Motor noise generation and prediction for high spinning speed hard disk drive

The acoustic level of a hard disk drive is an important specification. This is especially so for enterprise HDD which is required to operate under a high spinning speed. In order to reduce the acoustics level of a HDD, an in depth understanding behind the mechanisms whereby the noise is being generated in a HDD should be established. This paper will study the acoustics characteristics of a high speed permanent magnet brushless DC motor (PM BLDC) and investigate the physics underlying the generation of noise associated with a motor. An analysis procedure of the PM BLDC motor noise generating mechanisms is proposed. Through finite element analysis and experimental verification, the results indicate that the major noise source for the high speed PM BLDC motor is due to the presence of electromagnetic (EM) torque ripples. Furthermore, it has been observed that the noise radiated by a HDD can be amplified when its structural dynamics are close to the frequency components of the noise source. Finally, a methodology which discusses the steps involved in the prediction of motor radiated noise will be presented.     

Self-adaptive interval type-2 neural fuzzy network control for PMLSM drives

This paper proposes a self-adaptive interval type-2 neural fuzzy network (SAIT2NFN) control system for the high-precision motion control of permanent magnet linear synchronous motor (PMLSM) drives. The antecedent parts in the SAIT2NFN use interval type-2 fuzzy sets to handle uncertainties in PMLSM drives, including payload variation, external disturbance, and sense noise. The SAIT2NFN is firstly trained to model the inverse dynamics of PMLSM through concurrent structure and parameter learning. The fuzzy rules in the SAIT2NFN can be generated automatically by using online clustering algorithm to obtain a suitable-sized network structure, and a back propagation is proposed to adjust all network parameters. Then, a robust SAIT2NFN inverse control system that consists of the SAIT2NFN and an error-feedback controller is proposed to control the PMLSM drive in a changing environment. Moreover, the Kalman filtering algorithm with a dead zone is derived using Lyapunov stability theorem for online fine-tuning all network parameters to guarantee the convergence of the SAIT2NFN. Experimental results show that the proposed SAIT2NFN control system achieves the best tracking performance in comparison with type-1 NFN control systems.     

Design of DL-based certificateless digital signatures

Public-key cryptosystems without requiring digital certificates are very attractive in wireless communications due to limitations imposed by communication bandwidth and computational resource of the mobile wireless communication devices. To eliminate public-key digital certificate, Shamir introduced the concept of the identity-based (ID-based) cryptosystem. The main advantage of the ID-based cryptosystem is that instead of using a random integer as each user’s public key as in the traditional public-key systems, the user’s real identity, such as user’s name or email address, becomes the user’s public key. However, all identity-based signature (IBS) schemes have the inherent key escrow problem, that is private key generator (PKG) knows the private key of each user. As a result, the PKG is able to sign any message on the users’ behalf. This nature violates the “non-repudiation” requirement of digital signatures. To solve the key escrow problem of the IBS while still taking advantage of the benefits of the IBS, certificateless digital signature (CDS) was introduced. In this paper, we propose a generalized approach to construct CDS schemes. In our proposed CDS scheme, the user’s private key is known only to the user himself, therefore, it can eliminate the key escrow problem from the PKG. The proposed construction can be applied to all Discrete Logarithm (DL)-based signature schemes to convert a digital signature scheme into a CDS scheme. The proposed CDS scheme is secure against adaptive chosen-message attack in the random oracle model. In addition, it is also efficient in signature generation and verification.     

Hiding data in spatial domain images with distortion tolerance

Data hiding is a technique that is used to embed secret information into a cover media. It has been widely used in protecting copyright and transmitting sensitive data over an insecure channel. Conventional data hiding schemes only focus on how to reduce the distortion when sensitive data is embedded into the cover image. However, the transmitted images may be compressed or occur transmitting errors. If such errors occur, the receiver cannot extract the correct information from the stego-image. In this paper, we proposed a novel hiding data scheme with distortion tolerance. The proposed scheme not only can prevent the quality of the processed image from being seriously degraded, but also can simultaneously achieve distortion tolerance. Experimental results show that the proposed scheme indeed can obtain a good image quality and is superior to the other schemes in terms of its distortion tolerance.     

Automatic detection of breast cancers in mammograms using structured support vector machines

Breast cancer is one of the most common cancers diagnosed in women. Large margin classifiers like the support vector machine (SVM) have been reported effective in computer-assisted diagnosis systems for breast cancers. However, since the separating hyperplane determination exclusively relies on support vectors, the SVM is essentially a local classifier and its performance can be further improved. In this work, we introduce a structured SVM model to determine if each mammographic region is normal or cancerous by considering the cluster structures in the training set. The optimization problem in this new model can be solved efficiently by being formulated as one second order cone programming problem. Experimental evaluation is performed on the Digital Database for Screening Mammography (DDSM) dataset. Various types of features, including curvilinear features, texture features, Gabor features, and multi-resolution features, are extracted from the sample images. We then select the salient features using the recursive feature elimination algorithm. The structured SVM achieves better detection performance compared with a well-tested SVM classifier in terms of the area under the ROC curve.     

Efficient simulation of hard disk drive operational shock response using model order reduction

The complex structure, coupled mechanical and fluidic energy domains, and inherent nonlinearity of air bearing between slider and disk involved in the hard disk drive (HDD) are normally presented as a large scale problem which will result in very heavy computational costs in terms of intensive computation and time consuming for HDD research communities and industries to carry out the transient dynamic simulation for HDD design verification, performance analysis, and optimization by using the traditional full-order models, such as finite element model (FEM). This paper presents a method of application of model order reduction (MOR) technique to dramatically reduce the computation time for HDD transient shock performance analysis while capturing the behaviors of original problem faithfully. The reduced models are obtained by performing MOR directly to the FEMs through Krylov subspace and Arnoldi algorithm. The transient operational shock response results of the reduced models of a head suspension assembly (HSA) subjected to half-sine shock pulse demonstrate that the reduced models can dramatically reduce total computation by at least three orders and have very good agreement with those simulated from the original large problem by full-order FEM.     

A blind watermarking method using maximum wavelet coefficient quantization

This paper proposes a blind watermarking algorithm based on maximum wavelet coefficient quantization for copyright protection. The wavelet coefficients are grouped into different block size and blocks are randomly selected from different subbands. We add different energies to the maximum wavelet coefficient under the constraint that the maximum wavelet coefficient is always maximum in a block. The watermark is embedded the local maximum coefficient which can effectively resist attacks. Also, using the block-based watermarking, we can extract the watermark without using the original image or watermark. Experimental results show that the proposed method is quite robust under either non-geometry or geometry attacks.     

基于贝叶斯最大化后验估计方法的图片合成模型研究

在图像处理应用中,常常需要根据一些列相关的输入图片生成一张新的图片。现有的研究大都设定一些启发式规则用于图片的合成过程。为了提高图片合成的性能,提出了一种基于改进的贝叶斯方法的图片合成模型。在给定理想的图片合成模型后,对传感器误差和图片误差进行了分析。由于图片误差和几何误差之间是相关的,因此分析了它们之间的关系。在根据已有数据对模型进行后验估计时,通过最小化能量来得到模型的先验参数。在目标函数的优化过程中,基于现有研究通过重新赋权值的迭代方法进行优化问题的求解。最后,通过大量的实验表明,所提出的图片合成模型与相关方法相比具有更好的图片合成和渲染效果。     

Optimal replacement policy for a two-dissimilar-component cold standby system with different repair actions

In this paper, a cold standby repairable system consisting of two dissimilar components and one repairman is studied. When failures occur, the repair of both component 1 and component 2 are not ‘as good as new’. The consecutive operating times of component 1 after repair constitute a decreasing geometric process, while the repair times of component 1 are independent and identically distributed. For component 2, its failure is rectified by minimal repair, and the repair time is negligible. Component 1 has priority in use when both components are good. The replacement policy N is based on the failure number of component 1. Under policy N, we derive the explicit expression of the long-run average cost rate C(N) as well as the average number of repairs of component 2 before the system replaced. The optimal replacement policy N*, which minimises the long-run average cost rate C(N), is obtained theoretically. If the failure rate r(t) of component 2 is increasing, the existence and uniqueness of the optimal policy N* is also proved. Finally, a numerical example is given to validate the developed theoretical model. Some sensitivity analyses are provided to show the influence of some parameters, such as the costs for replacement and repair, and the parameters of the lifetime and repair time distributions of both components, to the optimal replacement policy N* and corresponding average cost rate C(N*).