Experience-consistent modeling: Regression and classification problems

In this study, we are concerned with system modeling which involves limited data and reconciles the developed model with some previously acquired domain knowledge being captured in the format of already constructed models. Each of these previously available models was formed on a basis of extensive data sets which are not available for the current identification pursuits. To emphasize the nature of modeling being guided by the reconciliation mechanisms, we refer to this mode of identification as experience-consistent modeling. The paper presents the conceptual and algorithmic framework by focusing on regression models. By forming a certain extended form of the performance index, it is shown that the domain knowledge captured by regression models can play a similar role as a regularization component used quite commonly in system identification. Experimental results involve both synthetic low-dimensional data and selected data coming from Machine Learning repository. The data used in the experiments tackle regression models as well as classification problems (two-class classifiers).     

Characterising and exploiting workloads of highly interactive video-on-demand

This paper presents a detailed characterisation of user behaviour for a series of interactive video experiments over a 12 month period, in which we served popular sporting and musical content. In addition to generic VCR-like features, our custom-built video-on-demand application provides advanced interactivity features such as bookmarking. The dramatic impact of such functionality on how users consume content is studied and analysed. We discuss in detail how this user behaviour can be exploited by content distributors to improve user experience. Specifically, we study how simple dynamic bookmark placement and interactivity-aware content pre-fetching and replication can reduce the impact of highly interactive media on CDN performance.     

SVM based robust watermarking for enhanced medical image security

Medical images are more typical than any other ordinary images, since it stores patient’s information for diagnosis purpose. Such images need more security and confidentiality as total diagnosis depends on it. In telemedicine applications, transmission of medical image via open channel, demands strong security and copyright protection. In our proposed robust watermarking model, a double layer security is introduced to ensure the robustness of embedded data. The embedded data is scrambled using a unique key and then a transform domain based hybrid watermarking technique is used to embed the scrambled data into the transform coefficients of the host image. The data embedding in medical images involves more attention, so that the diagnosis part must not be affected by any modification. Therefore, Support Vector Machine (SVM) is used as a classifier, which classify a medical image into two regions i.e. Non Region of Interest (NROI) and Region of Interest (ROI) to embed watermark data into the NROI part of the medical image, using the proposed embedding algorithm. The objective of the proposed model is to avoid any quality degradation to the medical image. The simulation is performed to measure the Peak Signal to Noise Ratio (PSNR) for imperceptibility and Structural Similarity Index (SSIM) to test the robustness. The experimented result shows, robustness and imperceptibility with SSIM of more than 0.50 and PSNR of more than 35 dB for proposed watermarking model.

     

Microhardness studies of SnI2 and SnI4 single crystals

The variation in the microhardness of tin-di-iodide (SnI₂) and tin-tetra-iodide (SnI₄) crystals has been determined using Vicker’s microhardness indentor. It is observed that the microhardness of the crystals depends on the applied load and is independent of the duration of loading. Vickers Hardness Numerals (vhn) for SnI₂ is found to be greater than that of SnI₄ crystals. Mayer’s equation and implications have been discussed.     

Magnetization Reversal by Electrical Spin Injection in Ferromagnetic (Ga,Mn)As-Based Magnetic Tunnel Junctions

We report current-induced magnetization reversal in a ferromagnetic semiconductor-based magnetic tunnel junction (Ga,Mn)As/AlAs/(Ga,Mn)As prepared by molecular beam epitaxy on a p-GaAs(001) substrate. A change in magneto-resistance that is asymmetric with respect to the current direction is found with the excitation current of 10⁶ A/cm². Contributions of both unpolarized and spin-polarized components are examined, and we conclude that the partial magnetization reversal occurs in the (Ga,Mn)As layer having smaller magnetization with the spin-polarized tunneling current of 10⁵ A/cm².     

A simplified approach to independent component analysis

Independent Component Analysis (ICA) is one of the fastest growing fields in the area of neural networks and signal processing. Blind Source Separation (BSS) is one of the applications of ICA. In this paper, ICA has been used for separating unknown source signals. BSS is used to extract independent signal components from their observed linear mixtures at an array of sensors. Various statistical techniques based on information theoretic and algebraic approaches exist for performing ICA. In this paper, we have used an objective function based on independence criterion of the signals. Optimisation of this objective function yields a neural algorithm along with a non-linear function for signal separation. Performance of the algorithm for artificially generated signals as well as audio signals has been evaluated.     

Heat penetration characteristics and shelf‐life studies of mushrooms in brine processed in retort pouches

White button mushrooms were washed, blanched and cut longitudinally into two halves. 100 g mushroom halves was placed into each retort pouch and 90 ml hot brine (2% salt, 0.1% citric acid) was added. Retort pouches (105 µm thick) had an outer polyester layer (12.5 µm), a middle aluminium layer (12.5 µm) and an inner cast polypropylene layer (80 µm); pouch size was 20 × 16 cm, seal size 10 mm and lip size 4 mm. Pouches were fixed with thermocouples for recording the core temperature of the mushroom pieces, using a data recorder and a computer. After sealing and over‐pressure retorting at F₀ = 9.6, the pouches were stored at the ambient conditions. The heat penetration parameters were calculated. The heating curve obtained was logarithmic in nature. Sensory evaluation of mushroom curry prepared from the stored mushrooms showed that the product had high acceptability (7.9 on a scale of 10) which reduced very slightly (to 7.5) during storage for 12 months. No deformity, leakage or spoilage was noticed and the product remained sterile and acceptable even after 12 months of storage at the ambient conditions (20–30°C). Copyright © 2004 John Wiley & Sons, Ltd.     

Modeling and analysis of automobile warranty data in presence of bias due to customer-rush near warranty expiration limit

Automobile users experiencing soft failures, often delay reporting of warranty claims till the coverage is about to expire. This results into a customer-rush near the warranty expiration limit leading to an occurrence of ‘spikes’ in warranty claims towards the end of warranty period and thereby introducing a bias into the dataset. At the same time, an occurrence of manufacturing/assembly defects in addition to the usage related failures, lead to ‘spikes’ in warranty claims near the beginning of the warranty period. When such data are used to capture the field failures for obtaining feedback on product quality/reliability, it may lead product or reliability engineers to potentially obtain a distorted picture of the reality. Although in reliability studies from automobile warranty data, several authors have addressed the well-recognized issues of incomplete and unclean nature of warranty data, the issue of ‘spikes’ has not received much attention. In this article, we address the issue of ‘spikes’ in the presence of the incomplete and unclean nature of warranty data and provide a methodology to arrive at component-level empirical hazard plots from such automobile warranty data.     

基于磁阻原理非接触式位移测量的非线性方法

针对低功耗和非接触式位移测量的应用需求，利用磁阻传感器，本文在传统的线性测量方法的基础上，提出了一种非线性的测量方法。设计了一个测量系统，实测结果表明该方法测量精度高、测量范围广、简单易用，也节省了成本。     

A Petri Net based approach to determine the disassembly strategy of a product

In order to protect the environment and regain value added to products, a process known as disassembly has come into the limelight. This process is to be applied to reuse abandoned goods and materials. Manufacturers are being forced to establish disassembly plants and to develop their products' designs so as to maintain the government's dictate to dispose off their products in an environmentally responsible manner. This research presents a cost-based heuristic analysis for a circuit board assembly. Various components of the product and their assembly relationships are represented by a Petri Net diagram. Firing the transitions of the disassembly Petri Net is integrated with cost-based indices to develop an effective disassembly strategy. The methodology discussed here simplifies the decisionmaking process involved in disassembly planning. A comprehensive disassembly process planning system is proposed here and is exemplified by a case study of circuit board assembly.