99 research outputs found
An efficient approach to measure the difficulty degree of practical programming exercises based on student performances
oai:ojs.www.rev-jec.org:article/282This study examines the generality of easy to hard practice questions in programming subjects. One of the most important contributions is to propose four new formulas for determining the difficulty degree of questions. These formulas aim to describe different aspects of difficulty degree from the learner's perspective instead of the instructor's subjective opinions. Then, we used clustering technique to group the questions into three easy, medium and difficult degrees. The results will be the baseline to consider the generality of the exercise sets according to each topic. The proposed solution is then tested on the data set that includes the results of the two subjects: Programming Fundamentals, Data Structures and Algorithms from Ho Chi Minh City University of Technology. The most important result is to suggest the instructors complete various degrees according to each topic for better evaluating student's performance
Do Technical Barriers to Trade Measures Affect Vietnamâs Tea Exports? Evidence from the Gravity Model
This paper explores how technical barriers to trade (TBT) affect Vietnamâs tea exports to 55 importing countries from 2001 to 2019. We use the gravity model with different estimation methods: ordinary least square (OLS), fixed-effect (FE), and random effect (RE) to estimate the impact of TBT on Vietnamâs tea exports. The results show that although GDP, population, distance, tariff, and participation in World Trade Organization (WTO) are crucial factors, the TBT measures imposed by these importing countries have significantly negative impacts on Vietnamâs tea exports. Our findings reveal that while a 1% increase in the cumulative TBT measures imposed by developing countries decreases Vietnam's tea export by 0.341%, the figure for developed countries is 1.308%
LES RĂLES DE L'ORGANISATION PAYSANNE ET DE L'ACTION COLLECTIVE POUR LE RENFORCEMENT DES FILIĂRES DE COMMERCIALISATION DES PRODUITS DE «SPĂCIALITĂ LOCALE» LE CAS DU LONGANE «LONG» DE LA PROVINCE DE HUNGYEN AU VIETNAME
N° ISBN - 978-2-7380-1284-5International audienceLe Vietnam est actuellement engagĂ© dans un processus d'intĂ©gration Ă©conomique internationale issue notamment de son adhĂ©sion rĂ©cente Ă l'OMC. Ce processus inclut une ouverture croissante du secteur agro-alimentaire domestique Ă la concurrence des produits importĂ©s. Les exploitations agricoles familiales sont particuliĂšrement fragilisĂ©es par ce nouveau contexte, en raison de le petite taille et du morcellement des superficies cultivables. Les moyens de renforcer la compĂ©titivitĂ© des produits issues de l'agriculture familiale constitue ainsi une des prioritĂ©s pour les recherches vietnamiennes en Ă©conomie agricole. Au Vietnam, le longane âLongâ produit dans la province de Hungyen est un produit de spĂ©cialitĂ© locale, c'est-Ă -dire dont la qualitĂ© spĂ©cifique est reconnue par une partie des consommateurs. NĂ©anmoins, le manque d'action collective entre les exploitations agricoles familiales fragilisent les performances de cette filiĂšre face aux longanes des autres rĂ©gions du Vietnam et les longanes importĂ©s. Cet article prĂ©sente les expĂ©riences d'appui pour le renforcement de la filiĂšre du longane âLongâ de la province de Hungyen au Vietnam vers le dĂ©veloppement de l'indication gĂ©ographique. GrĂące Ă l'appui de GTZ (German Technical Cooperation) et de l'IPSARD (Institut de politique et de stratĂ©gie pour l'agriculture et le dĂ©veloppement rural), la coopĂ©rative de longane Long Hongnam, qui consiste en une organisation de producteurs et de commerçants, a Ă©tĂ© mise sur pied en 2006. La coopĂ©rative a permis la mise en place des actions collectives suivantes: l'application d'un itinĂ©raire technique de production amĂ©liorĂ© incluant le respect de certaines bonnes pratiques agricoles locales (Good agricultural practices ou GAP), et la mise sur pied d'un espace de dialogue avec les commerçants. Grace Ă ce dispositif, les producteurs ont pu augmenter leur prix du vente, amĂ©liorer l'homogĂ©nĂ©itĂ© de la qualitĂ© des produits, et amĂ©liorer leur revenu. La durabilitĂ© de ce dispositif est discutĂ©e. L'article fait le bilan des forces et faiblesses de ces strategies de soutien a l'action collective
Numerical investigation of force transmission in granular media using discrete element method
In this paper, a numerical Discrete Element Method (DEM) model was calibrated to investigate the transmission of force in granular media. To this aim, DEM simulation was performed for reproducing the behavior of a given granular material under uniform compression. The DEM model was validated by comparing the obtained shear stress/normal stress ratio with results published in the available literature. The network of contact forces was then computed, showing the arrangement of the material microstructure under applied loading. The number and distribution of the contacts force were also examined statistically, showing that the macroscopic behavior of the granular medium highly depended on the force chain network. The DEM model could be useful in exploring the mechanical response of granular materials under different loadings and boundary conditions
Semi-Supervised Semantic Segmentation using Redesigned Self-Training for White Blood Cells
Artificial Intelligence (AI) in healthcare, especially in white blood cell
cancer diagnosis, is hindered by two primary challenges: the lack of
large-scale labeled datasets for white blood cell (WBC) segmentation and
outdated segmentation methods. These challenges inhibit the development of more
accurate and modern techniques to diagnose cancer relating to white blood
cells. To address the first challenge, a semi-supervised learning framework
should be devised to efficiently capitalize on the scarcity of the dataset
available. In this work, we address this issue by proposing a novel
self-training pipeline with the incorporation of FixMatch. Self-training is a
technique that utilizes the model trained on labeled data to generate
pseudo-labels for the unlabeled data and then re-train on both of them.
FixMatch is a consistency-regularization algorithm to enforce the model's
robustness against variations in the input image. We discover that by
incorporating FixMatch in the self-training pipeline, the performance improves
in the majority of cases. Our performance achieved the best performance with
the self-training scheme with consistency on DeepLab-V3 architecture and
ResNet-50, reaching 90.69%, 87.37%, and 76.49% on Zheng 1, Zheng 2, and LISC
datasets, respectively
CRLH Leaky-Wave Antenna with High Gain and Wide Beam-Scanning Angle for 5G mmWave Applications
In this paper, a novel composite right-/left-handed (CRLH) leaky-wave antenna with a simple structure, low cost, high gain, and wide beam-scanning range performance for the millimeter wave (mmWave) band. The proposed antenna comprises a series-fed array of asymmetrically slotted elliptical CRLH unit cells loaded with a short-circuit stub. By optimizing the length of the stub, the condition of the CRLH structure is balanced to enable beam scanning from the backward to the forward direction within the mmWave band. The proposed antenna exhibits a wide beam-scanning angle of 112° (â60° to 52°), coupled with high gain and radiation efficiency at the designated band. Furthermore, it is fabricated on a traditional microwave substrate, Rogers RT/duroid 5880, thus offering a cost-effective approach to streamlining the manufacturing process. The measurement results confirmed a peak realized gain of 16.8 dBi. The excellent performance achieved using a low-cost design makes the proposed antenna attractive for 5G mmWave applications
HighARCS Integrated Action Planning for the Dakrong District study site, Quang Tri Province, Vietnam
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