On the Pixel Expansion of Visual Cryptography Scheme

In this paper, we first follow Ateniese et al.'s work that provides upper bounds of the pixel expansion of visual cryptography schemes(VCSs) for more kinds of graph access structures, in which we require that a subset of parties can determine the secret if they contain an edge of the graph G. The constructive upper bounds are derived by the graph decomposition technique. Then we generalize Ateniese et al.'s method of comparing the optimal pixel expansion of VCSs with two different access structures.

Bipartite Weighted Graph Access for Optimal Label Prediction

This article portrayed a novel bipartite weighted graph strategy for Feature optimization for machine learning models. Unlike many of the existing optimization techniques of diverse categories such as evolutionary computation techniques, diversity assessment strategies, the proposal is deterministic approach with minimal computational overhead, which has referred further as Bipartite Weighted Graph Approach for Optimal label prediction (BWG-OLP). The proposed model is about to derive a given feature is optimal or not by the respective feature’s correlation with the records and the correlation with the fellow features. The experimental study has carried on benchmark datasets to estimate the significance of the proposed method.

A Sequence Distance Graph framework for genome assembly and analysis

The Sequence Distance Graph (SDG) framework works with genome assembly graphs and raw data from paired, linked and long reads. It includes a simple deBruijn graph module, and can import graphs using the graphical fragment assembly (GFA) format. It also maps raw reads onto graphs, and provides a Python application programming interface (API) to navigate the graph, access the mapped and raw data and perform interactive or scripted analyses. Its complete workspace can be dumped to and loaded from disk, decoupling mapping from analysis and supporting multi-stage pipelines. We present the design and implementation of the framework, and example analyses scaffolding a short read graph with long reads, and navigating paths in a heterozygous graph for a simulated parent-offspring trio dataset. SDG is freely available under the MIT license at https://github.com/bioinfologics/sdg

On the Pixel Expansion of Visual Cryptography Scheme

In this paper, we first follow Ateniese et al.'s work that provides upper bounds of the pixel expansion of visual cryptography schemes(VCSs) for more kinds of graph access structures, in which we require that a subset of parties can determine the secret if they contain an edge of the graph G. The constructive upper bounds are derived by the graph decomposition technique. Then we generalize Ateniese et al.'s method of comparing the optimal pixel expansion of VCSs with two different access structures.

The complexity of the connected graph access structure on seven participants

In this paper, we study an important problem in secret sharing that determines the exact value or bound for the complexity. First, we use the induced subgraph complexity of the graph G with access structure Γ to obtain a lower bound on the complexity of the graph G. Then, applying decomposition techniques, we obtain an upper bound on the complexity of the graph G. We determine the exact values of the complexity for each of the ten graph access structures on seven participants. Also, we improve the value bound of the complexity for the six graph access structures with seven participants.