Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

Objective: Restrictions, this research article is carried out with the purpose of identifying the physical and political restrictions that exist in the IPS of the Special, Industrial and Port District of Barranquilla, Atlántico, Colombia. Methodology: For the development of the study, an instrument for collecting information was designed based on scale type questions, addressed to a sample of 149 IPS in Barranquilla. Results: The results of the study show that the most important physical constraints in the IPS have to do with infrastructure, raw materials and human capital; While political constraints focus on relationships of vertical authority, difficulties in measuring the effectiveness and efficiency of processes, and problem|s regarding collaborative and interpersonal labor relations.  Conclusions: The problems of productivity and competitiveness of the IPS, do not lie exclusively in the late payment of the EPS or ARL, but in the difficulties in the management caused by limitations or physical and political restrictions.

Objective: To use computational techniques for removing rain from images. This is motivated by the fact that for many computer vision systems, correctly capturing the scene is a key need, and if such systems receive images degraded by rain as input, their performance may be compromised.  Methodology: We built a dataset comprised by 11000 synthetic rain images. We resized and normalized all the images, then we employed 9000 of them for training the autoencoder architecture. The autoencoder outputs a de-rained version of the image which is then lighting corrected in order to produce the final, de-rained image. Results: We determined the best autoencoder architecture was a 6-layer autoencoder. We evaluated it on the remaining 2000 images, resulting in a Mean Squared Error of 0.61 and Structural Similarity Index of 0.8493, which means a fair amount of information from the rain-degraded images was recovered. Conclusions: The results we obtained were superior to proposals based in the spatial / frequency domain reported in the literature. However, we determined that it is possible to improve on the current results if we consider the frequency domain as part of the architecture. Thus, options for future work include combining machine learning-based approaches with frequency domain-based image processing.

Objective: To build a robotic system for exploration and mapping of indoor working environments with our own architecture and design methodology. Methodology: We defined an architecture and a design methodology for both the hardware and the logical levels. At the logical level, we used an environment representation based in occupancy cells and a behavior-based control architecture which was implemented through fuzzy control. Results: The robotic platform was tested in structured scenarios such as corridors and rooms. The effectivity of the platform could be verified using maps constructed with an application developed in Matlab.  Conclusions: We demonstrated the ability of the robotic platform of constructing maps of its environment explicitly, which although could result computationally demanding, allows a precise and comprehensive representation.

Objective: To analyze the efficiency of gelatin obtained from a sacrifice waste mixed with aluminum sulfate and used in water clarification processes.  Methodology: Water from the Malambo swamp was analyzed for a study and a simple sampling was conducted for its collection. A jug test was conducted using doses of 10, 20, 40, 60, 80, and 100 mg/L of a 9:1 ratio gelatin–aluminum sulfate mixture and the aluminum sulfate as specified in NTC 3903 of 2010. Results: The gelatin–aluminum sulfate mixture removed 82.63% of the turbidity of the water analyzed, while the chemical coagulant removed 83.25% of the turbidity.  Conclusions: The coagulant mixture proposed in this research shows clarification properties very close to those used commercially, which boosts its potential for use.

Objective: This work proposes and evaluates a technology for improving heavy crude oil mobility through the addition of magnetic nanoparticles and external electromagnetic fields.  Methodology: The study first individually characterizes heavy crude oil, magnetite nanoparticles, and magnetic graphene. Then, the magneto-rheological behavior of heavy crude oil and its mixtures with nanoparticles and magnetic graphene assessed using 0.5 to 10 wt.% compounds. Subsequently, these mixtures were subjected to electromagnetic radiation within the microwave range at different radiation times to achieve different compositions. These treatments were conducted in an electromagnetic cavity using a cylindrical waveguide with powers ranging between 0.8 and 1 kW. Results: Initially, the crude oil did not respond to the electromagnetic radiation treatment as it is transparent to this treatment. However, after adding magnetic nanoparticles, comprising both magnetite and magnetic graphene, the mixture strongly interacted with the electromagnetic field. The higher the concentration of these particles, the greater the temperature increase experimented by the mixture. For the experiments in the electromagnetic cavity, an increase from the original temperature of 22°C to the 58.2°C–60°C range was evidenced in 60 s for the magnetite at a 0.5 wt.% concentration. For experiments using the cylindrical waveguide as an applicator at the same previous experimental conditions, temperatures above 90°C were reached. Using magnetic graphene and the same electromagnetic cavity, temperatures between 81.9°C and 96.5°C were reached. Conclusions: Both materials notably increased heavy crude oil heating rates (decreasing its viscosity), when subjected to electromagnetic radiation within the microwave range. In fact, both materials can be considered as candidates for improving crude oil extraction and transportation processes.

Objective: Structure a method to analyze the adoption and use of Information and Communication Technologies-ICT in 7542 companies in the Colombian manufacturing sector. Methodology: For this research, the multivariate analysis of conglomerate and discriminant techniques were applied, and the results of the annual manufacturing survey of the National Administrative Department of Statistics of Colombia for 2017 were applied. A cluster analysis was applied to identify characteristic profiles in the adoption and use of ICT, then the ability of the analyzed variables to correctly classify the manufacturing companies in the profiles identified was evaluated. Results: The results show that the model correctly classifies the ICT profiles of the analyzed sector in 94.4%.  Conclusions: The application of the method allowed to contrast the discriminant capacity of the variables to identify characteristic profiles that were significantly homogeneous intra-groups and heterogeneous extra-groups.

Objective: To obtain an analytical model that can determine the index of organizational development in the management of higher education institutions.  Methodology: The methodology used was an epistemological, descriptive, and explanatory approach. Results: The analysis identifies the components that prioritize possible organizational management alternatives by quantifying the most significant indicators obtained from the experimental field study to analyze the variables of strategic thought and competitiveness. In the statistical process, the indicators that constitute the analysis of the main components are obtained, from which five factors stand out, representing 86.386% in the case of the Francisco de Paula Santander University and 75.02% for the University of Pamplona of the total variance explained using a combination of the two sets of variables.  Conclusions: The mathematical results represent the perception of the governance system of higher education institutions that reflects the need to implement leadership strategies that allow a more holistic understanding of the environment to improve competitiveness through the reinvention of institutional policies based on marketing, the supply of new services, innovation, quality, and efficiency as instruments of differentiation.

Objective: Identify the stability behavior of transtibial amputees and examine the relationship and differences between amputees and non-amputees in static postural stability. Maintaining the standing position requires simultaneous control of posture in both directions, anteroposterior (AP) and medial-lateral (ML). The address of the most affected CoP was verified.  Methodology: Nine individuals with unilateral transtibial limb loss, and nine healthy controls completed a series of static upright measurements. The body metrics of linear analysis, e.g. Excursion, Velocity, Range and Mean, and nonlinear analysis, e.g. Discrete Wavelet Transform (DWT) and its relative energy (RWE), were compared between groups. Results: The U Mann-Whitney test with significance of 0.05 to compare measurements between groups was used. Healthy people exhibited regular increase in postural balance compared to people with prostheses, the variation occurred mostly in the anteroposterior direction. The concentration of energy in the levels was different between the groups. Conclusions: The behavior of postural stability allows to know the level of adaptability of the prosthesis; there is a difference in the variability of the displacement and velocity of the CoP between the groups; due to the loss of bone and muscular structures, the amputees constantly alter the location of the CoP as a strategy to maintain stability, hence the energy levels are in ranges greater than those of non-amputees.

Objective: To design and develop a discrete event simulation model for the customer service process of an SME dedicated to the fast food business to conduct experiments aimed at understanding system behavior and evaluating optimization strategies.  Methodology: The procedure is classified in four stages: (I) Analysis of the company and definition of the problem; (II) Description of processes and contextualization of a model; (III) Generation of the preliminary model, verification, validation, and sensitivity analysis; (IV) Analysis of results and improvement proposals. Results: The modeling enabled us to suggest a series of optimizations for the processes and the analyzed SME, which would result in the reduction of waiting times in the sale of drinks, pizzas, and other products.  Conclusions: It was proven that through tools such as Simul8®, it is possible to easily model processes and suggest relevant optimizations for them, although it should be noted that the tool is not as effective for service modeling.

Objective: Identify computational technologies that are being used in the automatic identification and selection of sites for small hydroelectric power plants.  Methodology: Systematic searches of scientific articles, conference papers, indexed journals, and engineering books in databases of bibliographic references were conducted, allowing an exploratory and analytical review for the collection of significant information about the technologies used in the automatic location of this type of projects. Results: This review established that the Big Data for geospatial data analysis, grouping algorithms, multi-criteria decision-making methodologies, and visual analysis of data are directly involved in the automatic location of small hydropower plants. Conclusions: In Latin America, some research can be found on the automatic site selection for small hydropower plants. However, Colombia has not yet published studies of this type in main scientific journals and databases of bibliographic references. Similarly, less than 10% of the papers examined in this research have been written in this region of the continent.