Sharif Digital Repository

In high speed machining, friction between the moving parts, generates heat. One of the major causes of thermal errors in linear axes is the heat generated in ball screw during operation at high speed. Thermal errors affect the accuracy of the linear axes and can cause a deviation from the nominal machining circular motion. The subject of this paper is to study the effects of feed velocity and ball screw Preload on the accuracy of circular motion. The temperature rise in the ball screw is measured by a laser thermometer. The errors in the linear and circular motions are measured by laser interferometer and ball bar. Training a neural network by the test results, thermal errors in all parts of... 

Parallel corpora are the necessary resources in many multilingual natural language processing applications, including machine translation and cross-lingual information retrieval. Manual preparation of a large scale parallel corpus is a very time consuming and costly procedure. In this paper, the work towards building a sentence-level aligned English-Persian corpus in a semi-automated manner is presented. The design of the corpus, collection, and alignment process of the sentences is described. Two statistical similarity measures were used to find the similarities of sentence pairs. To verify the alignment process automatically, Google Translator was used. The corpus is based on news... 

In process planning, determining feature's machining precedence is an essential step. The task becomes more difficult if features interact with each other, in which case the feature precedence information may suggest multiple machining sequences of the features. This paper considers interacting features in a feature-based model for process planning tasks. For each feature, precedence information is generated considering both roughing and finishing operations. A rule-based system is developed and implemented based on the information about machining precedence of the interacting features. The STEP-NC data model is used as the underlying data model. This model is object-oriented and compliant... 

This article contributes a torque control based on hysteresis for Brushless Doubly Fed Induction Machine (BDFM) through machine analysis and extracting the d-q parameters that influence on the machine behavior. In this research, a Direct Torque Control (DTC) based on stator flux-oriented vectors and machine's relation and equations with voltage and current of both stators have been introduced. The control for the BDFM is implemented by a voltage source inverter connected to the second stator as a torque controller that uses the classical field-oriented control method widely used in voltage sector selection. Finally BDFM as a closed loop model with DTC is simulated and evaluated  

This article contributes a torque control based on hysteresis for Brushless Doubly Fed Induction Machine (BDFM) through machine analysis and extracting the d-q parameters that influence on the machine behavior. In this research, a Direct Torque Control (DTC) based on stator flux-oriented vectors and machine's relation and equations with voltage and current of both stators have been introduced. The control for the BDFM is implemented by a voltage source inverter connected to the second stator as a torque controller that uses the classical field-oriented control method widely used in voltage sector selection. Finally BDFM as closed loop model with DTC is simulated and evaluated  

Laser assisted machining (LAM) is a promising technology for machining hard to cut materials. In most experimental cases, LAM is undergone in two stages; first, the temperature at the material removal point (Tmr) is tuned by adjusting laser parameters and next, the cutting tool is engaged. Introduction of highly localized heat energy to the workpiece makes the modeling of this process very complicated. Hence, an analytical model for the first stage of the process - rather than multiple experiments or FE modelling - would be beneficial. This article presents an analytical solution to the transient, temperature field in a rotating cylinder subject to a localized laser heat source. The... 

A robust target recognition method proposed based on recurrence plot and recurrence quantification analysis (RQA) to generate robust features against noise, target velocity and aspect angle from micro-Doppler (m-D) signatures. The proposed method is tested on simulated data of three different targets using multiclass support vector machine (MSVM) and classification rate of about 95 % is achieved. Also, effect of noise and coherent processing time (CPT) on classification rate is investigated  

This study introduces a new identifier for nuclear power plants (NPPs) transients. The proposed identifier performs its function in two steps. First, the transient is identified by the previously developed supervised classifier combining ARIMA model and EBP algorithm. In the second step, the patterns of unknown transients are fed to the identifier based on the semi-supervised learning (SSL). The transductive support vector machine (TSVM) as a semi-supervised algorithm is trained by the labeled data of transients to predict some unlabeled data. The labeled and newly predicted data is then used to train the TSVM for another portion of unlabeled data. Training and prediction is continued until... 

The dynamic nature of today’s manufacturing industry, which is caused by the intense global competition and constant technological advancements, requires systems that are highly adaptive and responsive to demand fluctuations. Reconfigurable manufacturing systems (RMS) enable such responsiveness through their main characteristics. This paper addresses the problem of RMS configuration design, where the demand of a single product varies throughout its production life cycle, and the system configuration must change accordingly to satisfy the required demand with minimum cost. A two-phased method is developed to handle the primary system configuration design and the necessary system... 

This paper proposes a new method to detect and classify all kinds of faults, capacitor switching, and load switching in a power system network based on wavelet transform and support vector machines (SVMs). In this regard, a sample of a power system is simulated via MATLAB/Simulink, and by reading the voltage of the point of common coupling and using the wavelet transform, the differences of the outputs of the wavelet transform are investigated. The SVM approach is employed to distinguish the type of the transient (capacitor switching, fault, and/or load switching) in use for the high level outputs of the wavelet transform. Similar to neural networks, this method, which is based on learning,... 

In this paper, we propose a method for steganalysis of grayscale images using both spatial and Gabor features. The basis of our work is to use Gabor filter coefficients and statistics of the graylevel co-occurrence matrix of images to train a support vector machine. We show that this feature set works well in steganalysis of grayscale images steganographied by LSB matching and S-tools. ©2009 IEEE  

The efficiency of a learning process directly depends on how well the students are attentive. Detecting the level of attention can help to improve the learning quality. In recent years, there have been several attempts to leverage EEG signal processing as a tool to detect whether a student is attentive or not. In such work, the level of attention is determined by analyzing the EEG power spectrum, which is mostly followed by machine learning approaches. However, the efficiency of such methods for detecting auditory attention of blind or visually-impaired students has not been analyzed. This study aims to investigate such a scenario. To this end, we propose an EEG recording protocol to... 

The desired milling process with high material removal rate (MRR) and low surface roughness of the product can be achieved only if machining chatter is absent. Incorporating chatter into the optimal selection of the machining parameters leads to a complex problem. Therefore, the approach of selecting conservative intervals for the machining parameters is usually employed instead. In this paper, a practical approach is proposed to specify the optimal machining parameters (depth of cut and spindle speed) in order to maximize MRR and minimize forced vibrations by considering machining chatter. Firstly, the worst-case scenario-based optimization problem in terms of the surface quality is solved... 

In this paper, a new and simple control method based on Direct Torque Control (DTC) of induction motors is proposed for a multi-machine system. Similar to a conventional DTC, the proposed method has two separate control loops. In the torque control loop, before selection of optimum voltage from the DTC look-up table, the system overall requirement is determined based on requirements of motors torque. Also, Switchable Master-Slave control is used in the flux control loop. The method, which is simulated for a two-parallel induction machine system, can be extended to a multi-machine system. Simulation results are also provided to investigate the performance of the proposed technique. © 2008... 

Fake news detection has become an emerging and critical topic of research in recent years. One of the major complications of fake news detection lies in the fact that news in social networks is multilingual, and therefore developing methods for each and every language in the world is impossible, especially for low resource languages like Persian. In an effort to solve this problem, researchers use machine translation to uniform the data and develop a method for the uniformed data. In this paper, we aim to explore the impacts of machine translation on fake news detection. For this purpose, we extracted and labeled a dataset of Persian Tweets from Twitter on the subject of COVID-19 and...