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To understand the genetic diversity and differentiation of Vietnamese melon (Cucumis melo L.), we collected 64 landraces from the central and southern parts of the country and assessed molecular polymorphism using simple sequence repeat and random amplified polymorphic DNA markers. The Vietnamese melon was divided into seven cultivar groups, namely “Dua le”, “Dua vang”, “Dua bo”, “Dua gang-andromonoecious”, “Dua gang-monoecious”, “Dua thom”, “Montok”, and the weedy-type melon “Dua dai”. Among these, Dua le, Dua vang, Dua bo, and Dua gang-andromonoecious are cultivated on plains and they formed cluster II along with the reference accessions of Conomon and Makuwa. Based on genetic distance, Dua le and Dua vang were regarded as Makuwa and Dua bo and Dua gang-andromonoecious as Conomon. In contrast, Dua thom and Montok are cultivated in highlands, and they formed cluster III along with landraces from the southern and eastern foot of the Himalayas. Dua gang-monoecious which is commonly cultivated in the southern parts of Vietnam, exhibited the greatest genetic diversity, as explained by its possible origin through the hybridization between Dua gang-andromonoecious and Montok. Genetic differences in melon landraces between plains and highlands and hybridization between these two geographical groups have contributed to the enhancement of genetic diversity in Vietnamese melon.

Purpose We aimed to determine the incidence and prediction nomogram for new-onset metabolic syndrome (MetS) in a middle-aged Vietnamese population.Methods A population-based prospective study was conducted in 1150 participants aged 40-64 years without MetS at baseline and followed-up for 5 years. Data on lifestyle factors, socioeconomic status, family diabetes history, and anthropometric measures were collected. MetS incidence was estimated in general population and subgroup of age, gender, and MetS components. A Cox proportional hazards regression was used to estimate hazard ratios (HRs) with 95% confidence intervals (CI) for MetS. A prediction nomogram was developed and checked for discrimination and calibration.Results During median follow-up of 5.14 years, the accumulate MetS incidence rate was 23.4% (95% CI: 22.2-24.7). The annual incidence rate (95%CI) was 52.9 (46.7-60.1) per 1000 person-years in general population and higher in women [56.6 (48.7-65.9)] than men [46.5 (36.9-59.3)]. The HRs (95% CI) for developing MetS were gender [females vs males: 2.04 (1.26-3.29)], advanced age [1.02 (1.01-1.04) per one year], waist circumference [1.08 (1.06-1.10) per one cm] and other obesity-related traits, and systolic blood pressure [1.02 (1.01-1.03) per one mmHg]. The prediction nomogram for MetS had a good discrimination (C-statistics = 0.742) and fit calibration (mean absolute error = 0.009) with a positive net benefit in the predicted probability thresholds between 0.13 and 0.70. Conclusions The study is the first to indicate an alarmingly high incidence of MetS in a middle-aged population in Vietnam. The nomogram with simply applicable variables would be useful to qualify individual risk of developing MetS.

Internet technology has popularized the “like” as a type of social endorsements on social media. Despite the high impact of brand passion on customer behavior and brand performance, questions remain regarding how social endorsement triggers customer desires toward a brand. This study establishes “like-clicking” behavior on social media as a form of friend-bonding social endorsement and crowd-bridging social endorsement, based on theories of social capital and self-congruence, and examines the extent to which endorsement turns into emotional attachment (i.e., brand passion). Two approaches were employed: Partial Least Square (PLS) and Fuzzy Set Qualitative Comparative Analysis (FsQCA). The PLS and fsQCA results revealed causal and structural associations of friend-bonding and crowd-bridging social endorsements with self-verification and self-enhancement, and thereby with the outcome of obsessive and harmonious brand passion. These findings enrich our understanding of social endorsement. Encouraging customers to endorse the brand through passionate behavior is a sound marketing strategy.

Adversarial images have been proposed to deceive deep neural networks (DNNs) by adding perturbations to the pixels. Unlike existing attacks, Su et al. [1] analyzed an attack in an extremely limited constraint where only one pixel was modified. However, their one-pixel attack is easy to recognize by humans. In this paper, we improve the attack to enable the deceit of both DNNs and humans. We conducted a human recognition analysis to prove our attack's effect. We then propose detection and defense methods against the attack by re-attacking the adversarial images. Our experimental results on the six most recent convolutional neural networks show that while our attack achieved approximately the same success rates and confidence scores as in the existing attack, our attack achieves a higher success rate for deceiving humans. Only 49.41 % of participants can recognize our attack even though 81.04 % participants have recognized the existing attack. OPA2D detects 99.33% of the existing attack and 100% of our attack and defends 92.00% of the existing attack and 95.33 % of our attack.

Background Talaromycosis (penicilliosis) is an invasive fungal infection and a major cause of human immunodeficiency virus (HIV)–related deaths in Southeast Asia. Guidelines recommend induction therapy with amphotericin B deoxycholate; however, treatment with itraconazole has fewer toxic effects, is easier to administer, and is less expensive. Our recent randomized controlled trial in Vietnam found that amphotericin B was superior to itraconazole with respect to 6-month mortality. We undertook an economic evaluation alongside this trial to determine whether the more effective treatment is cost-effective. Methods Resource use, direct and indirect costs, and health and quality-of-life outcomes (measured using quality-adjusted life-years [QALYs]) were evaluated for 405 trial participants from 2012 to 2016. Both a Vietnamese health service and a broader societal costing perspective were considered. Mean costs and QALYs were combined to calculate the within-trial cost-effectiveness of amphotericin vs itraconazole from both perspectives. Results From a Vietnamese health service perspective, amphotericin increases costs but improves health outcomes compared to itraconazole, at a cost of $3013/QALY gained. The probability that amphotericin is cost-effective at a conventional (World Health Organization CHOICE) threshold of value for money is 46%. From a societal perspective, amphotericin is cost-reducing and improves outcomes compared to itraconazole, and is likely to be a cost-effective strategy at any value for money threshold greater than $0. Conclusions Our analysis indicates that induction therapy with amphotericin is a cost-effective treatment strategy for HIV-infected adults diagnosed with talaromycosis in Vietnam. These results provide the evidence base for health care providers and policy makers to improve access to and use of amphotericin., Compared to itraconazole as induction therapy for talaromycosis, amphotericin leads to more adverse events and is more expensive, but reduces mortality. Here, we show that, from a societal perspective, amphotericin is likely to be cost-effective in HIV-infected adults in Asia.

This paper proposes a new approach for force sensation with the elimination of variable-frequency disturbances using deep learning based Kalman filter. The disturbance observer is employed for force estimation. To cancel the effect of undesired variable-frequency components superimposed in force information, the deep learning based Kalman filter is designed as an integration of the deep learning based frequency estimation and the periodic component elimination Kalman filter. The Kalman filter is designed to eliminate the periodic component by estimating the signal with periodic component, the first derivative and the second derivative of that signal. The deep learning based frequency estimation is constructed by the long short-term memory deep neural network to estimate the frequency of the periodic disturbance during force sensing operation. Hence, the frequency variation of the periodic component is detectable. This estimated frequency is a parameter which determines the performance of the Kalman filter in periodic component elimination. Therefore, the deep learning based Kalman filter is capable of excluding the undesired components with variable frequencies. The effectiveness of the proposed method is verified by numerical simulation results.

Background An endotracheal tube cuff pressure between 20 and 30 cmH2O is recommended to prevent ventilator-associated respiratory infection (VARI). We aimed to evaluate whether continuous cuff pressure control (CPC) was associated with reduced VARI incidence compared with intermittent CPC. Methods We conducted a multicenter open-label randomized controlled trial in intensive care unit (ICU) patients within 24 hours of intubation in Vietnam. Patients were randomly assigned 1:1 to receive either continuous CPC using an automated electronic device or intermittent CPC using a manually hand-held manometer. The primary endpoint was the occurrence of VARI, evaluated by an independent reviewer blinded to the CPC allocation. Results We randomized 600 patients; 597 received the intervention or control and were included in the intention to treat analysis. Compared with intermittent CPC, continuous CPC did not reduce the proportion of patients with at least one episode of VARI (74/296 [25%] vs 69/301 [23%]; odds ratio [OR] 1.13; 95% confidence interval [CI] .77–1.67]. There were no significant differences between continuous and intermittent CPC concerning the proportion of microbiologically confirmed VARI (OR 1.40; 95% CI .94–2.10), the proportion of intubated days without antimicrobials (relative proportion [RP] 0.99; 95% CI .87–1.12), rate of ICU discharge (cause-specific hazard ratio [HR] 0.95; 95% CI .78–1.16), cost of ICU stay (difference in transformed mean [DTM] 0.02; 95% CI −.05 to .08], cost of ICU antimicrobials (DTM 0.02; 95% CI −.25 to .28), cost of hospital stay (DTM 0.02; 95% CI −.04 to .08), and ICU mortality risk (OR 0.96; 95% CI .67–1.38). Conclusions Maintaining CPC through an automated electronic device did not reduce VARI incidence. Clinical Trial Registration NCT02966392.

Background. Uric acid is a powerful free-radical scavenger in humans, but hyperuricemia may induce insulin resistance and beta-cell dysfunction. The study aimed to evaluate the association between hyperuricemia and hyperglycemia, considering the confounding factors in a Vietnamese population. Methods. A population-based cross-sectional study recruited 1542 adults aged 50 to 70 years to collect data on socioeconomic status, lifestyle factors, and clinical patterns. Associations between hyperuricemia and hyperglycemia (isolated impaired fasting glucose (IFG), isolated impaired glucose tolerance (IGT), combined IFG-IGT, and type 2 diabetes (T2D)) were evaluated by multinomial logistic regression analysis in several models, adjusting for the confounding factors including socioeconomic status, lifestyle factors, and clinical measures. Results. Uric acid values were much higher in IFG, IFG-IGT, and T2D groups compared to those in the normal glucose tolerance (NGT) group. The significant association of hyperuricemia with IFG, IFG-IGT, and T2D was found in the model unadjusted and remained consistently in several models adjusted for socioeconomic status, lifestyle factors, and clinical patterns. In the final model, the consistent hyperglycemia risk was found in total sample (OR = 2.23 for IFG, OR = 2.29 for IFG-IGT, and 1.75 for T2D, P≤0.006) and in women (OR = 2.90 for IFG, OR = 3.96 for IFG-IGT, and OR = 2.49 for T2D, P<0.001) but not in men. Conclusions. It is the first report in Vietnamese population suggesting the significant association of hyperuricemia with IFG, IFG-IGT, and T2D; and the predominant association was found in women than in men, taken into account the confounding factors.

Background: To evaluate the value of narrow band imaging (NBI) endosocopy in diagnosis of hypopharyngeal and laryngeal cancer and following – up post treatment. Material and methods: A total of 75 patients included 36 patients with hypopharyngeal cancer and 39 patients with laryngeal cancer who had diagnosed at Department of Otoloryngology – Hue Central Hospital from 5/2017 to 5/2018. A prospective cohort study was conducted. Results: The age group 51 - 60 years occurred most often, 33.3%, the mean age was 62.1 ± 13.4. The UICC stage III was 65.3%. Tumor was in ulcerlarative and infiltrate form (89.4%), edema and inflammation of magrin tumor (41.3%), invasive (58.7%). Intrapapillary capillary loops – IPCL - type V was predominant, type V-n was 46.7%. The tumor with IPCL type V-n had strong enhancement (51.3%) and moderate enhancement (44.4%) after contrast medium injection on CT scan. One month after treatment, there were 33.3% of tumor – free, 53.7% of mucosal edema and 13% tumor size-decreasing on NBI image. Conclusion: NBI endoscopy is an useful tool for diagnosing of hypopharyngeal and laryngeal cancer and following – up post treatment. Key words: narrow band imaging endoscopy, hypopharyngeal cancer, laryngeal cancer

Background: The coagulation system is closely linked with vascular inflammation, although the underlying mechanisms are still obscure. Recent studies show that protease-activated receptor (PAR)-2, a major receptor of activated factor X, is expressed in both vascular cells and leukocytes, suggesting that PAR-2 may contribute to the pathogenesis of inflammatory diseases. Here we investigated the role of PAR-2 in vascular inflammation and atherogenesis. Methods: We generated apolipoprotein E-deficient ( ApoE -/- ) mice lacking systemic PAR-2 expression ( PAR-2 -/- ApoE -/- ). ApoE -/- mice, which lack or express PAR-2 only in bone marrow (BM) cells, were also generated by BM transplantation. Atherosclerotic lesions were investigated after 20 weeks on a Western-type diet by histological analyses, quantitative reverse transcription polymerase chain reaction, and Western blotting. In vitro experiments using BM-derived macrophages were performed to confirm the proinflammatory roles of PAR-2. The association between plasma activated factor X level and the severity of coronary atherosclerosis was also examined in humans who underwent coronary intervention. Results: PAR-2 -/- ApoE -/- mice showed reduced atherosclerotic lesions in the aortic arch ( P P P P P ApoE -/- mice. Systemic PAR2 deletion in ApoE -/- mice significantly decreased the expression of inflammatory molecules in the aorta. The results of BM transplantation experiments demonstrated that PAR-2 in hematopoietic cells contributed to atherogenesis in ApoE -/- mice. PAR-2 deletion did not alter metabolic parameters. In vitro experiments demonstrated that activated factor X or a specific peptide agonist of PAR-2 significantly increased the expression of inflammatory molecules and lipid uptake in BM-derived macrophages from wild-type mice compared with those from PAR-2–deficient mice. Activation of nuclear factor-κB signaling was involved in PAR-2–associated vascular inflammation and macrophage activation. In humans who underwent coronary intervention, plasma activated factor X level independently correlated with the severity of coronary atherosclerosis as determined by Gensini score ( P P Conclusions: PAR-2 signaling activates macrophages and promotes vascular inflammation, increasing atherosclerosis in ApoE -/- mice. This signaling pathway may also participate in atherogenesis in humans.

This study investigates the impacts of intellectual capital through Value-Added Intellectual Capital (VAIC) and its components: human capital efficiency (HCE) and structural capital efficiency (SCE) on financial performance in terms of return on assets (ROA) and return on equity (ROE). In addition, this study compares the effects between firms from financial and pharmaceutical industries. A total of 149 Vietnamese firms comprising of 108 financial firms and 41 pharmaceutical firms were examined. Based on the findings, VAIC and HCE show beneficial impacts on both financial performance measures, ROA, and ROE. However, SCE shows adverse and beneficial implications on ROA and ROE, respectively. In terms of industry comparison, VAIC has positive effects on ROA and ROE among the firms from financial industry, whereas it has no effect in the firms from pharmaceutical industry. The effect of HCE on ROA is stronger in the firms from financial industry than firms from pharmaceutical industry while the effect of HCE on ROE is stronger in the firms from pharmaceutical industry than firms from financial industry. The effect of SCE on ROA is stronger in the pharmaceutical firms than financial firms while the effect of SCE on ROE is stronger in the financial firms than pharmaceutical firms. Lastly, the implications of the importance of knowledge-based resources on value creation were elaborated.

This paper proposes a new approach for realization of wideband sensor-less force sensing based on deep learning based singular spectrum analysis. The force sensation function is performed by a disturbance observer. The wideband force sensing is realized at high value of observer pole. To extract force information from the noisy estimation of the disturbance observer, the deep learning based singular spectrum analysis is designed with consideration of variable noise characteristics during operation. The deep learning algorithm is employed to design the online estimation of the embedded dimension, which is related to the noise extraction performance of the singular spectrum analysis. The effectiveness of the proposed method is verified by numerical simulations and simulations based on experimental results.

Translated texts have been used for malicious purposes, i.e., plagiarism or fake reviews. Existing detectors have been built around a specific translator (e.g., Google) but fail to detect a translated text from a strange translator. If we use the same translator, the translated text is similar to its round-trip translation, which is when text is translated into another language and translated back into the original language. However, a round-trip translated text is significantly different from the original text or a translated text using a strange translator. Hence, we propose a detector using text similarity with round-trip translation (TSRT). TSRT achieves 86.9% accuracy in detecting a translated text from a strange translator. It outperforms existing detectors (77.9%) and human recognition (53.3%).

In recent years, lifestyle authentication, which combines multiple personal behavioral data for authentication, has been proposed as a new authentication method in addition to traditional knowledge-based authentication, possession-based authentication, and biometrics-based authentication. In previous research on lifestyle authentication, authentication scores of each authentication element were often calculated independently and used for the final authentication, ignoring the correlation between each element. It was also often difficult to apply lifestyle authentication methods in the real world because they required a large amount of preliminary data. In this paper, we propose a new method that solves these problems by using the correlation between GPS/Wi-Fi data from smartphones and activity data (activity types that are inferred from the metabolic equivalent of task (MET)) from activity trackers. We applied our method to the data collected in the MITHRA project, which is a proof-of-concept experiment of lifestyle authentication. As a result, we achieved an equal error rate (EER) of 0.087 and 0.130 when ideal data were obtained and not obtained, respectively.

A visual homograph attack is a way that the attacker deceives the web users about which domain they are visiting by exploiting forged domains that look similar to the genuine domains. T. Thao et al. (IFIP SEC'19) proposed a homograph classification by applying conventional supervised learning algorithms on the features extracted from a single-character-based Structural Similarity Index (SSIM). This paper aims to improve the classification accuracy by combining their SSIM features with 199 features extracted from a N-gram model and applying advanced ensemble learning algorithms. The experimental result showed that our proposed method could enhance even 1.81% of accuracy and reduce 2.15% of false-positive rate. Furthermore, existing work applied machine learning on some features without being able to explain why applying it can improve the accuracy. Even though the accuracy could be improved, understanding the ground-truth is also crucial. Therefore, in this paper, we conducted an error empirical analysis and could obtain several findings behind our proposed approach.

Automatic information extraction from identity cards is crucial in many applications such as eKYC, customer registration, and profile digitalization. Identity card detection and normalization are crucial steps before further information extraction. In practice, many identity cards of different types with both front and back sides may appear in an image or on the same page of a profile. This paper proposes a method to estimate the pose of multiple identity cards and classify the card into four categories: front/back sides of new/old identity cards. Particularly, we propose an EfficientNet-based model to detect the corners in an anchor-free manner and estimate the edges of identity cards using part affinity fields (PAF). According to the estimated PAF, the detected corners are then grouped in clusters, each of which corresponds to a single identity card. Experimental results show that our method yields promising results on our private dataset. We achieve a realtime speed of 24 fps on a machine with NVIDIA GPU GTX 1080 Ti.

Internationalized Domain Name (IDN) homograph is a web security attack in which the attackers deceive the computer users about what websites they are accessing by using homologous domain names. Recently, the growth of IDN homograph attack has become a severe problem with a significant probability of criminality like frauds for web users. This paper proposes an enhanced classification method for IDN homograph detection by utilizing the Structural Similarity Index (SSIM). Compared to the existing approach, the experiment results showed that our improved classification method could increase the accuracy from 95.07% to 96.18% and decrease the false positive rate from 3.92% to 3.23%. Moreover, we apply a multi-group-of-classifier method to our model, which can further increase the accuracy of 98.34% with a false positive rate of 3.77%. We also conducted an empirical analysis of the IDN homograph data and the SSIM classification approach’s training processes to discuss why our method outperforms the existing method in homograph detection.

INTRODUCTION In Reunion Island (RUN), cervical cancer is the 4th most common cancer in women and standardized mortality rate is 4.8 for 100 000 women. It is preventable by HPV vaccination, yet only 8.1% of girls aged

Web security issues have become more critical for web users because the development of information technologies makes many web threats much sophisticated. Internationalized Domain Name (IDN) homograph attack is one of the common threats which deceives web users by fabricating homologous domain names of their accessed websites by exploiting the fact that many characters look alike, for instance, go0gle.com is a homograph targeting to the brand domain google.com by replacing the third character ‘o’ to zero. Since IDN homograph attacks can lead users to web phishing or privacy interception, its detection has been an important challenge. In this paper, we propose an IDN homograph detection method by multi-feature classification based on Mean Squared Error (MSE), Peak Signal-to-noise Ratio (PSNR), and Structural Similarity Index (SSIM). Compared to the state-of-art existing classification method, our accuracy is increased from 95.07% to 97.04%, and false positive rate (FPR) is reduced from 3.92% to 2.31%.

Part 5: Spatial Systems and Crowdsourcing Security; International audience; Behavioral-based authentication is a new research approach for user authentication. A promising idea for this approach is to use location history as the behavioral features for the user classification because location history is relatively unique even when there are many people living in the same area and even when the people have occasional travel, it does not vary from day to day. For Global Positioning System (GPS) location data, most of the previous work used longitude and latitude values. In this paper, we investigate the advantage of metadata extracted from the longitude and latitude themselves without the need to require any other information other than the longitude and latitude. That is the location identification name (i.e., the address). Our idea is based on the fact that given a pair of longitude and latitude, there is a corresponding address. This is why we use the term self-enhancing in the title. We then applied text mining on the address and combined the extracted text features with the longitude and latitude for the features of the classification. The result showed that the combination approach outperforms the GPS approach using Adaptive Boosting and Gradient Boosting algorithms.

The research was conducted in order to identify the relationships between human resource practices, employee motivation and employee loyalty. Quantitative research method was applied with questionnaires directly delivered to 595 employees in hospitality sector in Ho Chi Minh city, Vietnam. Statistics techniques including exploratory factor analysis, reliability analysis, multiple regression and mediation analysis were used. The empirical results showed that variables of team spirit, career development, compensation, relationship with manager and working environment directly affected employee motivation and consequently, they provided indirect effects on loyalty through the mediation of employee motivation. In addition, employee loyalty was also directly affected by career development, working environment and employee motivation. It is suggested that hospitality sector should develop attractive compen-sation and benefit policies, comfortable workplace environment, coherent teamwork culture as well as straightforward career training and development plan for achieving higher level of employee loyalty.

With the development of the Internet, web content is exponentially increasing. Along with this, web-based attacks such as drive-by download attacks and phishing have grown year on year. To prevent such attacks, URL blacklists are widely used. However, URL blacklists are not enough because they lack the ability to detect newly generated malicious URLs. In this paper, we propose an automatic query template generation method to detect malicious websites. Our method focus on URL query strings that contained similarities on malicious website groups. Additionally, we evaluate our proposed method with large-scale dataset and verify effectiveness. Consequently, our proposed method can grasp the characteristics of malicious campaigns; it can detect 11,292 malicious unique domains not detected by Google Safe Browsing. Moreover, our method achieved high precision in the seven months of experiments.

Current user authentication systems are based on PIN code, password, or biometrics traits, which can have some limitations in usage and security. Lifestyle authentication has become a new research approach in which the promising idea is to use the location history since it is relatively unique. Even when people live in the same area or have occasional travel, it does not vary from day to day. For Global Positioning System (GPS) data, previous work used the longitude, latitude, and timestamp as the classification features. In this paper, we investigate a new approach utilizing distance coherence, which can be extracted from the GPS itself without the need to require other information. We applied three ensemble classifications, including RandomForest, ExtraTrees, and Bagging algorithms. The experimental result showed that our approach could achieve 99.42%, 99.12%, and 99.25% of accuracy, respectively.

To sought for an easily applicable nomogram for detecting individuals at high risk of undiagnosed type 2 diabetes.The development cohort included 2542 participants recruited randomly from a rural population in 2011.The glycemic status of subjects was determined using the fasting plasma glucose test and the oral glucose tolerance test. The Bayesian Model Average approach was used to search for a parsimonious model with minimum number of predictor and maximum discriminatory power. The corresponding prediction nomograms were constructed and checked for discrimination, calibration, clinical usefulness, and generalizability in nationwide population in 2012.The non-lab nomogram including waist circumference and systolic blood pressure was the most parsimonious with the area under receiver operating characteristic curve (AUC) of 0.71 (95 %CI = 0.64-0.76). Adding low-density lipoprotein cholesterol in the non-lab nomogram generated the lab-based nomogram with significantly improved AUC of 0.83 (0.78-0.87, P 0.001). The nomograms had a positive net benefit at threshold probability between 0.01 and 0.15. Applying the non-lab nomogram to the national population yielded the AUC of 0.66 (0.63-0.70) and 0.68 (0.65-0.71) in the cohorts aged 40-64 and 30-69 years, respectively.The novel nomograms could help promote the early detection of undiagnosed diabetes in rural Vietnamese population.

In today's world, energy is the single most important parameter to consider when assessing the impacts of technical systems on the environment. More amount of electricity is consumed due to street lights. Intelligent lighting control and energy management system is a perfect solution for energy saving, especially in public lighting management. The paper focuses on products and innovative components for street lighting, proposing a consumption reducing solution based on an intelligent system for remote measurements and control with GPS/GPRS/4G technologies for public lighting system. The architecture was successfully tested and validated and continues to be in development.

Visual homograph attack is a way that the attackers deceive victims about what domain they are communicating with by exploiting the fact that many characters look alike. The attack is growing into a serious problem and raising broad attention in reality when recently many brand domains have been attacked such as apple.com (Apple Inc.), adobe.com (Adobe Systems Incorporated), lloydsbank.co.uk (Lloyds Bank), etc. Therefore, how to detect visual homograph becomes a hot topic both in industry and research community. Several existing papers and tools have been proposed to find some homographs of a given domain based on different subsets of certain look-alike characters, or based on an analysis on the registered International Domain Name (IDN) database. However, we still lack a scalable and systematic approach that can detect sufficient homographs registered by attackers with a high accuracy and low false positive rate. In this paper, we construct a classification model to detect homographs and potential homographs registered by attackers using machine learning on feasible and novel features which are the visual similarity on each character and some selected information from Whois. The implementation results show that our approach can bring up to 95.90% of accuracy with merely 3.27% of false positive rate. Furthermore, we also make an empirical analysis on the collected homographs and found some interesting statistics along with concrete misbehaviors and purposes of the attackers.

Machine-translated text plays a crucial role in the communication of people using different languages. However, adversaries can use such text for malicious purposes such as plagiarism and fake review. The existing methods detected a machine-translated text only using the text's intrinsic content, but they are unsuitable for classifying the machine-translated and human-written texts with the same meanings. We have proposed a method to extract features used to distinguish machine/human text based on the similarity between the intrinsic text and its back-translation. The evaluation of detecting translated sentences with French shows that our method achieves 75.0% of both accuracy and F-score. It outperforms the existing methods whose the best accuracy is 62.8% and the F-score is 62.7%. The proposed method even detects more efficiently the back-translated text with 83.4% of accuracy, which is higher than 66.7% of the best previous accuracy. We also achieve similar results not only with F-score but also with similar experiments related to Japanese. Moreover, we prove that our detector can recognize both machine-translated and machine-back-translated texts without the language information which is used to generate these machine texts. It demonstrates the persistence of our method in various applications in both low- and rich-resource languages., Comment: INLG 2019, 9 pages

Based on Reddy's higher-order shear deformation plate theory, this article presents an analysis of the nonlinear dynamic response and vibration of imperfect functionally graded material (FGM) thick plates subjected to blast and thermal loads resting on elastic foundations. The material properties are assumed to be temperature-dependent and graded in the thickness direction according to a simple power-law distribution in terms of the volume fractions of the constituents. Numerical results for the dynamic response and vibration of the FGM plates with two cases of boundary conditions are obtained by the Galerkin method and fourth-order Runge–Kutta method. The results show the effects of geometrical parameters, material properties, imperfections, temperature increment, elastic foundations, and boundary conditions on the nonlinear dynamic response and vibration of FGM plates.

Some countries concentrate to study on BIM as an effective tool in quantities taking-off and costs estimating. In contrast, due to special features of Vietnamese law regulations, issues on BIM application for these works are still not considered properly in Vietnam. Therefore, in this research, the authors would like to review studies performed on BIM uses on these works in Vietnam, and to analyze the necessities and difficulties when using BIM for automatically taking off quantities and estimating construction costs, then to propose technology methods for addressing this issue. Two methods are proposed to automatically calculate construction works quantities and costs based on models designed in Revit, more specifically, the first one is using Keynote to develop a database on components codes and to establish the components schedule in Revit; the second is using Dynamo to develop connection nodes between Revit models and Excel Sheets, facilitating the data export from Revit to Excel, then using Excel to adjust data in consistency with models.

Despite the enactment of several privacy laws by the governments of several nations, achieving user privacy on the Internet has remained elusive, primarily due to the conflicting objectives of the stakeholders, i.e., users, web-based service providers, represented primarily by Internet Service Providers (ISPs) and governments. Internet usage data is still collected by ISPs and in certain jurisdictions is mandated by law, even with the inherent risk of possible data breaches that this brings. Data breaches have become very common nowadays and have affected several large renowned organizations and are likely to occur again in the future. To this end, it is not uncommon to find certain users resorting to the user of peer-to-peer anonymity services like Tor. According to Tor metrics, at least 2 million people use Tor on a daily basis. This number would probably be higher if more users were aware of online privacy risks and were tech-savvy enough to install it on their systems. Using services like Tor, however has its downside, primarily because its legitimate users are likely to be viewed suspiciously by law enforcement due to the abuse of the service by criminal elements. In this paper, we propose a web access protocol that guarantees basic user anonymity while trying to achieve a compromise on the conflicting objectives of the stakeholders. The protocol simultaneously provides anonymity to the user, allows the web usage data to be analyzed by interested parties (e.g., the ISP), and reduces the risk of abuse by criminal elements thereby allowing for flexibility in the enactment of laws that mandate collection of web usage information in support of law enforcement. The main techniques used in our protocol are: (i) the Onion Protocol, which is used to conceal web users' identities, (ii) the Secure Computation, which allows the parties (user and ISP) to jointly compute a common function while keeping those inputs private, (iii) and the Licensing and Digital Certificates, which ensure that only authorized web-content providers can provide content to users who want to be anonymous and that no one can impersonate the service providers licensed to provide services anonymously.

Background: BMIs of Vietnamese type 2 diabetes mellitus (DM) are within the normal range. We felt that the crucial factor in DM is not obesity but rather low intake of vegetables and fiber (transition nutrition). Fiber has effect on controlling blood glucose. The main source of fiber in Vietnamese cuisine is vegetables but consumption is very low. In this study, we tried to increase vegetable and fiber intakes by using dressing and mayonnaise which are new foods in Vietnamand assessed their effects on blood glucose concentrations. Methods: We contacted 300 subjects from 2,000 DM outpatients at a hospital and selected 60 of them for the study. We made 30 pairs matched by sex, age, BMI and years of DM, and divided them randomly into intervention and control group. Both groups received basic nutrition education about vegetables. The intervention group was further instructed to use dressing and mayonnaise. At the baseline and final periods, anthropometric measurements, blood withdrawal and a 3-day weighing method nutrition survey were conducted. Results: From our daily contact, we think that vegetable intakes were 300g and 450g in the control and intervention group, respectively were maintained throughout the whole period. The fructosamine concentration in the intervention group had decreased significantly (P0.05). There was a negative correlation between vegetable intake and blood fructosamine levels. Conclusion: By using dressing and mayonnaise for 2 weeks, vegetable and fiber intakes were consumed about 450g and 12g a day respectively and fructosamine levels dropped.

Cloud Computing is a service by which clients can outsource their data to reduce the burdens of data storage and maintenance. However, cloud providers are untrustworthy, which therefore introduce several security challenges: data integrity, data availability and data confidentiality. Since integrity and availability are prerequisite conditions for the existence of a system, researchers focus on these before confidentiality. To ensure integrity and availability, network coding-based POR (Proof of Retrievability) schemes have been proposed to enable the client to check whether the distributed data stored in the cloud servers is intact or not. However, most existing schemes have not achieved exact-repair feature and efficiency. In this paper, we propose a new POR scheme named SW-POR (Slepian-Wolfbased Proof of Retrievability) to address these gaps. Our scheme supports exact repair in which the repaired data is the same as the original corrupted data. Our scheme also can reduce the storage, computation, communication overheads and the size of a coded block. We proposed SW-POR based on Slepian-Wolf data compression code. We prove our security using entropy theory and implement SW-POR to show the costs.

This paper proposes a force sensing method with periodic component extraction based on Kalman filter algorithm. In a ball-screw system exhibiting high friction, a dither is inserted to the desired reference signal to eliminate the effect of friction. The force estimation by a disturbance observer is integrated with the force estimation by Kalman filter to construct the force sensation with effective oscillatory component extraction. The disturbance observer estimates the oscillatory torque caused by dither signal. The Kalman filter uses this oscillatory torque as a measurable input to estimate the periodical torque, the first derivative and second derivative of periodical torque. The torque with oscillatory component extraction is generated from estimations achieved by Kalman filter. Moreover, because the force sensation is based on Kalman filter, the effect of noise in force estimation is suppressed effectively. Therefore, it is possible to increase the bandwidth of the force sensing. The effectiveness of the proposed method is verified by numerical simulation results based on experimental data of force control of a ball-screw system.

Item does not contain fulltext BACKGROUND: Talaromyces marneffei infection is a major cause of human immunodeficiency virus (HIV)-related death in South and Southeast Asia. Guidelines recommend initial treatment with amphotericin B deoxycholate, but this drug has substantial side effects, a high cost, and limited availability. Itraconazole is available in oral form, is associated with fewer unacceptable side effects than amphotericin, and is widely used in place of amphotericin; however, clinical trials comparing these two treatments are lacking. METHODS: In this open-label, noninferiority trial, we randomly assigned 440 HIV-infected adults who had talaromycosis, confirmed by either microscopy or culture, to receive either intravenous amphotericin B deoxycholate (amphotericin) (219 patients), at a dose of 0.7 to 1.0 mg per kilogram of body weight per day, or itraconazole capsules (221 patients), at a dose of 600 mg per day for 3 days, followed by 400 mg per day, for 11 days; thereafter, all the patients received maintenance therapy with itraconazole. The primary outcome was all-cause mortality at week 2. Secondary outcomes included all-cause mortality at week 24, the time to clinical resolution of talaromycosis, early fungicidal activity, relapse of talaromycosis, development of the immune reconstitution inflammatory syndrome (IRIS), and the side-effect profile. RESULTS: The risk of death at week 2 was 6.5% in the amphotericin group and 7.4% in the itraconazole group (absolute risk difference, 0.9 percentage points; 95% confidence interval [CI], -3.9 to 5.6; P

Nowadays, Content Centric Networking (CCN) could be the future Internet architecture for its advance feature: In-network caching due to cheaper to cache than to transmit contents nowadays. Besides, the popularity of content in CCN gives much challenge to researchers, but there are a few solutions for that, such as LCD (Leave Copy Down). LCD policy is known as simple and effective caching mechanism so far. This work presents a new way of cooperation between CCN nodes in caching mechanism. Our caching mechanism is an optimization of LCD that some CCN nodes can help the others for their work on caching decision policy. This cooperation method doesn’t require both additional signaling packet and much computation resource to work. Experiments show that this optimization in terms of cache hit can achieve better than convention LCD does. In additional, our solution is simple and very low overhead.

International audience; The use of Public-Private Partnerships (PPPs) to realize and operate public infrastructures is often associated with fiscal-circumventing motivations. Using data at the municipal level, this paper investigates whether budget-constrained public authorities adopt PPPs in order to hide public debt. The results show that financial difficulties often lead to a preference for PPPs instead of traditional forms of public procurement, but this behaviour is not explained by the possibility of debt-hiding. Explanations for these findings are discussed.

Oblivious RAM (ORAM) is a primitive for hiding storage access patterns in the context of software protection. With the trend of cloud computing, ORAM also has important applications in privacy-preserving cloud storage applications. Many ORAMs for cloud storage have been proposed to improve efficiency and security. However, data availability, data confidentiality, and data integrity have not been simultaneously addressed. In this paper, we formalize a new concept of ORAM called RORAM (Robust ORAM by enhancing availability, confidentiality and integrity), which can deal with these three challenges. Furthermore, RORAM not only can achieve a higher security level but also is more efficient compared with previous ORAMs by using linear network coding to reduce the client's computational cost of block encryption/decryption in every read/write operation in previous ORAMs. The security and complexity analyses show that RORAM is provably secure and highly lightweight.

In this paper, a novel force-sensing method is proposed for a high-performance force control system based on friction-free and noise-free force observation. A periodic signal is inserted into the control system for friction reduction. A combination of a high-order disturbance observer (DOB) (HDOB) and a Kalman filter is constructed to perform the force sensing. The HDOB is designed to estimate the force and reject oscillatory disturbances in the estimation. The force-sensing bandwidth is improved through effective noise suppression by the Kalman filter. Additionally, this paper proposes the application of the HDOB to the bilateral control system of a different master-slave mechanism. All the control algorithms are implemented in a field-programmable gate array with a high sampling rate that also enables the widening of the bandwidth of the force control system. The effectiveness of the proposed method is verified by experimental results.

Cloud storage has been gaining in popularity as an on-line service for archiving, backup, and even primary storage of files. However, due to the data outsourcing, cloud storage also introduces new security challenges, which require a data audit and data repair service to ensure data availability and data integrity in the cloud. In this paper, we present the design and implementation of a network-coding-based Proof Of Retrievability scheme called ELAR, which achieves a lightweight data auditing and data repairing. In particular, we support direct repair mechanism in which the client can be free from the data repair process. Simultaneously, we also support the task of allowing a third party auditor (TPA), on behalf of the client, to verify the availability and integrity of the data stored in the cloud servers without the need of an asymmetric-key setting. The client is thus also free from the data audit process. TPA uses spot-checking which is a very efficient probabilistic method for checking a large amount of data. Extensive security and performance analysis show that the proposed scheme is highly efficient and provably secure.

Proof Of Retrievability (POR) is a protocol that supports a data owner to check whether the data stored in cloud servers is available, intact and retrievable. Based on the POR, network coding technique has been applied to increase efficiency and throughput in data transmission and data repair. Although many network coding-based PORs have been proposed, most of them have not considered a practical scenario in which not only the data owner can check and can retrieve the data stored in the untrusted servers, but also an untrusted user can check and can retrieve the data stored in the servers without learning the secret keys of the data owner. This scenario occurs commonly in reality. For instance, in a data provision-payment system, the user must pay money to get data stored in the servers. In this paper, we propose a new network coding-based POR, named POR-2P (a network coding-based POR for data Provision-Payment system), to deal with this scenario. Furthermore, the complexity analysis and the performance evaluation show that the POR-2P is very efficient and applicable for a real cloud system.

Force sensation plays an important role in force control systems. The bandwidth of force sensing is vital to reproduce the vivid force information. Generally, sensor-less force control systems use the position-sensor-based disturbance observer for force estimation. The bandwidth of force sensation as well as the control performance, however, is limited by the noise problems. This paper proposes a method to achieve the high performance force sensing. In the paper, the force estimation operation is performed by a combination of a Kalman-filter and a disturbance observer implemented in a field programmable gate array (FPGA). The wide bandwidth force sensing can be attained owing to the shortened sampling time by FPGA. Moreover, the noise in the force information is suppressed effectively by the Kalman-filter. The experimental results show the viability of the proposed method.

INTRODUCTION Knowledge about type 2 diabetes (T2D) and attitude towards the condition are known to affect compliance and play an important role in diabetes management. T2D knowledge is a prerequisite for individuals and communities to take action on control of the disease. METHODS A cross-sectional study was designed to identify knowledge and related factors towards T2D, risk factors, complications, prevention and treatment of the disease. A total of 2580 subjects representative of the general population aged 40-64 years was recruited from a typical province of Red River Delta region, Vietnam. The trained surveyors interviewed subjects directly to collect data, using a structured questionnaire. To evaluate the overall knowledge of T2D, 14 questions were used to calculate the 100 points. Total knowledge score was classified into the following four categories: highly insufficient (≤25 points), insufficient (26-50 points), satisfactory (51-75 points), and highly satisfactory (>75 points). Association between inadequate knowledge (

To enhance the productivity and quality, high speed and high precision industrial robots are required. In the highspeed motion, the dynamic torque of industrial robot prevents the precise operation. To achieve high speed and high precision operation, the dynamic torque calculation is often used to compensate the dynamic torque. Although, it is difficult to calculate the accurate dynamic torque because the accurate dynamic parameters is difficult to obtain. To estimate the dynamic torque without the dynamic torque calculation, this paper uses the disturbance observer (DOB). To achieve the instantaneous dynamic torque estimation of industrial robot, the authors have proposed an instantaneous state observer (ISOB). However, the load torque estimated by the ISOB becomes noisy because the acceleration sensor has the measurement noise. To overcome this problem, this paper proposes a new method for instantaneous load torque estimation using the ISOB and a variable noise-covariance (VNC) Kalman filter. The effectiveness of VNC Kalman filter based ISOB is confirmed by the numerical simulation and experiments using the single joint of industrial robot arm.

POR (Proof of Retrievability) is a protocol by which clients can distribute their data to cloud servers and can check if the data stored in the servers is available and intact. Based on the POR, the network coding is applied to improve network throughput. Although many network coding-based PORs have been proposed, most of them have not achieved the following practical features: direct repair and dynamic operations. In this paper, we propose the DD-POR (Dynamic operations and Direct repair in network coding-based POR) to address these shortcomings. When a server is corrupted, the DD-POR can support the direct repair in which the data stored in the corrupted server can be repaired using the data provided directly from the healthy servers. The client is thus free from the burden of data repair. Furthermore, the DD-POR allows the client to efficiently perform dynamic operations, i.e., modification, insertion and deletion.

Secret sharing scheme has been applied commonly in distributed storage for Big Data. It is a method for protecting outsourced data against data leakage and for securing key management systems. The secret is distributed among a group of participants where each participant holds a share of the secret. The secret can be only reconstructed when a sufficient number of shares are reconstituted. Although many secret sharing schemes have been proposed, they are still inefficient in terms of share size, communication cost and storage cost; and also lack robustness in terms of exact-share repair. In this paper, for the first time, we propose a new secret sharing scheme based on Slepian-Wolf coding. Our scheme can achieve an optimal share size utilizing the simple binning idea of the coding. It also enhances the exact-share repair feature whereby the shares remain consistent even if they are corrupted. We show, through experiments, how our scheme can significantly reduce the communication and storage costs while still being able to support direct share repair leveraging lightweight exclusive-OR (XOR) operation for fast computation.

Background Metabolic syndrome (MetS) is a clustering of metabolic risk factors for cardiovascular diseases and type 2 diabetes. The study aimed to estimate the prevalence of MetS, its components, and their associations among rural middle-aged population in Vietnam. Methods A cross-sectional study with a representative sample (n = 2443) was conducted to collect data on demographic, socioeconomic, anthropometric, lifestyles, plasma glucose, and lipid profile. The age- and sex-adjusted prevalences of MetS and its components were calculated using the direct standardization. Associations of risk factors with MetS were evaluated using logistic regression, taken into account the confounding factors. Results The total age- and sex-adjusted prevalence (95% CI) of MetS was 16.3% (14.0 - 18.6). The most frequent component of MetS was high triglycerides (43.2%), followed by low HDL-C (42.0%), elevated blood pressure (29.2%), high plasma glucose (14.3%), and central obesity (12.3%). Of the total population, only 17.6% did not have any component of MetS and more than 40% had at least two MetS components. The association of MetS with residence, age, body mass index, marital status, and siesta time per day was statistically significant in univariate analysis and replicated in multivariate analysis. Conclusion The MetS prevalence and its components are common and major public health burden in the middle-aged adults in Vietnam. Habitants living in urban, being never-married, having an increase in age, BMI, and siesta time per day are significantly associated with MetS, and they should be paid much more attention for screening and implementing preventive activities.

This paper presents a motion-copying system of different master-slave mechanism in variable speed of motion reproduction. The motion-saving system is performed by bilateral control algorithm to preserve arbitrary motions of human operator to a data memory. The slave actuator is affected by friction; hence, a friction-free disturbance observer is employed for force estimation on the slave side. The motion-loading system is able to reproduce human motion saved in data memory with changeable speed of motion reproduction. To improve the performance of motion-loading system, a displacement-based reproduction correction is used to eliminate the effect of unpredictable disturbances in variable speed of motion regeneration. The effectiveness of the proposed method is confirmed by simulation results.