This study conducts a comparative analysis of the performance of different programming languages on Android embedded systems, focusing on execution time. Through controlled experiments, we compared traditional and emerging programming languages (Java, Kotlin, C, C++, Python, Golang, and Rust) using a variety of representative algorithms. The results revealed significant disparities among the programming languages, with C and C++ performing significantly better than the others, although in some algorithms Golang approached close in terms of execution time. The native Android application languages, Java and Kotlin, showed intermediate results compared to the others, with very close outcomes between them. Python and Rust had the worst results, with Python's performance being justified by the interpreted nature of the language and the lack of multiprocessing features on Android. Rust was possibly hindered by its inability to efficiently access low-level resources when applied to the Android application layer.

In this work, the Vehicle Routing Problem with Time Windows (VRPTW) is addressed as a way of incorporating dynamic characteristics of the urban express delivery logistics chain, exploring theoretical aspects that best define the problem and its instances. The problem is to determine minimum cost routes that must be performed by a fleet respecting the capacities of vehicles and the time windows associated with each delivery. A strategy that uses the Branch-Cut-and-Price method through the VRPsolver tool was applied to two sets of instances, the first being Solomon’s artificial classical instances and, the second, real instances of Brazilian urban cities adapted from the loggiBUD benchmark.

Several systems proposed for processing keyword queries over relational databases rely on the generation and evaluation of Candidate Networks (CNs), i.e., networks of joined database relations that when processed as SQL queries, provide a relevant answer to the input keyword query. Although the evaluation of CNs has been extensively addressed in the literature, the problem of generating CNs efficiently and effectively has received much less attention. This challenging problem consists of automatically locating relations in the database that may contain relevant pieces of information, given a handful of keywords, and determining suitable ways of joining these relations to satisfy the implicit information needs expressed by a user while formulating his/her query. In this paper, we propose a novel approach for generating CNs, wherein the possible matches for the query in the database are efficiently enumerated at first. Thesequery matchesare then used to guide the CN generation process, avoiding the exhaustive search procedure used by the current state-of-art approaches. We show that our approach allows the generation of a compact set of CNs that leads to superior quality answers, and demands less resources in terms of processing time and memory. These claims are supported by a comprehensive set of experiments that we carried out using several query sets and datasets used in previous related works and whose results we report and analyze here.

The Gangal-Ranade algorithm presents the best approximation ratio for the classic scheduling problem with unit execution time and precedence constrained jobs, on a variable number of identical parallel machines, to minimize the makespan. This work presents results about the optimality of the algorithm when the acyclic directed graph (DAG) that represents the precedence constraints are arborescences (directed trees, in-tree and out-tree), reinforcing that these types of DAGs provide optimal substructures for the problem. Understanding the behavior of this algorithm for classes of arborescences can lead to optimality or better approximations for classes of larger DAGs, which is our ongoing research work. Furthermore, the search for optimal cases for algorithms such as Gangal-Ranade can provide intuition to obtain partial answers to problems that remain open, such as the famous Open 8 in the list presented in the classical Garey and Johnson book.

A fast way to reconstruct the three-dimensional molecular conformation of SARS-CoV-2 virus proteins is addressed in this article, involving the most worrying variant discovered in patients from Brazil, the lineage$B$.1.1.28/$P$.1. The proposed methodology is based on the sequencing of virus proteins and that, through the incorporation of mutations in silico, which are then computationally reconstructed using an enumerative feasibility algorithm validated by the Ramachandran diagram and structural alignment, in addition to the subsequent study of structural stability through classical molecular dynamics. From the resulting structure to the ACE2-RBD complex, the valid solution presented 97.06% of the residues in the most favorable region while the reference crystallographic structure presented 95.0%, a difference therefore very small and revealing the great consistency of the developed algorithm. Another important result was the low RMSD alignment between the best solution by the BP algorithm and the reference structure, where we obtained 0.483Å. Finally, the molecular dynamics indicated greater structural stability in the ACE2-RBD interaction with the P.1 strain, which could be a plausible explanation for convergent evolution that provides an increase in the interaction affinity with the ACE2 receptor.

In this work, an initial study on the automatic recognition of the main Brazilian music genres is presented: Axé, Forró, MPB, Rock, Samba, and Sertanejo. Through the extraction of representative musical characteristics, automatic classification experiments were performed applying classical supervised learning algorithms and Weka ML tool. An analysis of the main available databases was also carried out: GTZAN, FMA, AudioSet, RWC, ISMIR, Magnatune, and LMD. There is a scarcity of cultural diversity on these bases, most of which concentrate globally more popular styles such as Pop and Rock, reinforcing the need to include more diverse and culturally identifiable genres, such as Brazilians. The preliminary results obtained demonstrate the adequacy of the recognition process of the main Brazilian musical genres.

Using mobile devices is part of modern daily life for communication, work, and leisure. Its use in entertainment events such as music concert and sports games is easily noted. Thus, in this work, we investigate how these devices can increase engagement in entertainment events. For this, we developed a collaborative game called Cabo DIGuerra that uses motion and audio sensors in an interactive dynamic with the audience using concepts from Mobile Crowd Sensing and User eXperience. The game was evaluated through experimental studies both in a controlled environment and in real use scenarios of the application, highlighting its educational potential beyond entertainment.

Several systems for processing keyword queries over relational databases rely on the generation and evaluation of Candidate Networks (CNs), i.e., networks of joined relations that when processed as SQL queries, provide a relevant answer to the input keyword query. Although the evaluation of CNs has been extensively addressed in the literature, the problem of generating CNs has received much less attention. We propose a novel approach for generating CNs, wherein the possible matches for the query in the database are efficiently enumerated at first. These query matches are then used to guide the CN generation process, avoiding the exhaustive search procedure used by the current state-of-art approaches. We experimentally show that our approach allows the generation of a compact set of CNs that results in superior quality answers and demands less resources in terms of processing time and memory.

We present a strategy to improve an evolutionary process related to a hybridization of a genetic algorithm, strongly based on local search, for the weighted tardiness and Just-in-Time scheduling problems without idle time. The presented solutions represent a schedule in identical parallel machines that are indirectly encoded in a single sequence. An empirical analysis of these features is presented, by comparing this method with the previously one proposed, results from the literature, and also with an exact method, based on an IP formulation, for smaller instances, also proposed by the authors. With the proposed improvements, it was possible to solve larger instances up to 300 jobs and 2-20 parallel machines.

In this paper we present a correlation between a variation of the list problem coloring in graphs, the (γ, μ)-coloring, and the property of choosability in graphs, resulting in the k-(γ, μ)-choosability. The list coloring problem is a variation of the classical vertex coloring problem, introduced by Erdos et al. in 1979, along with a property very studied in list coloring: the choosability in graphs. In this work, algorithms were developed to determine the k-choosability and the k-(γ, μ)-choosability of a general simple graph, and a greedy heuristic based on DSATUR. In addition, we applied special techniques to prove the property of choosability in some classes of graphs, involving a general proof for simple graphs, which guarantees that if a graph is k-colorable it is also k-(γ, μ)-choosable, being the computational complexity reduced from the class Πp2-complete to the NP-complete.

The problem of estimating the full three-dimensional structure of a molecule, determining the position in space of all the atoms that compose it, is called Molecular Distance Geometry Problem (MDGP). To do this from an incomplete set of distances is NP-hard computational problem, where to get a feasible solution in a reasonable execution time presenting interesting mathematical and computational challenges. In this work, continuous and discrete mathematical approaches to solve MDGP is revised, based on the analysis of two types of calculating of sphere intersection: solving nonlinear systems from interatomic Euclidean distance equations, or solving internal coordinate systems using matrix multiplication techniques. We adapted the Branch-and-Prune (BP) method considering four spheres intersection. Computational experiments using instances from PDB benchmark are performed, determining the 3D structure based on our theoretical assumptions in a competitive computational processing time.