Grouped Approach for the Design of H.264/AVC Motion Estimation Architectures

This letter presents a novel approach for organizing computational resources into groups within H.264/AVC motion estimation architectures, leading to reductions of up to 75% in the equivalent gate count with respect to state‐of‐the‐art designs.     

Organizational determinants of IT adoption in the pharmaceutical distribution sector

The aim of this paper is to propose new organizational factors that might explain the differences in the extent and the speed of IT adoption. With this in mind, we carried out an analysis of 16 cases in the pharmaceutical distribution sector in Spain. The results indicate that there are certain intangible assets that favour the introduction and development of IT. Among these are a frank and fluid communication between departments and members of the organization, low levels of conflict, the explicit support of top management towards IT adoption and learning and creative skills of IT-staff. In addition to these factors, we found others that we propose as catalysts of IT adoption. Among these we might mention the special relationship between the member-clients and the company in the case of cooperative firms.     

Leveraging 802.11n frame aggregation to enhance QoS and power consumption in Wi-Fi networks

The Wi-Fi technology, driven by its tremendous success, is expanding into a wide variety of devices and applications. However, many of these new devices, like handheld devices, pose new challenges in terms of QoS and energy efficiency. In order to address these challenges, in this paper we study how the novel MAC aggregation mechanisms developed in the 802.11n standard can be used to enhance the current 802.11 QoS and power saving protocols. Our contribution is twofold. First, we present a simulation study that illustrates the interactions between 802.11n and the current 802.11 QoS and power saving protocols. This study reveals that the 802.11n MAC aggregation mechanisms perform better when combined with the power save mode included in the original 802.11 standard than with the 802.11e U-APSD protocol. Second, we design CA-DFA, an algorithm that, using only information available at layer two, adapts the amount of 802.11n aggregation used by a Wi-Fi station according to the level of congestion in the network. A detailed performance evaluation demonstrates the benefits of CA-DFA in terms of QoS, energy efficiency and network capacity with respect to state of the art alternatives.     

Design Optimization of Composite Prosthetic Tubes Using GA-ANN Algorithm Considering Tsai-Wu Failure Criteria

The investigation of possible failures in composite materials is a matter of very great importance, and the Tsai-Wu criterion is an effective criterion for analyzing those flaws in anisotropic materials and defining whether the material at a given load will or will not suffer structural failure. In this study, an optimization procedure is proposed to minimize the maximum value of Tsai-Wu of laminated composite tubes subject to axial loading. Artificial neural networks and genetic algorithms are chosen as optimization tools. The results of this study show that the developed algorithm converges faster. Then, the maximum Tsai-Wu value is used as the objective function and the fiber orientations are the constraints in the optimization process. The results yielded by them are compared and discussed. Optimal results are compared with respect to the usual initial design. The design approach is recommended for structures where composites are the key load-carrying members such as orthopedic prosthesis.     

Multiple instance learning for classifying students in learning management systems

In this paper, a new approach based on multiple instance learning is proposed to predict student’s performance and to improve the obtained results using a classical single instance learning. Multiple instance learning provides a more suitable and optimized representation that is adapted to available information of each student and course eliminating the missing values that make difficult to find efficient solutions when traditional supervised learning is used. To check the efficiency of the new proposed representation, the most popular techniques of traditional supervised learning based on single instances are compared to those based on multiple instance learning. Computational experiments show that when the problem is regarded as a multiple instance one, performance is significantly better and the weaknesses of single-instance representation are overcome.     

Ultrastructural characteristics of spermatogenesis in Pallas's mastiff bat, Molossus molossus (Chiroptera: Molossidae)

Despite the large number of species, their wide distribution, and unique reproductive characteristics, Neotropical bats have been poorly studied, and important aspects of the reproduction of these animals have not been elucidated. We made an ultrastructural analysis of spermatogenesis in Molossus molossus (Molossidae). The process of spermatogonial differentiation is similar to that found in other bats and is also relatively similar to that of Primates, with three main spermatogonia types: A(d), A(p), and B. Meiotic divisions proceed similarly to those of most mammals, and spermiogenesis is clearly divided into 12 steps, in the middle of the range known for bats (9-16 steps). Formation of the acrosome is similar to that known from other mammals; however, the ultrastructure of spermatozoa was found to have unique characteristics, including many wavy acrosomal projections on its surface, which seems to be specific for the family Molossidae. Comparing the ultrastructure of the spermatozoon of M. molossus with other bats already study, we observed that three characters vary: morphology of the outer dense fibers, of the perforatorium, and of the spermatozoon head. The great similarity of morphological characters between M. molossus and Platyrrhinus lineatus suggests that M. molossus is more closely related to the Phyllostomidae than to the Rhinolophidae and the Vespertilionidae.     

Robust h-index

Scientometrics - The h-index is the most used measurement of impact for researchers. Sites such as Web of Science, Google Scholar, Microsoft Academic, and Scopus leverage it to show and compare the...     

Design and behavior study of a grammar-guided genetic programming algorithm for mining association rules

This paper presents a proposal for the extraction of association rules called G3PARM (Grammar-Guided Genetic Programming for Association Rule Mining) that makes the knowledge extracted more expressive and flexible. This algorithm allows a context-free grammar to be adapted and applied to each specific problem or domain and eliminates the problems raised by discretization. This proposal keeps the best individuals (those that exceed a certain threshold of support and confidence) obtained with the passing of generations in an auxiliary population of fixed size n. G3PARM obtains solutions within specified time limits and does not require the large amounts of memory that the exhaustive search algorithms in the field of association rules do. Our approach is compared to exhaustive search (Apriori and FP-Growth) and genetic (QuantMiner and ARMGA) algorithms for mining association rules and performs an analysis of the mined rules. Finally, a series of experiments serve to contrast the scalability of our algorithm. The proposal obtains a small set of rules with high support and confidence, over 90 and 99% respectively. Moreover, the resulting set of rules closely satisfies all the dataset instances. These results illustrate that our proposal is highly promising for the discovery of association rules in different types of datasets.     

Determination of the complex permittivity of cherry,pulped, green,and roasted coffee using a planar dielectric platform and a coaxial probe between 0.3 and 6 GHz

The complex permittivity for four processing stages of coffee: coffee cherries, pulped coffee, green coffee, and roasted coffee was obtained and divided into two groups. The wet group is constituted by cherry and pulped coffee, and the dry group by green and roasted coffee. The wet group presented a dielectric constant between 64 and 43, and a loss factor between 34 and 12. The dry group has values oscillating between 1.55 and 1.1 for the dielectric constant, and 0.037 and 0.005 for the loss factor. The permittivity difference between the wet and dry groups suggests the dependence of the coffee permittivity on the water content, along with the presence of other polar compounds. A decaying response for the dielectric constant was seen, with a proportion of 30:1 from the wet to the dry group. The loss factor presents a convex response for the wet group and a constant response for the dry group with a factor of 500 to a 100:1 from the wet to the dry group. A set of 18 samples at every stage was used to estimate the moisture content by partial least squares. The Meyer and Schilz coefficient was used for these models, that resulted in prediction errors of 2.8% and 3.8% when compared to the stage mean moisture content for the wet group. The dry group resulted in errors of 21% and 89.7%. These results indicate that the complex permittivity of coffee is capable of estimating physicochemical variables as the moisture content of the beans at distinct processing stages.