Co-Degeneracy and Co-Treewidth: Using the Complement to Solve Dense Instances

Clique-width and treewidth are two of the most important and useful graph parameters, and several problems can be solved efficiently when restricted to graphs of bounded clique-width or treewidth. Bounded treewidth implies bounded clique-width, but not vice versa. Problems like Longest Cycle, Longest Path, MaxCut, Edge Dominating Set, and Graph Coloring are fixed-parameter tractable when parameterized by the treewidth, but they cannot be solved in FPT time when parameterized by the clique-width unless FPT = W[1], as shown by Fomin, Golovach, Lokshtanov, and Saurabh [SIAM J. Comput. 2010, SIAM J. Comput. 2014]. For a given problem that is fixed-parameter tractable when parameterized by treewidth, but intractable when parameterized by clique-width, there may exist infinite families of instances of bounded clique-width and unbounded treewidth where the problem can be solved efficiently. In this work, we initiate a systematic study of the parameters co-treewidth (the treewidth of the complement of the input graph) and co-degeneracy (the degeneracy of the complement of the input graph). We show that Longest Cycle, Longest Path, and Edge Dominating Set are FPT when parameterized by co-degeneracy. On the other hand, Graph Coloring is para-NP-complete when parameterized by co-degeneracy but FPT when parameterized by the co-treewidth. Concerning MaxCut, we give an FPT algorithm parameterized by co-treewidth, while we leave open the complexity of the problem parameterized by co-degeneracy. Additionally, we show that Precoloring Extension is fixed-parameter tractable when parameterized by co-treewidth, while this problem is known to be W[1]-hard when parameterized by treewidth. These results give evidence that co-treewidth is a useful width parameter for handling dense instances of problems for which an FPT algorithm for clique-width is unlikely to exist. Finally, we develop an algorithmic framework for co-degeneracy based on the notion of Bondy-Chvátal closure.publishedVersio

A Robust Real-Time Automatic License Plate Recognition Based on the YOLO Detector

Automatic License Plate Recognition (ALPR) has been a frequent topic of research due to many practical applications. However, many of the current solutions are still not robust in real-world situations, commonly depending on many constraints. This paper presents a robust and efficient ALPR system based on the state-of-the-art YOLO object detector. The Convolutional Neural Networks (CNNs) are trained and fine-tuned for each ALPR stage so that they are robust under different conditions (e.g., variations in camera, lighting, and background). Specially for character segmentation and recognition, we design a two-stage approach employing simple data augmentation tricks such as inverted License Plates (LPs) and flipped characters. The resulting ALPR approach achieved impressive results in two datasets. First, in the SSIG dataset, composed of 2,000 frames from 101 vehicle videos, our system achieved a recognition rate of 93.53% and 47 Frames Per Second (FPS), performing better than both Sighthound and OpenALPR commercial systems (89.80% and 93.03%, respectively) and considerably outperforming previous results (81.80%). Second, targeting a more realistic scenario, we introduce a larger public dataset, called UFPR-ALPR dataset, designed to ALPR. This dataset contains 150 videos and 4,500 frames captured when both camera and vehicles are moving and also contains different types of vehicles (cars, motorcycles, buses and trucks). In our proposed dataset, the trial versions of commercial systems achieved recognition rates below 70%. On the other hand, our system performed better, with recognition rate of 78.33% and 35 FPS.Comment: Accepted for presentation at the International Joint Conference on Neural Networks (IJCNN) 201

Complex Network Tools to Understand the Behavior of Criminality in Urban Areas

Complex networks are nowadays employed in several applications. Modeling urban street networks is one of them, and in particular to analyze criminal aspects of a city. Several research groups have focused on such application, but until now, there is a lack of a well-defined methodology for employing complex networks in a whole crime analysis process, i.e. from data preparation to a deep analysis of criminal communities. Furthermore, the "toolset" available for those works is not complete enough, also lacking techniques to maintain up-to-date, complete crime datasets and proper assessment measures. In this sense, we propose a threefold methodology for employing complex networks in the detection of highly criminal areas within a city. Our methodology comprises three tasks: (i) Mapping of Urban Crimes; (ii) Criminal Community Identification; and (iii) Crime Analysis. Moreover, it provides a proper set of assessment measures for analyzing intrinsic criminality of communities, especially when considering different crime types. We show our methodology by applying it to a real crime dataset from the city of San Francisco - CA, USA. The results confirm its effectiveness to identify and analyze high criminality areas within a city. Hence, our contributions provide a basis for further developments on complex networks applied to crime analysis.Comment: 7 pages, 2 figures, 14th International Conference on Information Technology : New Generation

Challenges in the use of NG2 antigen as a marker to predict MLL rearrangements in multi-center studies

AbstractRearrangements in MLL (MLL-r) are common within very young children with leukemia and affect the prognosis and treatment. Previous studies have suggested the use of the NG2 molecule as a marker for MLL-r but these studies were performed using a small number of infants. We analyzed 148 patients (all less than 24 months, 86 less than 12 months) from various centers in Brazil to determine the predictive power of NG2 within that cohort. We show that NG2 can be used for MLL-r prediction; however, proper staff training and standardized sampling procedures are essential when receiving samples from multiple centers as the accuracy of the prediction varies greatly on a per center basis

Experimental Implementation of a Two-Stroke Quantum Heat Engine

We put forth an experimental simulation of a stroboscopic two-stroke thermal engine in the IBMQ processor. The system consists of a quantum spin chain connected to two baths at their boundaries, prepared at different temperatures using the variational quantum thermalizer algorithm. The dynamics alternates between heat and work strokes, which can be separately designed using independent quantum circuits. The results show good agreement with theoretical predictions, showcasing IBMQ as a powerful tool to study thermodynamics in the quantum regime, as well as the implementation of variational quantum algorithms in real-world quantum computers. It also opens the possibility of simulating quantum heat transport across a broad range of chains geometries and interactions

A forged ‘chimera’ including the second specimen of the protostegid sea turtle Santanachelys gaffneyi and shell parts of the pleurodire Araripemys from the Lower Cretaceous Santana Group of Brazil

Fossils of Cretaceous sea turtles adapted to an open marine lifestyle remain rare finds to date. Furthermore, the relationships between extant sea turtles, chelonioids, and other Mesozoic marine turtles are still contested, with one key species being Santanachelysgaffneyi Hirayama, 1998, long considered the earliest true sea turtle. The species is an Early Cretaceous member of Protostegidae, a controversial clade either placed within or closely related to Chelonioidea or, alternatively, along the stem lineage of hidden-neck turtles (Cryptodira) and representing an independent open marine radiation. Santanachelysgaffneyi is one of the most completely preserved early protostegids and is therefore critical for establishing the global phylogenetic position of the group. However, the single known specimen of this taxon is yet to be described in detail. Here we describe a second specimen of Santanachelysgaffneyi from its type horizon, the Romualdo Formation (late Aptian) of the Santana Group of the Araripe basin, NE Brazil. The skeletal elements preserved include the posterior part of the skull, neck vertebrae, shoulder girdle, anterior-most and left/central part of the carapace with few peripherals, and plastron lacking most of the hyoplastra. The remaining part of the carapace was apparently completed by fossil dealers using an anterior part of the pleurodiran Araripemydidae, tentatively identified as a shell portion of cf. Araripemysbarretoi, a more common Santana fossil turtle, among other indeterminate turtle shell fragments. The purpose of this paper is to report the repatriation of the specimen to Brazil and to provide a preliminary description