Abstract Background The DNA microarray technology allows the measurement of expression levels thousands genes under tens/hundreds different conditions. In data, with similar functions usually co-express certain conditions only [1]. Thus, biclustering which clusters and simultaneously is preferred over traditional clustering technique in discovering these coherent genes. Various algorithms have been developed using bicluster formulations. Unfortunately, many useful formulations result...

An image segmentation algorithm based on adaptive fuzzy c-means (FCM) clustering is presented in this paper. In the conventional FCM algorithm, cluster assignment solely distribution of pixel attributes feature space, and does not take into consideration spatial pixels an image. By introducing a novel dissimilarity index modified objective function, new capable utilizing local contextual information to impose continuity, thus exploiting high inter-pixel correlation inherent most real-world...

Abstract Summary: BiVisu is an open-source software tool for detecting and visualizing biclusters embedded in a gene expression matrix. Through the use of appropriate coherence relations, can detect constant, constant-row, constant-column, additive-related as well multiplicative-related biclusters. The biclustering results are then visualized under 2D setting easy inspection. In particular, parallel coordinate (PC) plots each bicluster displayed, from which objective subjective cluster...

Source camera identification has long been a hot topic in the field of image forensics. Besides conventional feature engineering algorithms developed based on studying traces left upon shooting, several deep-learning-based methods have also emerged recently. However, performance is susceptible to content and far from satisfactory for small patches real demanding applications. In this paper, an efficient patch-level source method proposed convolutional neural network. First, order obtain...

<title>Abstract</title> Smart contracts and blockchain technology have revolutionized our transactions interactions with digital systems, yet their vulnerabilities can lead to devastating consequences such as financial losses, data breaches, compromised system integrity. Existing detection methods, including static analysis, dynamic machine learning-based approaches, limitations, requiring large amounts of labeled or being computationally expensive. To address these we propose a novel...

It is well known that low bit rate block-based discrete cosine transform coded image exhibits visually annoying coding artifacts. In this paper, we proposed a projection onto convex sets (PCOS)-based deblocking algorithm using novel region smoothness constraint set for graphic images containing objects with smooth regions. The obtained by an explicit modeling of regions in the spatially adaptive thin-plate spline. contrast to most algorithms which enforce just around 8/spl times/8 block...

A binary wavelet transform (BWT) has several distinct advantages over a real when applied to data. No quantisation distortion is introduced and the completely invertible. Since all operations involved are modulo-2 arithmetic, it extremely fast. The outstanding qualities of BWT make suitable for image-processing applications. BWT, originally designed images, extended lossless compression grey-level images. An in-place implementation structure explored. Then, simple embedded BWT-based...

In this paper, an object based bi-directional counting system is proposed, which comprises of advanced detection and tracking algorithm to count the people flow in monitoring scene. The result shows that approach can provide about 90% accuracy for with angle 45°

Due to the advancement of DNA sequencing techniques, number sequenced individual genomes has experienced an exponential growth. Thus, effective compression this kind sequences is highly desired. In work, we present a novel algorithm called Reference-based Compression using concept Clustering (RCC). The rationale behind RCC based on observation about existence substructures within population sequences. To utilize these substructures, k-means clustering employed partition into clusters for...

Traditionally, intra-sequence similarity is exploited for compressing a single DNA sequence. Recently, remarkable compression performance of individual sequence from the same population achieved by encoding its difference with nearly identical reference Nevertheless, there lack general algorithms that also allow less similar sequences. In this work, we extend to inter-sequence in approximate matches subsequences are found between and set Hence, sequences or partially like chromosome related...