The enhanced suffix array is an indexing data structure used for a wide range of applications in Bioinformatics. It is basically the suffix array but enhanced with extra tables that provide extra information to improve the performance in theory and in practice. In this paper, we present a number of improvements to the enhanced suffix array: 1) We show how to find a pattern of length m in O(m) time, i.e., independent of the alphabet size. 2) We present an improved representation of the bucket table. 3) We improve the access time of addressing the LCP (longest common prefix) table when one byte

Background: Comparative genomics is the analysis and comparison of genomes from different species. This area of research is driven by the large number of sequenced genomes and heavily relies on efficient algorithms and software to perform pairwise and multiple genome comparisons. Results: Most of the software tools available are tailored for one specific task. In contrast, we have developed a novel system CoCoNUT (Computational Comparative geNomics Utility Toolkit) that allows solving several different tasks in a unified framework: (1) finding regions of high similarity among multiple genomic

Optic Disc (OD) localization is an important pre-processing step that significantly simplifies subsequent segmentation of the OD and other retinal structures. Current OD localization techniques suffer from impractically-high computation times (few minutes per image). In this work, we present a fast technique that requires less than a second to localize the OD. The technique is based upon obtaining two projections of certain image features that encode the x- and y- coordinates of the OD. The resulting 1-D projections are then searched to determine the location of the OD. This avoids searching

Vehicular Ad-hoc Networks (VANETs) are a subset of Mobile Ad-hoc Networks (MANETs). They are deployed to introduce the ability of inter-communication among vehicles in order to guarantee safety and provide services for people while driving. VANETs are exposed to many types of attacks like denial of service, spoofing, ID disclosure and Sybil attacks. In this paper, a novel lightweight approach for preventing Sybil attack in VANETs is proposed. The presented protocol scheme uses symmetric key encryption and authentication between Road Side Units (RSUs) and vehicles on the road so that no

Federated learning (FL) has recently been proposed as an emerging paradigm to build machine learning models using distributed training datasets that are locally stored and maintained on different devices in 5G networks while providing privacy preservation for participants. In FL, the central aggregator accumulates local updates uploaded by participants to update a global model. However, there are two critical security threats: poisoning and membership inference attacks. These attacks may be carried out by malicious or unreliable participants, resulting in the construction failure of global

This paper deals with solving large instances of the Linear Sum Assignment Problems (LSAPs) under realtime constraints, using Graphical Processing Units (GPUs). The motivating scenario is an industrial application for P2P live streaming that is moderated by a central tracker that is periodically solving LSAP instances to optimize the connectivity of thousands of peers. However, our findings are generic enough to be applied in other contexts. Our main contribution is a parallel version of a heuristic algorithm called Deep Greedy Switching (DGS) on GPUs using the CUDA programming language. DGS

The radical change in technology and high customer expectations and demand are pushing the service desk to provide a competent service for the customers. And this service should be faster, more flexible and gives a more accurate response and high user experience. Replacing the human call agent’s activities with a cognitive agent could improve the user experience by providing a faster response to customer’s requests, removing the human errors and giving 24/7 support with less operational cost. The cognitive agent has the potential to scale personalized and tailored interactions. And this will

Hand gesture recognition is one of the most challenging topics in computer vision. In this paper, a new hand gesture recognition algorithm presenting a 2D representation of histogram of oriented gradients is proposed, where each bin represents a range of angles dealt with in a separate layer which allows using 2DPCA. This method maintains the spatial relation between pixels which enhances the recognition accuracy. In addition, it can be applied on either hand contour or image representing hand details. Experimental results were performed on the latest existing depth camera dataset. The

In this paper, we present an analytical tool for under-standing the performance of structured overlay networks under churn based on the master-equation approach of physics. We motivate and derive an equation for the average number of hops taken by lookups during churn, for the Chord network. We analyse this equation in detail to understand the behaviour with and without churn. We then use this understanding to predict how lookups will scale for varying peer population as well as varying the sizes of the routing tables. We also consider a change in the maintenance algorithm of the overlay, from

The boom in telecommunications is expected to have many impacts on peoples' activities and travel behavior. Recent advances in information and communication technologies (ICTs) make it possible to conduct activities virtually. Thus the need for physical travel for some types of activities is obviated. Accordingly, the use of ICT may contribute to reducing urban congestion and alleviating air quality problems. However, ICT may generate significant additional travel because of the increased connectivity and access to resources. Empirical insights on how the growing use of ICT affects travel