摘要：In view of huge search space in drug design, machine learning has become a powerful method to predict the affinity between small molecular drug and targeting protein with the development of artificial intelligence technology. However, various machine learning algorithms including massive different parameters make the prediction framework choice to be quite difficult. In this work, we took a recent drug design competition(from XtalPi company on the DataCastle platform) as the typical case to find the optimized parameters for different machines learning algorithms and the most effective algorithm. After the parameter optimizations, we compared the typical machine learning methods as decision tree(XGBoost, LightGBM) and artificial neural network(MLP, CNN) with root-mean-square error(RMSE) and coefficient of determination(R^2) evaluation. As a result, decision tree is more effective than the neural network as LightGBM>XGBoost>CNN>MLP in the affinity prediction of the specific drug design problem with ～160000 samples. For a much larger screening task in a more complicated drug design study, the sophisticated neural network model may go beyond the decision tree algorithm after generalization enhancing and overfitting reducing. The advanced machine learning methods could extract more information of protein-ligand bindings than traditional ones and improve the screen efficiency of drug design up to 200–1000 times.

摘要：Floorplan is an important process whose quality determines the timing closure in integrated circuit(IC)physical *** generating a floorplan with satisfying timing result is time-consuming because much time is spent on the generation-evaluation *** machine learning to the floorplan stage is a potential method to accelerate the floorplan ***,there exist two challenges which are selecting proper features and achieving a satisfying model *** this paper,we propose a machine learning framework for floorplan acceleration with feature selection and model stacking to cope with the challenges,targeting to reduce time and effort in integrated circuit physical ***,the proposed framework supports predicting post-route slack of static random-access memory(SRAM)in the early floorplan ***,we introduce a feature selection method to rank and select important *** both feature importance and model accuracy,we reduce the number of features from 27 to 15(44%reduction),which can simplify the dataset and help educate novice ***,we build a stacking model by combining different kinds of models to improve *** 28 nm technology,we achieve the mean absolute error of slacks less than 23.03 ps and effectively accelerate the floorplan process by reducing evaluation time from 8 hours to less than 60 *** on our proposed framework,we can do design space exploration for thousands of locations of SRAM instances in few seconds,much more quickly than the traditional *** practical application,we improve the slacks of SRAMs more than 75.5 ps(177%improvement)on average than the initial design.

摘要：We studied the reliability of machine components with parameters that follow an arbitrary statistical distribution using the principle of maximum entropy(PME).We used PME to select the statistical distribution that best fits the available *** also established a probability density function(PDF)and a failure probability model for the parameters of mechanical components using the concept of entropy and the *** obtained the first four moments of the state function for reliability analysis and ***,we attained an estimate of the PDF with the fewest human bias factors using the *** function was used to calculate the reliability of the machine components,including a connecting rod,a vehicle half-shaft,a front axle,a rear axle housing,and a leaf spring,which have parameters that typically follow a non-normal *** were conducted for *** study provides a design methodology for the reliability of mechanical components for practical engineering projects.

摘要：The structure and the production process for flying shear machine are introduced ***,a quintic polynomial is applied to the design of an electronic cam system for the rotary knife axis in short materials *** dimensionless equation for a quintic polynomial cam curve is ***,the curve is plotted with the cam constructor integrated into Siemens engineering development software SCOUT and it is tested with a laboratory platform,which consists of a motion controller SIMOTION and motor drivers SINAMICS *** results show that the running stability of the flying shear machine and the position control accuracy of the rotary knife can be effectively improved by using the curve designed in this paper.

摘要：A compound machine tool was designed, which combined rotary ultrasonic assisted grinding, electrical discharge machining(EDM) and multi-axis milling. Experimental results indicated that its positioning accuracy was less than 5.6 μm and its repetitive positioning accuracy was less than 1.8 μm; the vibration amplitude of ultrasonic grinding system was uniform and stable, and the EDM system worked well and stably.A smooth surface of K9 optical glass component was achieved by the grinding method.

摘要：运用这个完整版machine

摘要：本月我们收集了一整套软件和资源的精选。除了Mister Retro的machine Wash Photoshop的五组滤镜外（见光盘教程）,你还可以找到Eovia的3D多边形建模工具Hexagon。

摘要：this paper overall programme research on virtual design technology of machine tools, not only established a virtual design environment, identify reasonable options in a relatively short period of time, but also providing the basis for quotation, therefore reflecting a favourable measures quickly to market demand.

摘要：This paper presents a systematic approach of optimal design and control of a surface-mount, permanent-magnet synchronous torque motor for the next-generation machine tools. A step-by-step procedure of optimization integrates multiple performance objectives and constraints to help the designer make the best decision on the final motor geometry from both design and control perspectives. In the perspective of design, a torque motor with concentrated windings and similar numbers of slots and poles may achieve the desired performance after optimization for multiple objectives, leading to a sinusoidal flux density for a nearly ripple-free torque distribution. From the control perspective, an optimal current waveform with an ideal shift angle is determined for each phase by aligning the current excitation with the back electromotive force. Both design and control of the surface-mount, permanent magnet machine are verified by the finite element method, and a prototype is fabricated for performance validation.

摘要：This paper presents a new Omni-Directional Tilt Sensor (ODTS), which consists of the LED light, transparent cone-shaped closed container, mercury, camera, embedded systems and so on. The volume of the mercury in the container is equal to half of the container’s. When the detected surface is horizontal, the shape of mercury in the image captured by the camera is a black disc since the mercury is lightproof. When the detected surface tilts, the mercury flows and the mercury surface always maintains horizontally due to the gravity force of the earth. At this time, some area of the transparent cone-shaped closed container is not shaded by mercury and the border of the mercury’s shape in the captured image is a half circle and a half ellipse. Thus there is a translucent crescent-shaped area in the image. With analyzing this area by the specific algorithm based on machine vision, the tilt angle and directional angle can be obtained. The experimental results show that the ODTS proposed has some advantages, such as simple maintenance, high precision, wide range, low cost, real-time, reliability and high visualization.