This paper elucidates the social context of HIV risk behavior and intra-couple risk communication among injecting drug users (IDUs) and their main sex partner. Data on shared injection equipment, ...unprotected sex with multiple partners, unprotected sex with a main partner and couples’ dynamics and risk communication were gathered through separate in-depth interviews with 11 active male IDUs and 11 of their primary female sex partners in northern Vietnam. The majority of IDUs’ sex partners does not inject drugs and is monogamous. In contrast, most IDUs reported a wide range of risky practices including needle sharing and unprotected sex with multiple, often concurrent, sex partners. Men rarely used condoms with primary partners. Many IDUs worried about their HIV-status, but none disclosed their injecting or sexual practices to their sex partners, leaving their partners unaware of their HIV risk. Among women who worried about HIV/AIDS, the vast majority was unable to influence their partner's needle sharing or extramarital affairs and most would not initiate condom use because they feared their partner's reaction. Couple-based interventions to facilitate risk communication combined with programs to promote condom use among male IDUs, may help to reduce HIV transmission from IDUs to their primary partners.
Travel location recommendation systems have long been used by travellers for their ability to suggest destinations and potential travel experiences that match travellers' desires. Recently, a new ...type of domestic travel has emerged, namely domestic overseas-like travel experiences. These experiences are attractive to travellers who have a preference for exotic locations but no desire to travel internationally. Existing travel recommendation systems were not designed for such applications, nor do they have the relevant ability to recommend domestic overseas-like travel experiences to support travel decision making. To address this challenge, this paper focuses on the development of a recommendation model based on the visual content of photos for domestic overseas-like travel experiences and a prototype application. The application uses the latest advancement in computer vision — the concept model — to learn high-level concepts in an overseas travel destination photo collection to identify similar domestic travel experiences. We demonstrate the usability of the prototype application with a large-scale data set of approximately 479,000 travel photos taken in several countries and evaluate its utility and efficacy through four focus groups with target users.
•Travel recommendation systems can suggest destinations to meet travellers' desires.•Current recommendation models mainly rely on travellers' past travel behaviours.•Domestic overseas-like travel experiences were not supported by any recommendation models.•We built a recommendation model to support travel decision-making.•We used a computer vision-based concept model to suggest domestic overseas-like travel experiences.
Groundwater resources are required for domestic water supply, agriculture, and industry, and the strategic importance of water resources will only increase in the context of climate change and ...population growth. For optimal management of this crucial resource, exploration of the potential of groundwater is necessary. To this end, the objective of this study was the development of a new method based on remote sensing, deep neural networks (DNNs), and the optimization algorithms Adam, Flower Pollination Algorithm (FPA), Artificial Ecosystem-based Optimization (AEO), Pathfinder Algorithm (PFA), African Vultures Optimization Algorithm (AVOA), and Whale Optimization Algorithm (WOA) to predict groundwater potential in the North Central region of Vietnam. 95 springs or wells with 13 conditioning factors were used as input data to the machine learning model to find the statistical relationships between the presence and nonpresence of groundwater and the conditioning factors. Statistical indices, namely root mean square error (RMSE), area under curve (AUC), accuracy, kappa (K) and coefficient of determination (R
2
), were used to validate the models. The results indicated that all the proposed models were effective in predicting groundwater potential, with AUC values of more than 0.95. Among the proposed models, the DNN-AVOA model was more effective than the other models, with an AUC value of 0.97 and an RMSE of 0.22. This was followed by DNN-PFA (AUC=0.97, RMSE=0.22), DNN-FPA (AUC=0.97, RMSE=0.24), DNN-AEO (AUC=0.96, RMSE=0.25), DNN-Adam (AUC=0.97, RMSE=0.28), and DNN-WOA (AUC=0.95, RMSE=0.3). In addition, according to the groundwater potential map, about 25–30% of the region was in the high and very high potential groundwater zone; 5–10% was in the moderate zone, and 60–70% was low or very low. The results of this study can be used in the management of water resources in general and the location of appropriate wells in particular.
In a community-based cross-sectional survey among out-of-treatment male opiate injecting drug users (IDU) aged 18-45, data on non-fatal overdose were collected using a semi-structured questionnaire. ...From August to September 2003, 299 IDU were recruited in two districts of Bac Ninh, a semi-urban province in North Vietnam. Prevalence of lifetime and recent non-fatal overdose were 43.5 and 83.1%, respectively. Logistic regression analyses showed associations between non-fatal overdose and younger age, unemployment, residence in the provincial township, frequency of injecting, injecting heroin mixed with valium, and history of drug treatment. While recognizing the limitations of this study, it is the first in Southeast Asia to report on prevalence of drug use-related overdose. Future research is recommended on occurrence of fatal overdose in this population.
Celotno besedilo
Dostopno za:
DOBA, FSPLJ, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
In this paper, we prove the existence of weak solutions to the complex m-Hessian equations in the class Dm(Ω) on an open subset Ω of Cn. In the end of the paper we give an example shows that in the ...unit ball B2(0,1)⊂C2 the complex Monge-Ampère equation (ddc.)2=μ is solvable but the complex Hessian equation H1(.)=μ has not any weak solutions where μ is a nonnegative Radon measure on B2(0,1).
Automatic speech recognition for languages in Southeast Asia, including Chinese, Thai and Vietnamese, typically models both acoustics and languages at the syllable level. This paper presents a new ...approach for recognizing those languages by exploiting information at the word level. The new approach, adapted from our FLaVoR architecture1, consists of two layers. In the first layer, a pure acoustic-phonemic search generates a dense phoneme network enriched with meta data. In the second layer, a word decoding is performed in the composition of a series of finite state transducers (FST), combining various knowledge sources across sub-lexical, word lexical and word-based language models. Experimental results on the Vietnamese Broadcast News corpus showed that our approach is both effective and flexible.
With the advancement of deep learning (DL) in various fields, there are many attempts to reveal software vulnerabilities by data-driven approach. Nonetheless, such existing works lack the effective ...representation that can retain the non-sequential semantic characteristics and contextual relationship of source code attributes. Hence, in this work, we propose XGV-BERT, a framework that combines the pre-trained CodeBERT model and Graph Neural Network (GCN) to detect software vulnerabilities. By jointly training the CodeBERT and GCN modules within XGV-BERT, the proposed model leverages the advantages of large-scale pre-training, harnessing vast raw data, and transfer learning by learning representations for training data through graph convolution. The research results demonstrate that the XGV-BERT method significantly improves vulnerability detection accuracy compared to two existing methods such as VulDeePecker and SySeVR. For the VulDeePecker dataset, XGV-BERT achieves an impressive F1-score of 97.5%, significantly outperforming VulDeePecker, which achieved an F1-score of 78.3%. Again, with the SySeVR dataset, XGV-BERT achieves an F1-score of 95.5%, surpassing the results of SySeVR with an F1-score of 83.5%.
ABSTRACT The objective of this study was the development of a new machine learning model using a radial basis function neural network (RBFNN) to build flood susceptibility maps and damage assessment ...for the Phu Yen province of Vietnam. The built model will be optimized by five algorithms, namely Giant Trevally Optimization (GTO), Golden Jackal Optimization (GJO), Brown-Bear Optimization (BBO), Gray Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA) to find out the best model to establish the flood susceptibility map. These models were evaluated using the statistical indices such as root mean square error (RMSE), mean absolute error (MAE), receiver operating characteristic (ROC), area under the curve (AUC), and coefficient of determination (COD). The result showed that all five optimization algorithms were successfully improving the performance of the RBFNN model, among them the hybrid model RBFNN–BBO has the highest performance with AUC = 0.998 and R2 = 0.8 and the RBFNN–GTO model has the lowest performance with AUC = 0.755 and R2 = 0.65. The regions identified with a high- and very-high flood susceptibility area (1,075 km2) were concentrated on the plain and along three of the largest rivers in Phu Yen province.
The digital method in which control signals are activated according to charging modes is commonly used in the Li-Ion battery charger. At transition time, spike phenomenon can occur in charging ...current due to asynchronous control signals leading to bad impact on performance of Li-Ion battery charger. In this paper, a design approach of charging mode control circuit is proposed to eliminate this phenomenon. Moreover, parallel current source architecture is applied to lower trickle current approximate to 210mA for Li-Ion battery's safety as well as enhance large current up to 1A for saving charging time. The Li-Ion battery charging circuit is designed based on 0.13um CMOS technology and simulated by Cadence.
Abstract Background Sexual risk and STDs are relatively high among injecting drug users (IDUs) in Vietnam. We sought to determine characteristics of sexually active IDUs and correlates of high-risk ...sexual practices among IDUs in Bac Ninh province in northern Vietnam. Methods We used data collected for a community-based cross-sectional pilot study to identify correlates of recent high-risk sex (>1 sex partner and inconsistent/no condom use in the past year). Factors associated with high-risk sex were identified using logistic regression. Results Among 216 sexually active male IDUs, one third ( n = 72) had engaged in high-risk sex within the last year. IDUs who reported injecting with others more frequently, having someone else inject their drugs at last injection, sharing needles or sharing any injection equipment were more likely to have reported recent high-risk sex. Factors independently associated with high-risk sexual activity were not injecting oneself AOR: 2.22; 95% CI (1.09–4.51), and sharing needles in the past 12 months AOR: 2.57; 95% CI (1.10–5.99). Conclusions IDUs who inject socially and IDUs who share needles are likely to engage in high-risk sexual behaviours and may serve as an important bridge group for epidemic HIV transmission in Vietnam. In addition to messages regarding the dangers of sharing needles and other injection equipment, preventive interventions among newly initiated IDUs should also focus on reducing sexual risk.
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