A computer-aided diagnostic system for liver tumor detection using modified U-Net architecture

The Journal of Supercomputing - A multimedia-based medical decision-making system is an ultimate requirement in the medical imaging domain. In the healthcare sector, achieving quick and efficient...     

Silver (Ag) as a novel masking material in glass etching for microfluidics applications

In this paper, we report the use of a single masking film for deep glass etching in hydrofluoric acid (HF). Thin film silver (Ag) is the key masking material in this work enabling a simple and low cost fabrication of microfluidic structures. The Ag film was deposited by evaporation and etched in a diluted nitric acid and de-ionized water solution at a ratio of 1:3. Surface morphology for different thicknesses of Ag film and its correlation to the maximum achievable etch depth is analyzed. AFM results shows low roughness values (<5 nm), indicating the Ag films are of smooth surface. With a 100 nm Ag film, a 220 μm etch depth in borosilicate glass substrates were produced and by further thickening the Ag to 300 nm, etch depths exceeding 300 μm were successfully achieved. SEM images show that thinner Ag films are of finer grains, potentially a source for pinholes formation where rapid penetration of HF along the grain boundaries peels off the Ag film from the glass surface. However, the Ag film was found not to react with HF. The process was demonstrated in the fabrication of cavities for integration with other microfluidic devices.     

A new image encryption scheme with Feistel like structure using chaotic S-box and Rubik cube based P-box

Multimedia Tools and Applications - In this paper, a novel chaos-based dynamic encryption scheme with a permutation-substitution structure is presented. The S-boxes and P-boxes of the scheme are...     

Area-efficient HEVC core transform using multi-sized and reusable DCT architectures

Multimedia Tools and Applications - This paper presents an area-efficient and multi-sized DCT architecture for HEVC application. We exploit the commonality in the arithmetic units to increase the...     

Developing economic order quantity model for non-instantaneous deteriorating items in vendor-managed inventory (VMI) system

This paper develops an economic order quantity model for non-instantaneous deteriorating items with and without shortages to investigate the performance of the vendor-managed inventory (VMI) system. This model is developed for a two-level supply chain consisting of a single supplier and single retailer with a single non-instantaneous deteriorating item. A numerical example and sensitivity analysis are provided to illustrate how increasing or reducing the related parameters change the optimal values of the decision variables of the two proposed models. The results show that VMI works better and charges lower cost in all conditions.     

Feature extraction using median–mean and feature line embedding

In this article, we propose a feature extraction method based on median–mean and feature line embedding (MMFLE) for the classification of hyperspectral images. In MMFLE, we maximize the class separability using discriminant analysis. Moreover, we remove the negative effect of outliers on the class mean using the median–mean line (MML) measurement and virtually enlarge the training set using the feature line (FL) distance metric. The experimental results on Indian Pines and University of Pavia data sets show the better performance of MMFLE compared to nearest feature line embedding (NFLE), median–mean line discriminant analysis (MMLDA), and some other feature extraction approaches in terms of classification accuracy using a small training set.     

An adaptive local binarization method for document images based on a novel thresholding method and dynamic windows

Binary image representation is essential format for document analysis. In general, different available binarization techniques are implemented for different types of binarization problems. The majority of binarization techniques are complex and are compounded from filters and existing operations. However, the few simple thresholding methods available cannot be applied to many binarization problems. In this paper, we propose a local binarization method based on a simple, novel thresholding method with dynamic and flexible windows. The proposed method is tested on selected samples called the DIBCO 2009 benchmark dataset using specialized evaluation techniques for binarization processes. To evaluate the performance of our proposed method, we compared it with the Niblack, Sauvola and NICK methods. The results of the experiments show that the proposed method adapts well to all types of binarization challenges, can deal with higher numbers of binarization problems and boosts the overall performance of the binarization.     

Post Recognition Speech Localization

How much does knowledge regarding a certain spoken word or phrase help with its localization? This is a very fundamental question for speech processing, and will be partially addressed in this paper. In particular, this work will utilize prior information regarding the contents of a speech signal in order to improve the artificial localization of it using Time delay of arrival (TDOA) between two microphones. The prior information, which is used to develop a very simple frequency-selective phase transform (FPT), increases the effective SNR by only using a subset of the highest SNR frequencies in the Phase Transform. Simulations in a reverberant environment show that the proposed approach can more robustly and accurately localize speech sources. For 20 ms signal segments, it is shown that using a subset of 45 percent of available speech frequency bins is superior to using 30, 60, or 100, where using 100 corresponds to the standard Phase Transform.