical DI,with recognition rates in the range 89%to 96%.However,the simpler DI still yields fairly accurate results,with recognition rates 70%to 90%.These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.

OPEN ARCHITECTURE CNC SYSTEM HITCNC AND KEY TECHNOLOGY

Aiming at the characteristics of modularity and reconfigurable in open architecture computer numerical control （CNC） system, the open architecture CNC system, Harbin Institute of Tech- nology computer numerical control （HITCNC）, is researched and manufactured based on the interface standards. The system＇s external interfaces are coincident with the corresponding international standards, and the internal interfaces follow the open modular architecture controller （OMAC） agreement. In the research and manufacturing process, object-oriented technology is used to ensure the openness of the HITCNC, and static programming is applied in the CNC system according to the idea of modularization disassembly. The HITCNC also actualizes real-time and unreal-time modules adopting real-time dynamical linked library （RTDLL） and component object model （COM）. Finite state ma- chine （FSM） is adopted to do dynamically modeling of HITCNC. The complete separation between the software and the hardware is achieved in the HITCNC by applying the SoftSERCANS technique. The application of the above key techniques decreases the programming workload greatly, and uses software programs replacing hardware functions, which offers plenty technique ensures for the openness of HITCNC. Finally, based on the HITCNC, a three-dimensional milling system is established. On the system, series experiments are done to validate the expandability and interchangeability of HITCNC. The results of the experiments show that the established open architecture CNC system HITCNC is correct and feasible, and has good openness.

Implementing an innovated liver ex-situ machine perfusion technology:The 2018 Joint International Congress of ILTS,ELITA and LICAGE

The 2018 Joint International Congress of ILTS,ELITA and LICAGE were held in Lisbon,Portugal on May 23–26,2018.The exciting and innovative program brought together 1144 experts in liver transplantation(LT)such as surgeons,physicians or basic scientists from 61 countries.The presentations included 110 invited speakers,181 oral presentations,and 545 posters.This editorial highlights some of the most innovative and impactful presentations in

Research on Wireless Monitoring Technology of the Well Site Environment

Based on the characteristics of wireless communication technology and Wireless Sensor Network, this paper studies the well site environmental monitoring system. The relevant hardware and software of the system are designed to monitor the well site environment, thus preventing downhole accidents. The system uses the wireless ZigBee technology as the transmission mode, and combines the virtual instrument technology to design the upper machine interface. The test results show that the system can monitor the outdoor environment in real time. When the environmental parameters exceed the set value, the corresponding location of the LabVIEW interface will send an alarm.

Leveraging Geospatial Technology for Smallholder Farmer Credit Scoring

According to the Food and Agriculture Organization of the United Nations (FAO), there are about 500 million smallholder farmers in the world, and in developing countries, such farmers produce about 80% of the food consumed there;their farming activities are therefore critical to the economies of their countries and to the global food security. However, these farmers face the challenges of limited access to credit, often due to the fact that many of them farm on unregistered land that cannot be offered as collateral to lending institutions;but even when they are on registered land, the fear of losing such land that they should default on loan payments often prevents them from applying for farm credit;and even if they apply, they still get disadvantaged by low credit scores (a measure of creditworthiness). The result is that they are often unable to use optimal farm inputs such as fertilizer and good seeds among others. This depresses their yields, and in turn, has negative implications for the food security in their communities, and in the world, hence making it difficult for the UN to achieve its sustainable goal no.2 (no hunger). This study aimed to demonstrate how geospatial technology can be used to leverage farm credit scoring for the benefit of smallholder farmers. A survey was conducted within the study area to identify the smallholder farms and farmers. A sample of surveyed farmers was then subjected to credit scoring by machine learning. In the first instance, the traditional financial data approach was used and the results showed that over 40% of the farmers could not qualify for credit. When non-financial geospatial data, i.e. Normalized Difference Vegetation Index (NDVI) was introduced into the scoring model, the number of farmers not qualifying for credit reduced significantly to 24%. It is concluded that the introduction of the NDVI variable into the traditional scoring model could improve significantly the smallholder farmers’ chances of accessing credit, thus enabling such a farmer to be better evaluated for credit on the basis of the health of their crop, rather than on a traditional form of collateral.

Research and test of the adaptive quadrature demodulation technology for silicon micro-machined gyroscope

A program of adaptive quadrature demodulation is proposed to supply the gaps in the traditional analog detection technology of a silicon micro-machined gyroscope (SMG). This program is suitable for digital phase locked loop (DPLL) drive technology that proposed in other papers. In addition the program adopts an adaptive filtering algorithm, which selects the in-phase and quadrature components that are outputs of the DPLL of the SMG's drive mode as reference signals to update the amplitude of the in-phase and quadrature components of the input signal by iteratively. An objective of the program is to minimize the mean square error of the accurate amplitudes and the estimated amplitudes of SMG's detection mode. The simulation and test results prove the feasibility of the program that lays the foundation for the further improvement of the SMG's system performance and the implementation of the SMG system's self-calibration and self-demarcation in future.

Is the Genie of Artificial Intelligence Technology Out of the Bottle and Control?(A Short Review)

In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repercussions have surfaced.This article investigates the claim that AI technology has broken free from human control and is now unstoppable.We look at how AI is developing right now,what it means for society,and what steps are being taken to reduce the risks that come with it.We seek to highlight the need for responsible development and implementation of this game-changing technology by examining the opportunities and challenges that AI presents.

Research on Manufacturing Technology Based on Machine Vision

The concept of machine vision based manufacturing technology is proposed first,and the key algorithms used in two-dimensional and three-dimensional machining are discussed in detail.Machining information can be derived from the binary images and gray picture after processing and transforming the picture.Contour and the parallel cutting method about two-dimen- sional machining are proposed.Polygon approximating algorithm is used to cutting the profile of the workpiece.Fill Scanning al- gorithm used to machining inner part of a pocket.The improved Shape From Shading method with adaptive pre-processing is adopted to reconstruct the three-dimensional model.Layer cutting method is adopted for three-dimensional machining.The tool path is then gotten from the model,and NC code is formed subsequently.The model can be machined conveniently by the lathe, milling machine or engraver.Some examples are given to demonstrate the results of lmageCAM system,which is developed by the author to implement the algorithms previously mentioned.

The Symbiotic Relationship Unraveling the Interplay between Technology and Artificial Intelligence(An Intelligent Dynamic Relationship)

This article investigates the dynamic relationship between technology and AI(artificial intelligence)and the role that societal requirements play in pushing AI research and adoption.Technology has advanced dramatically throughout the years,providing the groundwork for the rise of AI.AI systems have achieved incredible feats in various disciplines thanks to advancements in computer power,data availability,and complex algorithms.On the other hand,society’s needs for efficiency,enhanced healthcare,environmental sustainability,and personalized experiences have worked as powerful accelerators for AI’s progress.This article digs into how technology empowers AI and how societal needs dictate its progress,emphasizing their symbiotic relationship.The findings underline the significance of responsible AI research,which considers both technological prowess and ethical issues,to ensure that AI continues to serve the greater good.

Industrial internet technology,resource reallocation and corporate risk-taking capacity:Evidence from the strategic management perspective

By employing machine learning techniques and the Word2Vec model,we quantify the micro-level implementation of Industrial Internet technology in Chinese manufacturing firms from 2010 to 2022.This provides empirical evidence for understanding how the Industrial Internet technology enhances corporate risk-taking capability.Our study shows that adopting this technology increases risk-taking capacity,mainly through resource reallocation.The information layer empowers improvements in organizational structure,the platform layer optimizes labor resources,and the edge/software layers facilitate the integration of supply chain resources.The effect is more pronounced in firms that are technology-and labor-intensive,particularly in environments of high economic policy uncertainty.In conclusion,the Industrial Internet boosts total factor productivity by fostering increased risk-taking.

Review of air disturbance technology for plant frost protection

Confronted with severe frost damage to plants,methods,technologies and equipment have been developed and applied during the past century.The paper presents a comprehensive review on the most effective and active technology to protect plants from radiation frost based on air disturbance technology.The working principle of the technology was elaborated with frost protection mechanism,structures and applicability of three types of working patterns:conventional wind machines,selective inverted sink and portable vertical blowing.As an automatic mechanized technology,control strategy,applicable occasion and proper parameters are introduced for each type of working pattern.The operation of the technology and equipment depends on plant critical temperature,prevailing climatic conditions,thermal inversions strength,as well as costs.The frost protection performance and effectiveness of conventional horizontal wind machines,selective inverted sinks and helicopters are discussed and compared from the cost-effectiveness and application aspects,and the feasibility of selective inverted sinks is still controversial.Therefore,conventional wind machines are the best choice for plant frost protection and consequently are widely used in temperate and subtropical areas throughout the world.The frost protection application with helicopters is not easy to use during the frost nights with high cost.The paper also provides researchers with some perspectives on improving air disturbance technology and its equipment,and some practice recommendations for growers.

Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical research.The review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health monitoring.Major findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and diagnosis.The synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment strategies.Additionally,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease detection.The review emphasizes the need for interdisciplinary collaboration to further advance this field.Future research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and security.By fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

A Definition Formalism of Machining Features for DFM

Benefiting from advances in feature technology for design and manufacture can not be expected before a formal methodology is established. This paper makes attempt to establish a definition formalism of machining features in design for manufacturability from two aspects: formal definition and manufacturability analysis. Some definitions for machining feature based upon the selection and sequencing of material removal operations for component in accordance with the design geometry are presented and a framework of feature based design for manufacturability is outlined correspondingly. The proposed scheme contributes to several aspects of feature based CAD/CAM integration, especially to encourage potentially a more generic approach to the automation of design.

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.

NC Rough Machining of Sculptured Surface Based on Measured Data

A new method for generating tool paths for rough machining of sculpturedsurface is presented in this paper. The sculptured surface is approximated by a regular mesh ofquadrangular facets. A set of equidistant horizontal planes are assigned to intersect the blank ofmachined part and surface model , resulting in a series of contours, which demarcate the feasiblecutting regions of each layer of material removal. The desired cutter path is computed through NCprogramming and any gouging between the cutter and the part being machined is detected and correctedautomatically. The proposed algorithm successfully solves the problem of layered milling forsculptured surface with nested islands.

Data-driven technology of fault diagnosis in railway point machines:review and challenges

Safety and reliability are absolutely vital for sophisticated Railway Point Machines(RPMs).Hence,various kinds of sensors and transducers are deployed on RPMs as much as possible to monitor their behaviour for detection of incipient faults and anticipation using data-driven technology.This paper firstly analyses and summarizes six RPMs’characteristics and then reviews the data-driven algorithms applied to fault diagnosis in RPMs during the past decade.It provides not only the process and evaluation metrics but also the pros and cons of these different methods.Ultimately,regarding the characteristics of RPMs and the existing studies,eight challenging problems and promising research directions are pointed out.