A Study on Employment for Rural Laborers in the Process of Industrialization and Modernization of Vietnam

Employment and job creation are global socio-economic issues and concern every country in the world and Vietnam is no exception. Today, the concept of development is comprehensively understood and economic growth is associated with progress, social justice, poverty reduction, on the basis of creating sustainable jobs for workers. At different times, employments for workers also have different characteristics. In the dimension of this study, employment for rural laborers with the case study of Nam Dinh of Vietnam have been investigated, then some recommendations are proposed for creating more jobs for rural people. Keywords: Employment, job creation, rural employment, rural labor. DOI: 10.7176/EJBM/12-21-13 Publication date:July 31st 202

Design and performance analysis of a mechanically coupled spring compliant to out-of-plane oscillation

In this paper, a spring system symmetrically arranged around a circular plate compliant to out-of-plane oscillation is proposed. The spring system consists of single serpentine springs mutually coupled in a plane. Three theoretical mechanical models for evaluating the stiffness of the spring system are built, which are based on the flexural beam, Sigitta, and serpentine spring theories and equivalent mechanical spring structure models. The theoretically calculated results are in good agreement with numerical solutions using the finite element method, with errors less than 10% in the appropriate dimension ranges of the spring. Compared to similar spring structures without mechanical coupling, the proposed mechanically coupled spring shows advantage in suppressing the mode coupling

Effect of Silica Nanoparticles on Properties of Coatings Based on Acrylic Emulsion Resin

Effect of nanosilica size on physic-mechanical properties, thermal stability and weathering durability of coating based on acrylic emulsion. Nanocomposite coating formulas were filled by 2 wt.% nanosilica particles which were used in this study, namely: nanosilica from Sigma (15-20nm), nansilica from rice husk (~70-200 nm) and nanosilica from Arosil – Belgium (7-12 nm). Obtained results showed that viscosity flow of coating formula containing nanosilica from Arosil saw the highest flow-time while coating formulas filled other nanosilica and unfilled nanosilica experienced similar flow-time. In presence of nanosilica, coating properties were improved in comparison with neat coating. However, coating filled by nanosilica from rice husk indicated the best properties in studied coating formula. It may explained that size of nanosilica from rice husk was the largest in studied nanosilica particles and thus easily dispersing into coating formula

Carbon dioxide reforming of methane over modified iron-cobalt alumina catalyst : Role of promoter

Cobalt-based catalysts are widely employed in methane dry reforming but tend to deactivate quickly due to coke deposits and metal sintering. To enhance the performance, iron, a cost-effective promoter, is added, improving cobalt's metal dispersibility, reducibility, and basicity on the support. This addition accelerates carbon gasification, effectively inhibiting coke deposition. Methods: A series of iron-doped cobalt alumina MFe-5Co/Al2O3 (M= 0, 0.4, 0.8, 1, 2 wt.%) were prepared via simple incipient-wetness impregnation. The catalysts were thoroughly characterized via modern techniques including BET, XRD, H2-TPR, CO2-TPD. Significant findings: The addition of iron had a minimal impact on the properties of γ-Al2O3, but it significantly affected the dispersibility of cobalt. At an optimal dosage of 0.8 wt.%, there was a notable decrease of 29.44% in Co3O4 particle size. However, excessive iron loading induced agglomeration of Co3O4, which was reversible. The presence of iron also resulted in a decrease in the reduction temperature of Co3O4. The material's basicity was primarily influenced by the loading of iron, reaching its highest value of 705.7 μmol CO2 g−1 in the 2Fe-5Co/Al2O3. The correlation between catalytic activity and the physicochemical properties of the material was established. The 0.8Fe-5Co/Al2O3 sample exhibited excellent performance due to the favorable dispersibility of cobalt, its reducibility, and its affordable basicity

Design and simulation analysis of an integrated xyz micro-actuator for controlling displacement of a scanning probe

We report an integrated micro-actuator for independent control of the displacement in three orthogonal directions. Electrostatic comb drives are employed for controlling the displace- ment in the x and y directions while a parallel plate-type actuation is used for driving the displacement in the z direction. The three actuators are mechanically coupled, but are elec- trically isolated. The calculation models are established for investigating the operation char- acteristics of the micro-actuator. The calculated results are in good agreement with those obtained by the finite element method in Comsol Multiphysics 4.3. The results of modal analysis show that the displacement in the three orthogonal directions can be independently controlled with low mode cross-talk

Performance analysis of serpentine springs compliant to out-of-plane oscillation

The performance of two serpentine type springs is comparatively investigated. The first type is composed of straight beams and the second one is composed of circular arcs. Based on comparing calculation results and simulation data, the crab-leg spring model is appropriate for evaluating the stiffness of springs. To obtain the operation mode to be the first mode, the number of turns and the opening angle of springs should be increased. The performance of springs is evaluated via analysis of mode coupling. This study is useful for choosing an appropriate serpentine spring and the stiffness calculation model for applications in microelectroemchanical sensors and actuators

Design and performance analysis of a mechanically coupled spring compliant to out-of-plane oscillation

In this paper, a spring system symmetrically arranged around a circular plate compliant to out-of-plane oscillation is proposed. The spring system consists of single serpentine springs mutually coupled in a plane. Three theoretical mechanical models for evaluating the stiffness of the spring system are built, which are based on the flexural beam, Sigitta, and serpentine spring theories and equivalent mechanical spring structure models. The theoretically calculated results are in good agreement with numerical solutions using the finite element method, with errors less than 10% in the appropriate dimension ranges of the spring. Compared to similar spring structures without mechanical coupling, the proposed mechanically coupled spring shows advantage in suppressing the mode coupling

Utilizing Half Convolutional Autoencoder to Generate User and Item Vectors for Initialization in Matrix Factorization

Recommendation systems based on convolutional neural network (CNN) have attracted great attention due to their effectiveness in processing unstructured data such as images or audio. However, a huge amount of raw data produced by data crawling and digital transformation is structured, which makes it difficult to utilize the advantages of CNN. This paper introduces a novel autoencoder, named Half Convolutional Autoencoder, which adopts convolutional layers to discover the high-order correlation between structured features in the form of Tag Genome, the side information associated with each movie in the MovieLens 20 M dataset, in order to generate a robust feature vector. Subsequently, these new movie representations, along with the introduction of users’ characteristics generated via Tag Genome and their past transactions, are applied into well-known matrix factorization models to resolve the initialization problem and enhance the predicting results. This method not only outperforms traditional matrix factorization techniques by at least 5.35% in terms of accuracy but also stabilizes the training process and guarantees faster convergence

Utilizing Half Convolutional Autoencoder to Generate User and Item Vectors for Initialization in Matrix Factorization

Recommendation systems based on convolutional neural network (CNN) have attracted great attention due to their effectiveness in processing unstructured data such as images or audio. However, a huge amount of raw data produced by data crawling and digital transformation is structured, which makes it difficult to utilize the advantages of CNN. This paper introduces a novel autoencoder, named Half Convolutional Autoencoder, which adopts convolutional layers to discover the high-order correlation between structured features in the form of Tag Genome, the side information associated with each movie in the MovieLens 20 M dataset, in order to generate a robust feature vector. Subsequently, these new movie representations, along with the introduction of users’ characteristics generated via Tag Genome and their past transactions, are applied into well-known matrix factorization models to resolve the initialization problem and enhance the predicting results. This method not only outperforms traditional matrix factorization techniques by at least 5.35% in terms of accuracy but also stabilizes the training process and guarantees faster convergence

New Design of ZnO Nanorod- and Nanowire-Based NO2 Room-Temperature Sensors Prepared by Hydrothermal Method

Room-temperature gas sensors are attracting attention because of their low power consumption, safe operation, and long-term stability. Herein, ZnO nanorods (NRs) and nanowires (NWs) were on-chip grown via a facile hydrothermal method and used for room-temperature NO2 gas sensor applications. The ZnO NRs were obtained by a one-step hydrothermal process, whereas the NWs were obtained by a two-step hydrothermal process. To obtain ZnO NW sensor, the length of NRs was controlled short enough so that none of the nanorod-nanorod junction was made. Thereafter, the NWs were grown from the tips of no-contact NRs to form nanowire-nanowire junctions. The gas-sensing characteristics of ZnO NRs and NWs were tested against NO2 gas at room temperature for comparison. The gas-sensing characteristics of the sensors were also tested at different applied voltages to evaluate the effect of the self-activated gas-sensing performance. Results show that the diameter of ZnO NRs and NWs is the dominant parameter of their NO2 gas-sensing performance at room temperature. In addition, self-activation by local heating occurred for both sensors, but because the NWs were smaller and sparser than the NRs, local heating thus required a lower applied voltage with maximal response compared with the NRs