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International eConference on Computer and Knowledge Engineering (ICCKE)

作者： Moein Owhadi-Kareshk Mohammad-R. Akbarzadeh-T Center of Excellence on Soft Computing and Intelligent Information Processing (SCIIP) Ferdowsi University of Mashhad (FUM) Mashhad Iran Center of Excellence on Soft Computing and Intelligent Information Processing (SCIIP) Ferdowsi University of Mashhad Mashhad Razavi Khorasan IR

Representation learning is a fast growing approach in machine learning that aims to improve the quality of the input data, instead of insisting on designing complex subsequent learning algorithms. In this paper, we propose to use Denoising AutoEncoders (DAEs), as one of the most effective representation learning methods, in Clustering-based Classification (CC). CC is a multi-class classification solution for large-scale and complicated data sets. In this approach, data are divided into small and simple clusters, which are described by One-Class Classifiers (OCCs). In the proposed Representation Learning for Clustering-based Classification (RLCC), the new representation of each cluster is generated locally to increase the performance of OCCs in term of accuracy. This method still preserves the scalability property as one of the significant advantages of CC methods. RLCC is evaluated with six different data sets from UCI. The results of the experiments show that RLCC has higher generalization power compared to the standard version of CC.

关键词： Glass Heart Iris Sonar Supervised learning Particle separators Testing

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Estimation biting force based using EMG signals and Laguerre estimation technique

Estimation biting force based using EMG signals and Laguerre...

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Iranian Conference on Electrical Engineering (ICEE)

作者： Nazanin Goharian Sahar Moghimi Hadi Kalani Electrical Engineering Dept Ferdowsi University of Mashhad Mashhad Iran Electrical Engineering Dept Center of Excellence on Soft Computing and Intelligent Information Processing Mashhad Iran Mechanical Engineering Dept Center of Excellence on Soft Computing and Intelligent Information Processing Mashhad Iran

Biting force varies based on type of food that is being chewed. To study human mastication comprehensively, it is better to consider the electromyography (EMG) activity of the masticatory muscles and bite force. The aim of this study is to evaluate SEMG-force relationship by utilizing Laguerre expansion technique (LET). In this work, the electrical activity of only two masticatory muscles, namely masseter and temporalis are measured. Results denote the ability of LET in predicting mastication biting force based on EMG signals. Additionally, the proposed model can be able to control masticatory robots using recorded EMG signals. In these applications, uses of non-expensive and portable of electromyography (EMG) electrodes have advantageous compared to the use of force sensors and cameras which are often very expensive and require massive structures.

关键词： Decision support systems Electrical engineering Force Q measurement Force measurement Time measurement

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Probabilistic fuzzy systems, expressions and approaches

Probabilistic fuzzy systems, expressions and approaches

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Iranian Joint Congress on Fuzzy and intelligent Systems (CFIS)

作者： Mohammad-R. Akbarzadeh-T Alireza Bemani-N Department of Electrical Engineering Ferdowsi University Center of Excellence on Soft Computing and Intelligent Information processing Mashhad Iran

In this paper, we aim to provide an overall perspective to the various expressions and approaches regarding probabilistic fuzzy systems. We begin with providing an introduction to the different kinds of uncertainties and associated tools that address them. A general description about the principle of modelling in stochastic environments is then represented. Two different expressions on probabilistic fuzzy sets are subsequently discussed. Moreover three distinct probabilistic fuzzy approaches facing stochastic problems are described and the ad-vantages and disadvantages related to each approach are also illustrated. Several simulations and comparative analysis are also provided to clarify the mentioned concepts.

关键词： Probabilistic logic Uncertainty Fuzzy systems Fuzzy sets Stochastic processes Manganese

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Gyrostabilized Two Wheeled Inverted Pendulum Robot

Gyrostabilized Two Wheeled Inverted Pendulum Robot

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RSI/ISM International Conference on Robotics and Mechatronics

作者： Ali Mahvan Alireza Akbarzadeh Center of Excellence on Soft Computing and Intelligent Information Processing Mechanical Engineering Department Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9781467372350

The increase in air pollution has motivated the design of many electrical transportation systems. In this paper, a "two wheeled inverted pendulum" personal transporter is considered. This system is inherently unstable and requires precise torque control of the two motor wheels to maintain its balance. To assist the control system, a mechanical controller or a "gyrostabilizer" is added to this robot. It is shown that the overall system stability is improved.

关键词： two wheeled inverted pendulum equations of motion gyrostabilizer Euler's equations rigid body dynamics

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A framework for analysis of extended fuzzy logic

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Journal of Zhejiang University-Science C(Computers and Electronics) 2014年第7期15卷 584-591页

作者： Farnaz SABAHI M.-R.AKBARZADEH-T Center of Excellence on Soft Computing and Intelligent Information Processing Department of Electrical EngineeringFerdowsi University of Mashhad

We address a framework for the analysis of extended fuzzy logic(FLe) and elaborate mainly the key characteris-tics of FLe by proving several qualification theorems and proposing a new mathematical tool named the A-granule. Specifically, we reveal that within FLe a solution in the presence of incomplete information approaches the one gained by complete infor-mation. It is also proved that the answers and their validities have a structural isomorphism within the same context. This rela-tionship is then used to prove the representation theorem that addresses the rationality of FLe-based reasoning. As a conse-quence of the developed theoretical description of FLe, we assert that in order to solve a problem, having complete information is not a critical need; however, with more information, the answers achieved become more specific. Furthermore, reasoning based on FLe has the advantage of being computationally less expensive in the analysis of a given problem and is faster.

关键词： Extended fuzzy logic Fuzzy logic f-Transformation S-answer Validity

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WS-TWSVM: Weighted Structural Twin Support Vector Machine by local and global information

WS-TWSVM: Weighted Structural Twin Support Vector Machine by...

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International eConference on Computer and Knowledge Engineering (ICCKE)

作者： Ramin Rezvani-KhorashadiZadeh Monsefi Reza Computer Department Ferdowsi University of Mashhad (FUM) Mashhad Iran Center of Excellence on Soft Computing and Intelligent Information Processing (SCIIP)

Recently many researches have published their papers on training a classifier based on the structural information of data. A Structural Twin Support Vector Machine (S-TWSVM) was proposed to introduce and balance all structural information of both intra-class and inter-class into its optimization problems. In fact, this method neither consider the structural information conflicting between clusters of one class nor the noise data points that can influence on the structure of the data distribution. In this paper, we propose a new Weighted Structural Twin Support Vector Machine (WS-TWSVM) by its local and global information. In our proposed method, we use a weighted (rather than a simple) summing of structural information to sufficiently exploit class's distribution information, so that, applying the density information of data points, the effects of the noise points on the data structure can be handled. Thus, our proposed method, WS-TWSVM can fully exploit the prior knowledge more efficiently than S-TWSVM leads to improve the model's generalization capacity. As been shown in the experiments, WS-TWSVM is superior to S-TWSVM in term of classification accuracy.

关键词： Data mining Lead Bismuth Ionosphere

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Design and Construction of a Linear-Rotary Joint for Robotics Applications

Design and Construction of a Linear-Rotary Joint for Robotic...

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RSI/ISM International Conference on Robotics and Mechatronics

作者： Ali Mousavi Alireza Akbarzadeh Morteza Shariatee Salman Alimardani Center of Excellence on Soft Computing and Intelligent Information Processing (SCIIP) Mechanical Engineering Department Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9781467372350

In this paper the mechanical design process of a special linear-rotary joint for a SCARA robot, called FUM SCARA, is illustrated. FUM SCARA is constructed in the Robotics Lab of Ferdowsi University of Mashhad, in Iran. Main features of this robot are overall ±0.015 mm repeatability in XYZ plane, 8.5 m/s end-effector velocity and 0.5 seconds full pick and place cycle time. FUM SCARA robot is capable of doing applications such as pick and place and assembly in production lines using a custom designed linear-rotary joint. SCARA is a common industrial robot with inherent high joint repeatability and rigidity. As a result, repeatability of the proposed joint is essential. To pick up and place a work piece, a vacuum system tubing must be designed into the linear-rotary joint. Mechanical design process, includes linear-rotary joint design and selection of the required components. The effectiveness of the presented joint and the robot is investigated through experimental and simulation results.

关键词： linear-rotary joint industrial robot joint mechanical design

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Hybrid Approach in Recognition of Visual Covert Selective Spatial Attention based on MEG Signals

Hybrid Approach in Recognition of Visual Covert Selective Sp...

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IEEE International Conference on Fuzzy Systems

作者： S.A. Hosseini M.-R. Akbarzadeh-T. M.-B. Naghibi-Sistani Dept. of Electrical Engineering Center of Excellence on Soft Computing and Intelligent Information Processing Ferdowsi University of Mashhad Mashhad Iran

ISBN: (纸本)9781467374293

This paper proposes a reliable and efficient method for recognition in two different orientations (either left or right) by Magnetoencephalograph (MEG) signals. The brain activities are measured using different approaches with different spatial and temporal resolutions. The MEG signals are usually used for brain-computer interface (BCI) applications due to high temporal resolution. The MEG signals were recorded from different brain regions of four different human subjects during visual covert selective spatial attention task. The hybrid method proposes pre-processing;feature extraction by Hurst exponent, Morlet wavelet coefficients, and Petrosian fractal dimension;normalization;feature selection by p-value;and classification by support vector machine (SVM) and fuzzy support vector machine (FSVM). The results show that the proposed method can predict the location of the attended stimulus with a high accuracy of 91.62% and 92.28% for two different orientations with SVM and FSVM, respectively. Finally, these methods can be useful for BCI applications based on visual covert selective spatial attention.

关键词： attention magnetoencephalograph brain-computer interface cognitive system Brain-Computer Interfaces Magnetoencephalography magnetoencephalograph Support Vector Network fuzzy support vector machine cognitive function Recognition (Psychology) brain activity brain region Feature extraction Attention task signals

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The power of cognitive science in overcoming cancer and chemo brain: A collaborative personalized therapy

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Journal of Cellular Immunotherapy 2015年第1期1卷 28-29页

作者： Nasibeh Rady Raz Saeed Setayeshi Department of Electrical and Computer Engineering Center of Excellence on Soft Computing and Intelligent Information Processing Ferdowsi University of Mashhad Mashhad Iran Department of Energy Engineering and Physics Amirkabir University Tehran Iran

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Promoting Cooperation in Multi Agent Systems Through Fuzzy Social Plasticity

Promoting Cooperation in Multi Agent Systems Through Fuzzy S...

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IEEE International Conference on Fuzzy Systems

作者： Vajiheh Dehdeleh Mohammad-R. Akbarzadeh-T. Department of Computer Engineering Tabaran Institute of Higher Education Departments of Electrical and Computer Engineering Center of Excellence on Soft Computing and Intelligent Information Processing Ferdowsi University of Mashhad

ISBN: (纸本)9781467374293

In multi agent systems, agents are supposed to be aware of each other and need to cooperate with their neighboring agents in order to reach their objectives. However, there may be some selfish agents that reject cooperation due to the cost of performing the requested task, even while taking benefit from network resources and using intermediate agents to send their requests. The existence of these nodes cannot be ignored;and system efficiency can significantly deteriorate as the number of such nodes increases. Thus, a special mechanism is needed in order to confront them. Here, local structural update based on fuzzy social plasticity is proposed to persuade cooperative behavior. In this mechanism, relationships with non-cooperative agents are disconnected and the more cooperative ones, i.e. those with a trusting history for cooperation, and closer agents are preferred for the chain of relationship by a fuzzy logic heuristic. The proposed strategy intensifies cooperation by diminishing the impact of non-cooperation and reinforcing that of the cooperation. The strategy is evaluated on some random networks with different cooperation rates. Results confirm increased network cooperation, even when the majority of the agents are non-cooperative.

关键词： Cooperation Fuzzy Logic Reputation Multi Agent Systems Social Plasticity

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