Research on A Master - slave Multi - microcomputers Control System for Hollow Spindle Fancy Yarn Spinning Machine

In this paper, a successfully studied and developed master - slave muld - microcomputers control system based on PC - BUS for hollow spindle fancy yarn spinning machine, mainly Its overall scheme, software and hardware construction, is introduced. Spinning experiments show that the system achieves satisfactory result. This system can solve the diftkultles of mechatronical fusion between domestic hollow splndk fancy yarn spuming muchine and its microcomputer control technology.

DK7732-1 Electric Spark CNC Wire-Cuffing Machine

The machine tool is one of the new products developed and produced by the Shanghai No.8 Machine Tool Plant. It adopts a lift adjustable wiretrame and molybdenum filament tensioning mechanism with large cutting thickness and high machining precision. It is equipped with an advanced IBM-PC 386 microcomputer-controlled system, with strong performance and CRT display. Man/

Comprehensive Overview on Computational Intelligence Techniques for Machinery Condition Monitoring and Fault Diagnosis

Computational intelligence is one of the most powerful data processing tools to solve complex nonlinear problems, and thus plays a significant role in intelligent fault diagnosis and prediction. However, only few com- prehensive reviews have summarized the ongoing efforts of computational intelligence in machinery condition moni- toring and fault diagnosis. The recent research and devel- opment of computational intelligence techniques in fault diagnosis, prediction and optimal sensor placement are reviewed. The advantages and limitations of computational intelligence techniques in practical applications are dis- cussed. The characteristics of different algorithms are compared, and application situations of these methods are summarized. Computational intelligence methods need to be further studied in deep understanding algorithm mech- anism, improving algorithm efficiency and enhancing engineering application. This review may be considered as a useful guidance for researchers in selecting a suit- able method for a specific situation and pointing out potential research directions.

Plasma microRNA-15a/16-1-based machine learning for early detection of hepatitis B virus-related hepatocellular carcinoma

Background and aims:Hepatocellular carcinoma(HCC),which is prevalent worldwide and has a high mortality rate,needs to be effectively diagnosed.We aimed to evaluate the significance of plasma microRNA-15a/16-1(miR-15a/16)as a biomarker of hepatitis B virus-related HCC(HBV-HCC)using the machine learning model.This study was the first large-scale investigation of these two miRNAs in HCC plasma samples.Methods:Using quantitative polymerase chain reaction,we measured the plasma miR-15a/16 levels in a total of 766 participants,including 74 healthy controls,335 with chronic hepatitis B(CHB),47 with compensated liver cirrhosis,and 310 with HBV-HCC.The diagnostic performance of miR-15a/16 was examined using a machine learning model and compared with that of alpha-fetoprotein(AFP).Lastly,to validate the diagnostic efficiency of miR-15a/16,we performed pseudotemporal sorting of the samples to simulate progression from CHB to HCC.Results:Plasma miR-15a/16 was significantly decreased in HCC than in all control groups(P<0.05 for all).In the training cohort,the area under the receiver operating characteristic curve(AUC),sensitivity,and average precision(AP)for the detection of HCC were higher for miR-15a(AUC=0.80,67.3%,AP=0.80)and miR-16(AUC=0.83,79.0%,AP=0.83)than for AFP(AUC=0.74,61.7%,AP=0.72).Combining miR-15a/16 with AFP increased the AUC to 0.86(sensitivity 85.9%)and the AP to 0.85 and was significantly superior to the other markers in this study(P<0.05 for all),as further demonstrated by the detection error tradeoff curves.Moreover,miR-15a/16 impressively showed potent diagnostic power in early-stage,small-tumor,and AFP-negative HCC.A validation cohort confirmed these results.Lastly,the simulated follow-up of patients further validated the diagnostic efficiency of miR-15a/16.Conclusions:We developed and validated a plasma miR-15a/16-based machine learning model,which exhibited better diagnostic performance for the early diagnosis of HCC compared to that of AFP.

Verifying the accuracy of interlocking tables for railway signalling systems using abstract state machines

Railway transportation system is a critical sector where design methods and techniques are defined by international standards in order to reduce possible risks to an acceptable minimum level. CENELEC 50128 strongly recommends the utilization of finite state machines during system modelling stage and formal proof methods during the verifi- cation and testing stages of control algorithms. Due to the high importance of interlocking table at the design state of a sig- nalization system, the modelling and verification of inter- locking tables are examined in this work. For this purpose, abstract state machines are used as a modelling tool. The developed models have been performed in a generalized structure such that the model control can be done automatically for the interlocking systems. In this study, NuSMV is used at the verification state. Also, the consistency of the developed models has been supervised through fault injection. The developed models and software components are applied on a real railway station operated by Metro Istanbul Co.

Real-time crash prediction on freeways using data mining and emerging techniques

Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.

Optimization Design for Fixed Table of Gantry Machining Center Based on Sensitivity and Topology Analyses

In order to decrease the deformation and stress and increase the natural frequency of the fixed table,a method of optimization driven by the sensitivity and topology analyses is proposed.The finite element model of the fixed table is constructed and analyzed by using ANSYS software.Based on the results of static analysis and modal analysis,the maximum deformation,the maximum stress,and natural frequencies are obtained.Then,the sensitivity analysis and topology optimization are carried out to find out the parameters to be optimized.The fixed table is reconstructed according to optimal design scheme.In the comparison of the results between original model and the optimized one,the maximum deformation and stress are decreased by 71.73%and 60.27%respectively.At the same time,the natural frequencies from the first mode to the sixth mode are increased by 30.28%,29.57%,29.51%,31.52%,22.19%,and 21.80%,respectively.The method can provide technology guide for the design and optimization of machining structure.

Ionic liquids inhibit the dynamic transition fromα-helices toβ-sheets in peptides

Abnormalities in the transition betweenα-helices andβ-sheets(α-βtransition)may lead to devastating neurodegenerative diseases,such as Parkinson's syndrome and Alzheimer's disease.Ionic liquids(ILs)are potential drugs for targeted therapies against these diseases because of their excellent bioactivity and designability of ILs.However,the mechanism through which ILs regulate the aα-βtransition remains unclear.Herein,a combination of GPU-accelerated microsecond molecular dynamics simulations,correlation analysis,and machine learning was used to probe the dynamicalα-βtransition process induced by ILs of 1-alkyl-3-methylimidazolium chloride([C_(n)mim]cl)and its molecular mechanism.Interestingly,the cation of [C_(n)mim]+in ILs can spontaneously insert into the peptides as free ions(n≤10)and clusters(n≥11).Such insertion can significantly inhibit theα-β,transition and the inhibiting ability for the clusters is more significant than that of free ions,where[Ciomim]+and[C_(12)mim]+can reduce the maximumβ-sheet content of the peptide by 18.5% and 44.9%,respectively.Furthermore,the correlation analysis and machine learning method were used to develop a predictive model accounting for the influencing factors on theα-βtransition,which could accurately predict the effect of ILs on theα-βtransition.Overall,these quantitative results may not only deepen the understanding of the role of ILs in theα-βtransition but also guide the development of the IL-based treatments for related diseases.

药渣机制炭特性参数对其市场影响的研究

药渣机制炭是采用中药渣及农林废弃物经粉碎以适当比例混合后,再经脱水(含水量≤7%)、挤压成炭坯,在无氧条件下制成的,根据经销商对其质量的要求,选择水分、灰分、挥发分、热值、抗碎强度、抗压强度及破碎率为质量控制参数进行测定,拟为机制炭生产方提高产品质量提供参考。结果表明,这些参数可为药渣机制炭的销售发挥重要作用,只要能达到一定的标准,产品即可具备较强的市场竞争力,取得更好的经济效益。

一种新型管道内环缝自动清渣机的设计及应用

为了清除长输管道内环缝上存留焊渣、药皮及其他脏物,设计了一种新型管道内环缝自动清渣机。该清渣机的机械部分由差动式双向打磨系统、渣尘回收系统、防倾斜整机驱动行走系统、自动收放线系统组成;控制部分由电源、电路、控制芯片和控制软件组成。文章介绍了主要结构的原理及技术特点。该清渣机的样机已进行了模拟现场中试,结果表明,打磨速度快,渣尘回收彻底,操作简单可靠。

动物蛋白源螺旋霉素药渣干燥的降耗工艺研究

简述了作为可利用动物蛋白饲料源之一的螺旋霉素药渣的挤水和干燥工艺以及设备现状,提出了一种在开发出新挤压设备基础上的降耗干燥新工艺,对该工艺的研究、试验和应用进行了较详尽的叙述和分析,还通过实测数据说明了本工艺的优势所在.并对新设计的药渣挤水机设备设计要点进行了简述.

Machining of circular micro holes by electrochemical micro-machining process

Machining of micro holes with micro electro- chemical machining （micro ECM） process has been carried out with an indigenously developed set up. This paper describes relevant problems and solutions for the circular micro holes machining process on 304 stainless steel sheets with 60 μm thickness using high speed steel cylindrical tool of diameter 500 ~tm and using dilute I-I2SO4 as elec- trolyte. The taper angle variation of the machined hole is analyzed and reported for different experimental setting parameters. The minimum value of the taper angle of machined holes is achieved at the parameter setting of 0.4 mol/L H2504, 700 kHz, 600 ns and 21 V, for stainless steel sheets and HSS tool.

油泥处理机滚动清洗装置的结构设计

落地油泥通过油泥处理机滚动清洗装置将大的石块及大的废物经出料口落到除渣机中排除,将小的泥沙废物经过洗油槽沉淀到除渣机中排除;原油经过溢流管进入到储油槽内,再经过油水分离机提炼。该工艺先进,结构简单,既解决环保问题又创造经济效益。

铬渣在济钢120m^2烧结机生产上的应用

介绍济钢120m2烧结机消化济南裕兴化工厂含Cr6+铬渣的生产情况,重点是使用铬渣进行的工艺改造和效果,达到消化铬渣的同时不产生二次污染,即消除污染,又造福社会。

燃煤电厂风冷式干渣机排渣系统的环保与节能

灰渣处理是燃煤电厂运行的重要环节,随着燃煤电厂规模的不断扩大,以及不断提升的环保和节能要求,灰渣处理也发生了变革,传统的水力除灰排渣逐渐被工作效率更高、自动化程度更高、更环保、更节能的风冷式干渣机排渣系统和湿式刮板捞渣机排渣系统所取代,使环境污染也得到了更好地解决。

11C01型扒渣机大臂歪斜问题的分析

鄂钢转炉炼钢厂脱硫用11C01开型扒渣机自投入使用以来,多次发生扒渣机大臂歪斜的现象,影响其正常扒渣。笔者经过数月的摸索分析,找出大臂歪斜的主要原因,提出了改进方案及防范措施,有效提高了扒渣机的使用效率,降低扒渣机大臂的非正常消耗,为转炉厂的正常生产提供了有力保证。

循环流化床锅炉的节能改造

本文针对循环流化床锅炉在设计、结构及安装上存在的一些问题进行了技术改造,取得了较好的节能效果。

融合多特征的异源视频复制-粘贴篡改检测

相比传统的视频帧插入或帧删除以及视频双压缩等篡改方式,复制-粘贴篡改更能直接的改变视频内容。因此,本研究提出一种融合多特征的异源视频复制-粘贴篡改检测方法。对于经过帧内复制-粘贴篡改的视频,其视频帧内会引入一些尖锐的变化,比如线条、边缘和角点等,而二维相位一致性可以很好的检测出这些变化。同时,来自异源视频帧复制的区域块会使得帧内引入不同的模式噪声,可以利用模式噪声和二维相位一致性提取视频帧的特征,然后将特征融合进行SVM分类实验来检测篡改视频。实验表明该算法可以有效地检测异源复制-粘贴篡改的视频。

An Improved vTPM-VM Live Migration Protocol

To prevent malicious virtual machine from harming the security of vTPM-VM live migration process, we propose an im- proved vTPM-VM live migration protocol which uses a TPM-based integrity verification policy and a specific encryption scheme to enhance security. The TPM-based integrity verification policy is presented to ensure that all participating entities in this process are trustworthy. In data transfer phase, the specific encryp- tion scheme is designed to associate the decipher process with one certain platform status so that only the destination platform can gain the key data of the migrated VM and vTPM instance. The security of this new protocol is analyzed. The results show that this protocol can effectively resist most of the attacks in the proc- ess ofvTPM-VM live migration.

Experimental investigation of tool wear and chip formation in cryogenic machining of titanium alloys

Titanium alloys are one of the most important design materials for the aircraft industry. The high strength-to-density-ratio and the compatibility with carbon fibre reinforced plastic are the reasons for a raising application in this field. The outstanding properties lead to challenging machining processes. High strength and low heat conductivity affect high mechanical and thermal loads for the cutting edge. Thus, the machining process is characterized by a rapid development of tool wear even at low cutting parameter. To reach a sufficient productivity it is necessary to dissipate the resulting heat from the cutting edge by a coolant. Therefore the cryogenic machining of two different titanium alloys is investigated in this work. The results point out the different behavior of the machining processes under cryogenic conditions because of the reduced thermal load for the cutting tool. According to this investigation, the cryogenic cooling with COa enables an increase of the tool life in comparison to emulsion based cooling principles when machining the α＋β-titanium alloy Ti-6Al-4V. The machining process of the high strength titanium alloy Ti-6Al-2Sn-4Zr-6Mo requires an additional lubrication realized by a minimum quantity lubrication （MQL） with oil. This combined cool- ing leads to a smoother chip underside and to slender shear bands between the different chip segments.