Optimal Design of V-Shaped Fin Heat Sink for Active Antenna Unit of 5G Base Station

The active antenna unit (AAU) is one of the main parts of the 5G base station, which has a large size and a high density of chipsets, and operates at a significantly high temperature. This systematic study presents an optimal design for the heat sink of an AAU with a V-shaped fin arrangement. First, a simulation of the heat dissipation was conducted on two designs of the heat sink – in-line and V-shaped fins – which was validated by experimental results. The result shows that the heat sink with V-shaped fins performed better compared to conventional models such as heat sinks with in-line fins. Secondly, computational fluid dynamics (CFD) and the Lagrange interpolation method were applied to find out an optimal set of design parameters for the heat sink. It is worth noting that the optimal parameters of the orientation angle and fin spacing considerably affected the heat sink’s performance.  

Optimal Design of V-Shaped Fin Heat Sink for Active Antenna Unit of 5G Base Station

The active antenna unit (AAU) is one of the main parts of the 5G base station, which has a large size and a high density of chipsets, and operates at a significantly high temperature. This systematic study presents an optimal design for the heat sink of an AAU with a V-shaped fin arrangement. First, a simulation of the heat dissipation was conducted on two designs of the heat sink – in-line and V-shaped fins – which was validated by experimental results. The result shows that the heat sink with V-shaped fins performed better compared to conventional models such as heat sinks with in-line fins. Secondly, computational fluid dynamics (CFD) and the Lagrange interpolation method were applied to find out an optimal set of design parameters for the heat sink. It is worth noting that the optimal parameters of the orientation angle and fin spacing considerably affected the heat sink’s performance.  

An enhanced nodal gradient finite element for non-linear heat transfer analysis

The present work is devoted to the analysis of non-linear heat transfer problems using the recent development of consective-interpolation procedure. Approximation of temperature is enhanced by taking into account both the nodal values and their averaged nodal gradients, which results in an improved finite element model. The novel formulation possesses many desirable properties including higher accuracy and higher-order continuity, without any change of the total number of degrees of freedom. The non-linear heat transfer problems equation is linearized and iteratively solved by the Newton-Raphson scheme. To show the accuracy and efficiency of the proposed method, several numerical examples are hence considered and analyzed

Applying Improve Differential Evolution Algorithm for Solving Gait Generation Problem of Humanoid Robots

This chapter addresses an approach to generate 3D gait for humanoid robots. The proposed method considers gait generation matter as optimization problem with constraints. Firstly, trigonometric function is used to produce trial gait data for conducting simulation. By collecting the result, we build an approximation model to predict final status of the robot in locomotion, and construct optimization problem with constraints. In next step, we apply an improve differential evolution algorithm with Gauss distribution for solving optimization problem and achieve better gait data for the robot. This approach is validated using Kondo robot in a simulated dynamic environment. The 3D gait of the robot is compared to human in walk

Optimization Procedure for Planar Leaky-Wave Antennas With Flat-Topped Radiation Patterns

International audienceWe describe here an optimization procedure to shape the radiation pattern of planar two-dimensional (2-D) leaky-wave antennas. The structures under investigation are superstrate configurations made by partially reflecting screens (impedances sheets) over a ground plane and excited by open-ended waveguides. The antenna configuration providing the required radiation pattern is obtained by resorting to an ad hoc optimization procedure that minimizes the mean squared error between the target pattern and the actual radiated far field. The radiated field is analytically evaluated using a Green's function spectral approach to speed up the optimization process. Several kinds of radiation patterns can be obtained using the proposed algorithm. In this work, we focus our attention on flat-topped radiation patterns, suitable as element pattern for phased array antennas covering a limited angular field of view such as those considered for space applications. The proposed procedure is validated by full-wave results and measurements

Educating and training labor force Under Covid 19; Impacts to Meet Market Demand in Vietnam during Globalization and Integration Era

During integration and globalization era, Vietnam labor market face challenges but also have lots of opportunities. This paper mainly use qualitative analysis with statistics, synthesis and inductive methods, combine with dialectical materialism methods. Research results indicate that because many Vietnam laborers do not have enough work skills and lack of training programs, they meet difficulties on job; hence, human resource management need to deal with issues of improving skills and knowledge for workforce to meet demand under EVFTA and Industry 4.0. There are lots of job opportunities from banking, finance to manufacturing, industries. Last but not least, this study also propose some solutions to deal with challenges in Human resources to meet demand from corporations. For instance, we need to invest more on equipment and infrastructures, as well as quality of trainers for human resources of training schools, so that Vietnam businesses can overcome challenges from EVFTA

Gene Family Abundance Visualization based on Feature Selection Combined Deep Learning to Improve Disease Diagnosis

Advancements in machine learning in general and in deep learning in particular have achieved great success in numerous fields. For personalized medicine approaches, frameworks derived from learning algorithms play an important role in supporting scientists to investigate and explore novel data sources such as metagenomic data to develop and examine methodologies to improve human healthcare. Some challenges when processing this data type include its very high dimensionality and the complexity of diseases. Metagenomic data that include gene families often have millions of features. This leads to a further increase of complexity in processing and requires a huge amount of time for computation. In this study, we propose a method combining feature selection using perceptron weight-based filters and synthetic image generation to leverage deep-learning advancements in order to predict various diseases based on gene family abundance data. An experiment was conducted using gene family datasets of five diseases, i.e. liver cirrhosis, obesity, inflammatory bowel diseases, type 2 diabetes, and colorectal cancer. The proposed method provides not only visualization for gene family abundance data but also achieved a promising performance level

The Role of Social Network Sites in English Language Teaching_Harnessing the Potential of Facebook and YouTube as Learning Tools

This paper provides a comprehensive review of the role of Social Network Sites (SNSs) in the context of English as a Second Language (ESL) and English as a Foreign Language (EFL) teaching and learning. It examines the definitions and potential applications of SNSs, with a specific focus on Facebook and YouTube. The paper discusses the educational and instructional implementations of these SNSs, as well as the challenges and drawbacks faced by both teachers and students when utilizing them. Furthermore, it explores the pedagogical implications of incorporating the cutting-edge features offered by SNSs, aiming to bridge the gap between traditional and technologically driven learning environment

Bioefficacy of leaf extracts from Pouzolzia zeylanica (L.) Benn against diamondback moth plutella xylostella in Viet Nam

In Viet Nam, Pouzolzia zeylanica (L.) Benn is a native plant and has been demonstrated its applicability as a medical plant. Additionally, Pouzolzia zeylanica was used to control fly larvae during food processing due to insecticidal activity. We optimized the extraction of Pouzolzia zeylanica by ethanol at different conditions: concentration, the ratio of solid (material) - liquid (ethanol volume) (mg/ml) and the extraction time (hour). Results indicated that extraction yield was effected by all of the factors. The optimized extraction yield was 6.85% (Y) with ethanol concentration at 96 percent ethanol (Z1), the ratio solid to liquid is 1: 25 (mg/ml) (Z2) and extraction time is 4 days (Z3). We tested the efficiency of leaf extracts from Pouzolzia zeylanica and antifeedant activity against diamondback moth Plutella xylostella at different leaf extract concentrations. Results indicated that 80% mortality induced by those compounds was recorded on Plutella xylostella second instars at 30% leaf extract concentration and had significant difference compared to the control (P=0.0000); the leaf extract affected the ratio of pupation, adult emergence and antifeedant activity of P. xylostella (P=0.0000). The obtained results promise a potential of using Pouzolzia zeylanica as biopesticide in Viet Nam

Phenomenology of the Reduced Minimal 3-3-1 Model

The detailed analysis of the gauge model based on $\mathrm{SU}(3)_C\otimes \mathrm{SU}(3)_L \otimes \mathrm{U}(1)_X$ group with minimal content of lepton and Higgs is presented. It is shown that with just two Higgs triplets, all fermions and gauge bosons can get correct   masses. The advantage of the model under consideration is that a huge number of free parameters is reduced, and the model's predictiveness is much improved