The Advantages of Using Rotating Machines with Profiled Rotors

In order to achieve a lower consumed energy, the performance of a new type of rotating volumetric pump with two profiled rotors (variant I) which is compared with a centrifugal pump (variant II) is presented. The analysis regarding the same flow rate of transported liquid and the same pressure increases points out the conduct of the system at the variation of the key operating parameters. The actual driving power of the rotating volumetric pump is higher stating that is more advantageous in operation. The effective efficiency of the system is improved due to the original constructive solution.

PROFILL滚挤机床故障分析及改造

通过对PROFILL滚挤机床从动支撑轴无动作故障的原因进行分析,阐述了解决过程,并对设备进行了预防性改造。

Design on Tool Profile for Machining Cone Screw with Opposed Conical High Pressure Seawater Hydraulic Pump

In order to meet the requirements of the machining process of cone screw of the Opposed Conical High Pressure Seawater Hydraulic Pump,this work describes the design process to determine the theoretical profile of the tool,starting from the surface equation of the cone screw. Along with the expression of the theoretical tool profile,the equation of the contact line between the cone screw and the tool is established based on the coordinate transformation theory and the space meshing theory,as well as the surface equation and the position relationship between the screw and the tool during processing. By solving the contact condition based on the method of numerical discretization analysis via MATLAB,the contact line trajectory and theoretical tool profile curve are derived.The feasibility of the proposed method is verified by an example of tool profile design for machining the screw.

Metabonomic analysis of hepatitis B virus-induced liver failure:identification of potential diagnostic biomarkers by fuzzy support vector machine

Hepatitis B virus （HBV）-induced liver failure is an emergent liver disease leading to high mortality. The severity of liver failure may be reflected by the profile of some metabolites. This study assessed the potential of using metabolites as biomarkers for liver failure by identifying metabolites with good discriminative performance for its phenotype. The serum samples from 24 HBV-indueed liver failure patients and 23 healthy volunteers were collected and analyzed by gas chromatography-mass spectrometry （GC-MS） to generate metabolite profiles. The 24 patients were further grouped into two classes according to the severity of liver failure. Twenty-five eommensal peaks in all metabolite profiles were extracted, and the relative area values of these peaks were used as features for each sample. Three algorithms, F-test, k-nearest neighbor （KNN） and fuzzy support vector machine （FSVM） combined with exhaustive search （ES）, were employed to identify a subset of metabolites （biomarkers） that best predict liver failure. Based on the achieved experimental dataset, 93.62% predictive accuracy by 6 features was selected with FSVM-ES and three key metabolites, glyeerie acid, cis-aeonitie acid and citric acid, are identified as potential diagnostic biomarkers.

Study of CNC Grinding Machining Method About Isometric Polygon Profile

The formed principle and CNC grinding machining method of isometric polygonal profile are studied deeply and systematically. Equation about section curve of isometric polygon profile is set up by means of geometric principle. With the use of differential geometry theory, the curve is proved to be with geometric feature of convex curve. It is referred to as Isometric Polygonal Curve (IPC), because that is a kind of convex curve on which the distance between any parallel tangent lines is equal. Isometric Polygonal Profile (IPP) or Isometric Polygonal Cone Profile (IPCP) or Isometric Polygonal Topless Cone (IPTC) is formed with the IPC and straight line as generating curve. But the machining and measuring of the IPCP are so inconvenient that it has little value. Keeping in mind the characteristic of the IPP and IPTC, this paper puts forward the program method of CNC grinding machining. Isometric polygonal profile connection is a kind of polygonal profile connection. It has the superiority over keys (prismatic key & spline etc), and can be suit for the situations such as high rotative velocity, large torque, high precision, and small fixed room and vibration. Nowadays, some countries such as America, Russia, German and Switzerland applied CNC machining to the machining of polygon surface coupling parts, which makes their applications in machine productions such as motor engine, heavy machine increase day by day. But reports about concrete machining technology of isometric polygonal profile and programming of CNC machining program are very few. CNC grinding of the IPP and IPTC is one kind of the precision machining technology. It is of great importance to the popularization of the IPP and IPTC connection. From the forming mechanism, we can see that the machining and measuring of the IPP and IPTC are convenient, and therefore they have the value of the popularization. But the machining and measuring of the IPCP are so inconvenient that it has little value. In the programming the CNC grinding of the IPP and IPTC, it is more reasonable to calculate the coordinate of node according to the approaching method of equal error arc. According to the method of CNC grinding mentioned above to design the grinding machine, the structure is simple and of economical and practical.

Technological requirements of profile machining

The term ‘profile machining’ is used to refer to the milling of vertical surfaces described by profile curves. Profile machining requires higher precision (1/1000 mm) than regular 3D machining (1/100 mm) with the erosion of sharp vertices should being especially avoided. Although, profile machining is very essential for making trimming and flange dies, it seldom brought into focus. This paper addresses the technological requirements of profile machining including machining width and depth control, minimizing toolware, and protecting sharp vertices. Issues of controller alarms are also addressed.

Masquerade Detection Using Support Vector Machine

A new method using support vector data description (SVDD) to distinguishlegitimate users from mas-queradcrs based on UNIX user command sequences is proposed Sliding windowsare used to get low detection delay. Experiments demonstrate that the detection effect usingenriched sequences is better than that of using truncated sequences. As a SVDD profile is composedof a small amount of support vectors, our SVDD-based method can achieve computation and storageadvantage when the detection performance issimilar to existing method.

Author’s Age and Gender Prediction on Hotel Review Using Machine Learning Techniques

Author’s Profile(AP)may only be displayed as an article,similar to text collection of material,and must differentiate between gender,age,education,occupation,local language,and relative personality traits.In several informationrelated fields,including security,forensics,and marketing,and medicine,AP prediction is a significant issue.For instance,it is important to comprehend who wrote the harassing communication.In essence,from a marketing perspective,businesses will get to know one another through examining items and websites on the internet.Accordingly,they will direct their efforts towards a certain gender or age restriction based on the kind of individuals who comment on their products.Recently many approaches have been presented many techniques to automatically detect user age and gender from the language which is based on text,documents,or comments on social media.The purpose of this research is to classify age(18–24,25–34,35–49,50–64,and 65–70)and gender(male,female)from a PAN 2014 Hotel Reviews dataset of the English language.The usage of six machine learning models is the main emphasis of this work,including the methods of Support Vector Machine(SVM),Random Forest(RF),Naive Bayes(NB),Logistic Regression(LR),Decision Tree(DT)and K-Nearest Neighbors(KNN).

A Calculation Method of Profile Error Influenced by Tool Error for Two-Axis Coordinated CNC Machining of a Spatial Barrel-Cam

Taking the CNC machining for the spatial barrel-cam with rectilinear translating and a conical roller follower as an example, the calculation method and the law of the profile error influenced by the tool error is given.

User Profile & Attitude Analysis Based on Unstructured Social Media and Online Activity

As social media and online activity continue to pervade all age groups, it serves as a crucial platform for sharing personal experiences and opinions as well as information about attitudes and preferences for certain interests or purchases. This generates a wealth of behavioral data, which, while invaluable to businesses, researchers, policymakers, and the cybersecurity sector, presents significant challenges due to its unstructured nature. Existing tools for analyzing this data often lack the capability to effectively retrieve and process it comprehensively. This paper addresses the need for an advanced analytical tool that ethically and legally collects and analyzes social media data and online activity logs, constructing detailed and structured user profiles. It reviews current solutions, highlights their limitations, and introduces a new approach, the Advanced Social Analyzer (ASAN), that bridges these gaps. The proposed solutions technical aspects, implementation, and evaluation are discussed, with results compared to existing methodologies. The paper concludes by suggesting future research directions to further enhance the utility and effectiveness of social media data analysis.

ABMRF:An Ensemble Model for Author Profiling Based on Stylistic Features Using Roman Urdu

This study explores the area of Author Profiling(AP)and its importance in several industries,including forensics,security,marketing,and education.A key component of AP is the extraction of useful information from text,with an emphasis on the writers’ages and genders.To improve the accuracy of AP tasks,the study develops an ensemble model dubbed ABMRF that combines AdaBoostM1(ABM1)and Random Forest(RF).The work uses an extensive technique that involves textmessage dataset pretreatment,model training,and assessment.To evaluate the effectiveness of several machine learning(ML)algorithms in classifying age and gender,including Composite Hypercube on Random Projection(CHIRP),Decision Trees(J48),Na飗e Bayes(NB),K Nearest Neighbor,AdaboostM1,NB-Updatable,RF,andABMRF,they are compared.The findings demonstrate thatABMRFregularly beats the competition,with a gender classification accuracy of 71.14%and an age classification accuracy of 54.29%,respectively.Additional metrics like precision,recall,F-measure,Matthews Correlation Coefficient(MCC),and accuracy support ABMRF’s outstanding performance in age and gender profiling tasks.This study demonstrates the usefulness of ABMRF as an ensemble model for author profiling and highlights its possible uses in marketing,law enforcement,and education.The results emphasize the effectiveness of ensemble approaches in enhancing author profiling task accuracy,particularly when it comes to age and gender identification.

Modification Design Method for an Enveloping Hourglass Worm Gear with Consideration of Machining and Misalignment Errors

The influences of machining and misalignment errors play a very critical role in the performance of the anti-backlash double-roller enveloping hourglass worm gear(ADEHWG).However,a corresponding efficient method for eliminating or reducing these errors on the tooth profile of the ADEHWG is seldom reported.The gear engagement equation and tooth profile equation for considering six different errors that could arise from the machining and gear misalignment are derived from the theories of differential geometry and gear meshing.Also,the tooth contact analysis(TCA) is used to systematically investigate the influence of the machining and misalignment errors on the contact curves and the tooth profile by means of numerical analysis and three-dimensional solid modeling.The research results show that vertical angular misalignment of the worm wheel(Δβ) has the strongest influences while the tooth angle error(Δα) has the weakest influences on the contact curves and the tooth profile.A novel efficient approach is proposed and used to minimize the effect of the errors in manufacturing by changing the radius of the grinding wheel and the approaching point of contact.The results from the TCA and the experiment demonstrate that this tooth profile design modification method can indeed reduce the machining and misalignment errors.This modification design method is helpful in understanding the manufacturing technology of the ADEHWG.

Profile and Rating Similarity Analysis for Recommendation Systems Using Deep Learning

Recommendation systems are going to be an integral part of any E-Business in near future.As in any other E-business,recommendation systems also play a key role in the travel business where the user has to be recommended with a restaurant that best suits him.In general,the recommendations to a user are made based on similarity that exists between the intended user and the other users.This similarity can be calculated either based on the similarity between the user profiles or the similarity between the ratings made by the users.First phase of this work concentrates on experimentally analyzing both these models and get a deep insight of these models.With the lessons learned from the insights,second phase of the work concentrates on developing a deep learning model.The model does not depend on the other user's profile or rating made by them.The model is tested with a small restaurant dataset and the model can predict whether a user likes the restaurant or not.The model is trained with different users and their rating.The system learns from it and in order to predict whether a new user likes or not a restaurant that he/she has not visited earlier,all the data the trained model needed is the rating made by the same user for different restaurants.The model is deployed in a cloud environment in order to extend it to be more realistic product in future.Result evaluated with dataset,it achieves 74.6%is accurate prediction of results,where as existing techniques achieves only 64%.

Adaptation of feed rate for 3-axis CNC high-speed machining

To improve the efficiency of CNC machining, assumptive transit circular arc is used to contour two adjacent moves together on the comer to make smooth paths. The radios of transit circular arc can be adjusted with contour accuracy, and the feed rate on the corner can be controlled through limiting the maximum feed rate of transit circular arc segment. A look-ahead algorithm for a series of moves is proposed for speed adjustment in advance, which avoids the occurrence of overload of cutting tool on the comer and reduces the servo track error of parts on the corner or of circular arc move. Equivalent trapezoidal velocity profile is used to analyze the speed of S-curve velocity profile and work out its accurate interpolation, which overcomes the disadvantage of looking up table to calculate feed rate approximately, hence high accuracy and fine surface quality can be obtained while the machining speed is high. The proposed methods can meet the requirements of real-time analysis of high-speed machining. The presented algorithm is effective and has been adopted by CNC system of newly developed high-speed milling machine.

HSP超前探测技术在煤矿TBM掘进巷道中的应用研究

随着全断面掘进机TBM(Tunnel Boring Machine)逐渐应用于煤矿岩巷掘进,对不良地质构造进行超前准确快速预测的需求日益迫切。通过对主动源地震波超前探测方法的特点和TBM破岩震源超前探测技术的适用性进行分析,结合煤矿巷道地质和生产条件,提出了适用于煤矿巷道TBM掘进的HSP超前探测方法。以河南平顶山首山一矿TBM掘进底板瓦斯治理巷道为工程背景,选用防爆硬件一体化设计的探测仪器在煤矿巷道中进行应用。构建了空间型观测方式对煤矿巷道近水平煤线进行探测,优化了双护盾TBM掘进巷道狭小空间检波器阵列式布置参数;基于时频分析、互相关干涉处理、反射与散射联合反演等方法处理原始信号并进行探测结果成像。研究表明:采用空间型观测方式可实现与巷道小角度斜交煤线的识别,设计震源与首检波器间距离为15 m时最优。通过时频分析提取有效信号,利用互相关干涉法获取虚拟震源道和反射特征曲线,并结合反射与散射联合反演成像得到探测区域地层反射能量分布图,能够较准确地推测得到围岩存在的不良地质构造。通过比较现场开挖揭露情况与探测结果发现两者吻合度较高,表明HSP超前探测方法可实现掘进工作面前方100 m范围内超前无损地质预测,有助于提高煤矿岩巷TBM掘进速度。

基于GA-SVM的钢轨廓形类型在线识别算法研究

针对轨道交通日常运维中钢轨廓形自动化检测识别率不高的情况,提出了一种基于几何描述符和支持向量机(SVM)的高精度钢轨廓形在线识别算法。利用结构光传感器对钢轨廓形数据进行采集,采用几何去噪算法对廓形进行离群点剔除和重采样预处理。通过廓形几何描述符对不同类别钢轨廓形进行特征提取,制作廓形特征数据集用于训练SVM。采用遗传算法(GA)对SVM模型参数进行优化选取。将优化训练后的SVM模型用于钢轨廓形检测并和传统廓形识别方法进行对比。结果表明:提出的采用几何描述符的GA-SVM模型平均准确率达到99.62%,单帧廓形识别用时6.43 ms,能有效提升廓形识别准确率与高速性,满足轨道车辆在线检测的需求,并为轨道自动化检测提供了理论和技术支撑。

基于MI特征选择的车辆能耗高精度预测方法

近年来,机器学习方法在车辆实时能耗预测方面得到了广泛应用,但实车采集数据中存在的精度不足、字段缺失以及多重共线性等问题,尤其是同款车型中驾驶工况和驾驶者行为存在显著差异,限制了能耗预测准确性和泛化能力的进一步提升。为此,本文系统考虑特征冗余度、数据平衡性、货运趟次、运输能力、路段拥挤程度和司机驾驶时长等因素,使用交互信息(MI)方法选择关键特征,并构建司机特征画像作为独立特征,进而结合XGBoost、RF和MLP等机器学习方法提出一种基于MI特征选择的能耗高精度预测方法,然后基于120辆轻型卡车的T-BOX采集数据进行实例验证。结果表明,本文提出的预测方法能够显著提高不同驾驶行为和驾驶工况下的能耗预测精度,研究成果可为开发预测轻卡能耗的通用模型提供参考。

考虑加工误差及多工况影响的压气机叶型鲁棒性优化

针对压气机叶型在宽攻角宽马赫数范围内低损失工作、叶型性能对加工误差不敏感的工程需求,首先,建立了考虑加工误差及几何参数的叶型优化流程;然后,以某压气机静子叶型为研究对象,基于构建的代理模型,在设计马赫数0.87(跨音流动)与低马赫数0.7(亚音流动)下开展了考虑加工误差及多攻角工况影响的压气机叶型鲁棒性优化设计研究。结果表明:针对跨音流动工况优化获得的叶型,其设计马赫数攻角特性大幅改善,但亚音流动工况下的攻角特性略微恶化;针对亚音流动工况优化获得的叶型,其攻角特性在多个低马赫数工况下大幅改善,在跨音流动工况下恶化。

同位素注入剖面测井解释智能化批量处理技术的实现与应用

同位素注入剖面测井是水驱油田了解各小层吸水状况的主要监测手段,该测井方法在中国油田的年测井工作量在3万井次左右,在注水油藏动态监测中占主导地位。传统的同位素注水剖面测井结果依赖人工解释,工作效率低、工作量大且多解性强,容易受到不同分析员人为因素影响,已经无法满足日益增长的生产需求。运用大数据监测和机器学习等技术,解决了基础数据录入、原始数据解编、深度匹配、工具识别、曲线叠合、综合评价等关键环节技术难题,形成了智能化批量处理技术。通过在CIFLog测井解释平台上的集成运行,单井处理时间从30~60min缩短到30s,人工干预率低于12%,验证了该处理流程及算法的有效性。