A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: progress and prospects

Applied Intelligence - The17 Sustainable Development Goals (SDGs) established by the United Nations Agenda 2030 constitute a global blueprint agenda and instrument for peace and prosperity...     

Algorithms for processing the group K nearest-neighbor query on distributed frameworks

Distributed and Parallel Databases - Given two datasets of points (called Query and Training), the Group (K) Nearest-Neighbor (GKNN) query retrieves (K) points of the Training with the smallest sum...     

Does maintainability relate to the energy consumption of software? A case study

Software Quality Journal - Energy consumption of software has been becoming increasingly significant, since it can vary according to how the software has been developed. In recent years, developers...     

The GPU on the simulation of cellular computing models

Membrane Computing is a discipline aiming to abstract formal computing models, called membrane systems or P systems, from the structure and functioning of the living cells as well as from the cooperation of cells in tissues, organs, and other higher order structures. This framework provides polynomial time solutions to NP-complete problems by trading space for time, and whose efficient simulation poses challenges in three different aspects: an intrinsic massively parallelism of P systems, an exponential computational workspace, and a non-intensive floating point nature. In this paper, we analyze the simulation of a family of recognizer P systems with active membranes that solves the Satisfiability problem in linear time on different instances of Graphics Processing Units (GPUs). For an efficient handling of the exponential workspace created by the P systems computation, we enable different data policies to increase memory bandwidth and exploit data locality through tiling and dynamic queues. Parallelism inherent to the target P system is also managed to demonstrate that GPUs offer a valid alternative for high-performance computing at a considerably lower cost. Furthermore, scalability is demonstrated on the way to the largest problem size we were able to run, and considering the new hardware generation from Nvidia, Fermi, for a total speed-up exceeding four orders of magnitude when running our simulations on the Tesla S2050 server.     

Effect of breed-type on the relationships between intramuscular and total body fat in steers

The partitioning of total dissectible body fat and the amounts of intramuscular fat in Psoas major, Semitendinosus and Biceps brachii muscles were determined in two groups of A. Angus and AA × Nelore steers with similar averages of total dissectible fat (27·7 kg). In addition, the fatty acid composition of total fat and the triglyceride fraction from dissectible and intramuscular fats were determined.

The AA × Nelore steers have higher levels of subcutaneous fat and lower levels of intermuscular fat than the A. Angus but contain lower levels of intramuscular fat in the three muscles. The allometric regressions varied according to the muscle and breed type. The fatty acid composition of subcutaneous and kidney fats were similar but differences in the percentages of 14:0, 18:0, 18:2 and 20:4 fatty acids in intramuscular fats between the two genetic groups were detected.     

A comparison of distribution and composition of intramuscular fat in Duroc Jersey and Hampshire pigs at 100 kg liveweight

The intramuscular fat content, its fatty acid composition and that from the triglyceride fraction, were determined in several muscles from the right sides of four Duroc Jersey and four Hampshire castrated male pigs slaughtered at 100 kg liveweight. The Hampshires had heavier muscles than the Duroc Jersey pigs, but did not show significant differences in the percentages of intramuscular fat. The concentrations of linoleic acid were, in general, higher in the Hampshire than in the Duroc Jersey pigs and in many muscles the differences were highly significant (p < 0·05) The concentrations of linoleic acid (18:2) in the triglyceride fraction did not differ among muscles within breeds but were higher in Hampshire than in Duroc Jersey pigs.     

A study of behavioural groupings of polyphenolic species in "fino" sherry wine. Evolution during vinification and mechanical treatment of the grape

The different groups and/or classes among phenolic acids and aldehydes identified during the elaboration process of "fino" sherry wine have been studied. The study was carried out using different processes during the elaboration of the wine and we have attempted to establish whether the different treatments of the grape affect these groupings. The study was undertaken by means of cluster and multifactorial analysis on the data obtained by the quantitative determination of phenolic acids and aldehydes during vinification and in experiments carried out on the grape under different mechanical treatments. The analysis of phenolic acids and aldehydes was done with HPLC, using a C-18 mu-Bondapak and a stepwise composite gradient. The samples were previously extracted with ethylic ether.     

Application of the classical levels of intelligence to structuring the control system in an automated distribution centre

Traditional management and control models can benefit from added levels of intelligence to increase their capability to adapt to the continuous changes in global markets. After reviewing the classical definition of intelligence and its levels, this paper provides a new approach to help increase the responsiveness of management and control to changes and disturbances in the manufacturing supply chain. The ancient concept of the “Tertium Quid” has inspired a three-level community of agents (MAS-TRIO) that is proposed to improve the coordination of all actors involved. The proposed model combines Multi-Agent Systems (MAS) with Radio-Frequency Identification (RFID) to make possible a certain level of Autonomous Intelligence in the decision-taking process. This paper analyses how these levels of intelligence can be applied to management and control, and the performance of the proposed model has been tested at low and mid-levels on an experimental platform representing the facilities of a distribution centre controlled by a network of programmable logic controllers (PLCs).     

PMMA‐modified divinylester/styrene resins: Phase diagrams and morphologies

Binary and ternary experimental cloud‐point curves (CPCs) for systems formulated with a low molar mass synthesized divinylester (DVE) resin, styrene (St), and poly(methyl methacrylate) (PMMA) were determined. The CPCs results were analyzed with the Flory–Huggins (F‐H) thermodynamic model taking into account the polydispersity of the DVE and PMMA components, to calculate the different binary interaction parameters and their temperature dependences. The St‐DVE system is miscible in all the composition range and down to the crystallization temperature of the St; therefore, the interaction parameter expression reported for a higher molar mass DVE was adapted. The interaction parameters obtained were used to calculate the phase diagrams of the St‐PMMA and the DVE‐PMMA binary systems and that of the St‐DVE‐PMMA ternary system at three different temperatures. Quasiternary phase diagrams show liquid–liquid partial miscibility of the St‐PMMA and DVE‐PMMA pairs. At room temperature, the St‐DVE‐PMMA system is miscible at all compositions. Final morphologies of PMMA‐modified cured St‐DVE materials were generated by polymerization‐induced phase separation (PIPS) mechanism from initial homogeneous mixtures. SEM and TEM micrographs were obtained to analyze the generated final morphologies, which showed a direct correlation with the initial miscibility of the system. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 4539–4549, 2006     

A GPU implementation of a hybrid evolutionary algorithm: GPuEGO

The high computation requirements of global optimization algorithms, when used to solve real optimization problems, have caused the appearance of different parallelization strategies using several parallel computing architectures. In this work, the Universal Evolutionary Global Optimizer is implemented in CUDA to be run on GPU architectures (GPuEGO). This parallelization of the referred evolutionary multimodal optimization algorithm is rather different from other previous parallel implementations designed to be executed into shared or distributed memory processors. In this case, due to the special characteristics of a GPU architecture, the original data structures are not valid and it has been necessary to redefine them and all the functions that operate with them. When this approach is applied the acceleration factors achieved by GPuEGO range from \({\times }\) 6.33 to \({\times }\) 23.20 depending on the test function.