IEEE Latin America Transactions Journal Impact Factor & Information

Publisher: Institute of Electrical and Electronics Engineers. Region 9, Institute of Electrical and Electronics Engineers

Journal description

Current impact factor: 0.33

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 0.326
2013 Impact Factor 0.186
2012 Impact Factor 0.218
2011 Impact Factor 0.346

Impact factor over time

Impact factor

Additional details

5-year impact 0.32
Cited half-life 3.20
Immediacy index 0.05
Eigenfactor 0.00
Article influence 0.05
Website Latin America Transactions, IEEE website
Other titles Revista IEEE América Latina, Revista do IEEE América Latina, Revista del IEEE América Latina, IEEE Latinamerica transactions, IEEE Latin America transactions, Transactions IEEE Latin America
ISSN 1548-0992
OCLC 53988421
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Institute of Electrical and Electronics Engineers

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Author's pre-print on Author's personal website, employers website or publicly accessible server
    • Author's post-print on Author's server or Institutional server
    • Author's pre-print must be removed upon publication of final version and replaced with either full citation to IEEE work with a Digital Object Identifier or link to article abstract in IEEE Xplore or replaced with Authors post-print
    • Author's pre-print must be accompanied with set-phrase, once submitted to IEEE for publication ("This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible")
    • Author's pre-print must be accompanied with set-phrase, when accepted by IEEE for publication ("(c) 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.")
    • IEEE must be informed as to the electronic address of the pre-print
    • If funding rules apply authors may post Author's post-print version in funder's designated repository
    • Author's Post-print - Publisher copyright and source must be acknowledged with citation (see above set statement)
    • Author's Post-print - Must link to publisher version with DOI
    • Publisher's version/PDF cannot be used
    • Publisher copyright and source must be acknowledged
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: This paper presents an overview of DERIVEX, the new Colombian market for standardized derivatives of energy commodities. With the aim of understanding the market operation in context and the sources of electricity price variability, this work presents: first, a disscusion the main physical characteristics of the electricity system; next, the operation of the energy market; and finally, the operation of DERIVEX
    IEEE Latin America Transactions 08/2015; 13(7). DOI:10.1109/TLA.2015.7273774
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    ABSTRACT: In nonlinear time series forecasting, neural networks are interpreted as a nonlinear autoregressive models because they take as inputs the previous values of the time series. However, the use of neural networks to forecast nonlinear time series with moving components is an issue usually omitted in the literature. In this article, we investigate the use of traditional neural networks for forecasting nonlinear time series with moving average components and we demonstrate the necessity of formulating new neural networks to adequately forecast this class of time series. Experimentally we show that traditional neural networks are not able to capture all the behavior of nonlinear time series with moving average components, which leads them to have a low capacity of forecast.
    IEEE Latin America Transactions 07/2015; 13(7):2292-2300. DOI:10.1109/TLA.2015.7273790
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    ABSTRACT: The agricultural commodities are important to economies of several countries, especially in Brazil. Despite the amount of money involved, as knows that in agribusiness activities do not have accurate information in all the process. Therefore some research centers in Brazil, such as Center for Advanced Studies on Applied Economics - CEPEA, collect and provide daily price indices of these commodities, on several agricultural products, and spread information to these researchers markets, producers and formulators public policy. The idea is to understand the evolution and pattern for the time series of Grains price indices for seven years. The aim of this paper is find common patterns on time series, i.e. highlight events that happens frequently over seven year of daily grain prices quotation in several products. The results give a understanding of the dynamic of these grains time series, such as, Some important aspects were detect was this products competes in fields for crops
    IEEE Latin America Transactions 07/2015; 13(7):2329-2334. DOI:10.1109/TLA.2015.7273795
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    ABSTRACT: This paper presents the design and implementation of a subvocal speech pattern recognition system using only one EMG channel. The objective of the system is, after being trained, to identify and classify limited-vocabulary sets of speaker-dependent Spanish words. First we present the EMG signal acquisition board designed and constructed for this end. Then, we describe the preprocessing stage where denoising and activity detection occurs. Then the various feature spaces representations alongside the different candidate classifiers are explained and compared; we obtained the best results using a filter bank analysis followed by cumulative residual entropy (CRE) profile and a Support Vector Machine (SVM) classifier. For testing, we considered two possible application of this type of systems: confidential communications and voice recognition in high acoustic noise environments. For both a vocabulary made up of six words was tested, and the latter was tested while simulating fire noise and also compared to a vocal speech system. The performance of both applications was evaluated on two groups of four-subject with no speech disorders, obtaining mean F1-Scores of 91.32 % and 90.83 % respectively.
    IEEE Latin America Transactions 07/2015; 13(7):2135-2143. DOI:10.1109/TLA.2015.7273769
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    ABSTRACT: This paper presents a pedestrian detection system in non-controlled environments based on sliding windows. Systems of this type are based on two major blocks: one for feature extraction and other for window classification. Two techniques for feature extraction are used: HOG (Histogram of Oriented Gradient) and CSS (Color Self Similarities), and to classify windows we use linear SVM (Support Vector Machines). Beyond these techniques, we use mean shift and hierarchical clustering to fuse multiple overlapping detections. To improve the system performance, each descriptor is separately classified using an assemble of SVMs. The results obtained on the dataset INRIA Person show that the proposed system, using only HOG descriptors, achieves better results over similar systems. These results were possible due to the cutting of the final detections to better adapt them to the modified annotations, and some modifications on the parameters of the descriptors. The addition of the modified CSS descriptor to the HOG descriptor increases the efficiency of the system, leading to a log average miss rate equal to 36.2%, when classifying each descriptor separately.
    IEEE Latin America Transactions 07/2015; 13(7):2416-2422. DOI:10.1109/TLA.2015.7273807
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    ABSTRACT: Market segmentation is a vital part of an organization's marketing because it provides a convenient way for the development of services, strategies and differentiated positioning. This study uses an approach that combines the Self-Organizing Maps of Kohonen (SOM) with the technique of Structural Equation Modeling (SEM) in the application of a segmentation issue in the Brazilian mobile marketing, one of the most competitive in the world. A model of satisfaction in mobile communications is used with the SEM to examine the moderation effects on customer segments. The results show that the combination of the techniques was found to be an adequate validation of the segmentation with structural models, being investigated various demographic, socioeconomic and behavioral factors of the customers. Furthermore, it was found that the moderating effect of the segmentation performed can affect the assessment of the overall satisfaction, especially the relationship with their background, quality, value and image.
    IEEE Latin America Transactions 07/2015; 13(7):2390-2397. DOI:10.1109/TLA.2015.7273803
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    ABSTRACT: State estimation is the primary tools for Energy Management Systems (EMS). Traditional state estimation data are measured SCADA systems which are rather low precision and do not include voltage angles measurements. This paper reports on the implementation of a state estimation algorithm able to incorporate both SCADA and PMU measurements. The implemented algorithm was validated using two well-known IEEE test systems (IEEE-14 and IEEE-118 buses). Analysis of the results obtained from the different case studies performed, may highlight some advantages of incorporating PMU's measurements in the power system state estimation.
    IEEE Latin America Transactions 07/2015; 13(7):2245-2251. DOI:10.1109/TLA.2015.7273784
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    ABSTRACT: Artificial Neural Networks (ANNs) competence in generalization and reconfigurable hardware using provide a solid base to developing critical embedded systems, capable of efficiently adapt itself as requirements change. Different level adaptation, from physical level up to system level, can be combined to provide efficient solutions using FPGA. So, this work aims to define a novel architecture to configure ANNs topologies using partial FPGA reconfiguration. NEURON block has been described using fixed-point notation and applying partial reconfiguration to load partial bitstreams of sigmoid and hiperbolic tangent functions, as well as dynamically inserting and removing NEURON blocks on the net, this way it is possible to configure MultiLayer Perceptron (MLP) networks with different topologies, using partial bitstreams in reconfigurable areas. It is conceived that, using this kind of hardware facilitates embedding applications using different topologies, MLP ANNs, easily reconfigurable on the field.
    IEEE Latin America Transactions 07/2015; 13(7):2094-2100. DOI:10.1109/TLA.2015.7273763
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    ABSTRACT: We address the multidimensional characterization of difficult instances of the Bin Packing Problem, well known in the combinatorial optimization realm. In search for efficient procedures to solve hard combinatorial optimization problems previous investigations have attempted to identify the instances' characteristics with the greatest impact in their difficulty. In the same vein and focusing on the Bin Packing Problem, we used clustering techniques to determine not only one but a set of characteristics that altogether could be considered as the main source of the instances difficulty. To this aim we selected 1,615 available instances of the Bin Packing Problem, and then we solved each instance with six well-known heuristic algorithms. From our experiment we identified relevant characteristics that correspond to 22 instances whose optimal solution was not obtained by any of the six heuristics. Finally, to validate our findings an adhoc heuristic based on these characteristics was developed. Our heuristic found two optimal solutions not previously reported, showing thus that this characterization can help to find improved solution algorithms.
    IEEE Latin America Transactions 07/2015; 13(7):2454-2462. DOI:10.1109/TLA.2015.7273812
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    ABSTRACT: Web 2.0 phenomenon, REST services and growing mobile service consumption, among other factors, are leading the development of web applications to a new paradigm, named cross-device web application. Those web sites let organizations of all sizes provide a pervasive and contextual access to their information and services, to customers, employees and partners via potentially any kind of device. Most organizations often possess legacy systems that should face an ongoing evolution process to enhance its accessibility and interoperability. Yesterday they had to evolve to provide the user with a Web layer, and now they should evolve again to adapt to the new ways of data and services consumption on the Web. In such scenario, REST services play a key role, defining the interaction layer between the legacy system and all its heterogeneous front ends. This work presents a model-driven approach to derive a REST service layer from a legacy web application within the frame defined by a modernization process. This approach departs from a conceptual model of the legacy application generated by reverse engineering techniques. In this work we detail the generation process and provide a sample implementation instrumenting one of the studied web development frameworks to evaluate the suitability of the approach.
    IEEE Latin America Transactions 07/2015; 13(7):2379. DOI:10.1109/TLA.2015.7273801
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    ABSTRACT: The wind energy generation is the huge driver behind the push for supergrids and cross-border infrastructure for renewable energy systems into smart grids. To provide balance supply, demand, and storage of energy over a region in a much more efficient manner than it is done today, smart grids will need to use an advanced communication infrastructure into a robust control system. Towards this objective, it is proposed in this work a wireless coded power control employing low density parity check coding for a switched reluctance machine applied in wind generation to improve system robustness and reliability. The performance improvements of the proposed system are investigated in a more realistic frequency selective fading propagation condition.
    IEEE Latin America Transactions 07/2015; 13(7):2048-2056. DOI:10.1109/TLA.2015.7273757
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    ABSTRACT: Devices with wireless receptors are common to the world's reality. Location based services (LBS) are becoming popular by taking advantage of the GPS positioning of the mobile devices, and sharing the positioning information with people. But there is nothing that can be done to, with the actual technology, enable the use of the GPS signal inside buildings and structures. The main purpose of this article is to investigate the viability of an environment oriented location approach, based on the wireless signals strengths indicators fingerprint. It was verified that the wireless fingerprint have standards signals for different house rooms. The use of the wireless signal strength fingerprint for the main purpose of this paper is possible.
    IEEE Latin America Transactions 07/2015; 13(7):2043-2047. DOI:10.1109/TLA.2015.7273756
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    ABSTRACT: The nearest neighbour (KNN) supervised classification technique is widely known and used. This technique can be expensive computationally for some applications. In order to improve KNN in relation to the time required for the classification, is proposed an adaptation using Adaptive simulated annealing, a heuristic method inspired by heat treatment, in order to determine similar samples. The modified technique was evaluated with classification problems that are present in the database UCI. The datasets are evaluated in some parameters, these are compared with the results in time and accuracy to explain the behavior of the results. At end is demonstrated that the method reduces the total execution time and its efficiency is comparable with the KNN algorithm based on partitioning trees in datasets with some restrictions
    IEEE Latin America Transactions 07/2015; 13(7):2398-2404. DOI:10.1109/TLA.2015.7273804
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    ABSTRACT: This paper proposes the use of the K-modes algorithm to classify according to its characteristics, user's interfaces in order to provide to the developer a recommendation system where elements such as interaction devices, kinds of users, standards, and other factors are described according to their application domain. Twelve specific cases are considered which are characterized using FODA. Also, the SPSS statistical analysis software is used to validate that the resulting classification is well grouped.
    IEEE Latin America Transactions 07/2015; 13(7):2308-2313. DOI:10.1109/TLA.2015.7273792