One of the most important threats to today’s civilization is terrorism. Terrorism not only disturbs law and order situations in a society but also affects quality lives humans makes them suppressed physically emotionally deprives enjoying life. The more civilizations have advanced, people are working towards exploring different mechanisms protect mankind from Different techniques been used as counterterrorism individuals improve life general. Machine learning methods recently explored...

The aim of this paper is to explore the use backtrackless walks and prime cycles for characterizing both labeled unlabeled graphs. reason using that they avoid tottering, can increase discriminative power resulting graph representation. However, such methods limited in practice because their computational cost. In paper, we present efficient computing kernels, which are based on a whose worst case running time same as kernels random walks. For clustering graphs, construct feature vectors...

Organizations can grow, succeed, and sustain if their employees are committed. The main assets of an organization those who giving it a required number hours per month, in other words, punctual towards attendance. Absenteeism from work is multibillion-dollar problem, costs money decreases revenue. At the time hiring employee, organizations do not have objective mechanism to predict whether employee will be attendance or habitually absent. For some organizations, very difficult deal with...

Link prediction in a complex network is problem of fundamental interest science and has attracted increasing attention recent years. It aims to predict missing (or future) links between two entities system that are not already connected. Among existing methods, local similarity indices most popular take into account the information common neighbours estimate likelihood existence connection nodes. In this paper, we propose global quasi-local extensions some commonly used indices. We have...

Reversible Data Hiding (RDH) techniques have gained popularity over the last two decades, where data is embedded in an image such a way that original can be restored. Earlier works on RDH was based Image Histogram Modification uses peak point to embed image. More recent focus Difference exploits fact neighbouring pixels of are highly correlated and therefore difference makes more space large amount data. In this paper we propose framework increase embedding capacity reversible hiding use The...

Background Numerous approaches have been proposed for the detection of epistatic interactions within GWAS datasets in order to better understand drivers disease and genetics. Methods A selection state-of-the-art were assessed. These included statistical tests, fast-epistasis, BOOST, logistic regression wtest; swarm intelligence methods, namely AntEpiSeeker, epiACO CINOEDV; data mining approaches, including MDR, GSS, SNPRuler MPI3SNP. Data simulated provide randomly generated models with no...

Abstract Traditional machine learning techniques follow a single shot approach. It includes all supervised, semi-supervised, transfer learning, hybrid and unsupervised having target domain known prior to analysis. Learning from one task is not carried the next task, therefore, they cannot scale up big data many unknown domains. Lifelong models are tailored for knowledge module that maintained automatically. The knowledge-base grows with experience where previous tasks helps in current task....

Lifelong machine learning (LML) models learn with experience maintaining a knowledge-base, without user intervention. Unlike traditional single-domain they can easily scale up to explore big data. The existing LML have high data dependency, consume more resources, and do not support streaming This paper proposes online model (OAMC) reduced dependency. With engineering the knowledge-base introducing new knowledge features pattern of is improved for arriving in pieces. OAMC improves accuracy...

Abstract Multimorbidity, frequently associated with aging, can be operationally defined as the presence of two or more chronic conditions. Predicting likelihood a patient multimorbidity to develop further particular disease in future is one key challenges research. In this paper we are using network-based approach analyze data and methods for predicting diseases that likely develop. The represented temporal bipartite network whose nodes represent patients link between these indicates has...

Heterogeneous systems have gained popularity due to the rapid growth in data and need for processing this big extract useful information. In recent years, many healthcare applications been developed which use machine learning algorithms perform tasks such as image classification, object detection, segmentation, instance segmentation. The increasing amount of visual requires images be processed efficiently. It is common that we heterogeneous type applications, a huge number on single PC may...

Link prediction in complex networks has recently attracted a great deal of attraction diverse scientific domains, including social and biological sciences. Given snapshot network, the goal is to predict links that are missing network or likely occur near future. This problem both theoretical practical significance; it not only helps us identify more efficiently by avoiding expensive time consuming experimental processes, but also allows study evolution with time. To address link prediction,...

This article explores the possibility of using a quantum graph representation to investigate information flow across complex network in form wave propagation. The term refers with differential operators acting on functions defined over real valued intervals associated edges. These provide convenient which allows from calculus be generalized or structures, simplest is metric Laplacian. We present complete solutions equation graph, obtained Laplacian are more than those traditional...

In mobile ad hoc networks (MANETs), the topology differs very often due to nodes (MNs). The flat network organization has high maintenance messages overload. To reduce this message overload in MANET, clustering organizations are recommended. Grouping MANET into MNs advantage of controlling congestion and easily repairing topology. When size is large, clustered MN partitioning a multiobjective optimization problem. Several evolutionary algorithms such as genetic (GAs) used divide clusters....

Topic models are extensively used for text analysis to extract prominent concepts as topics in a large collection of documents about subject domain. They extended with different approaches suit various application areas. Automatic knowledge-based topic recently introduced specifically meet the processing needs large-scale data having many domains. The model automatically learns rules across all domains and uses them improve results current domain by purposefully grouping words into better...

Abstract In this article, we present a novel approach to analyse the structure of complex networks represented by quantum graph. A graph is metric with differential operator (including edge-based Laplacian) acting on functions defined edges Every edge has length interval assigned it. The structural information contents are measured using entropy which been proved useful and compare networks. Our definition based local functionals. These functionals obtained diffusion process Laplacian...