Selection of suitable fragment from rbcL gene for DNA barcode analysis of family Halymeniaceae, Rhodophyta

Among the members of Halymeniaceae family, Grateloupia sensu lato occupies the largest composition in species. Classification based on morphological traits is difficult due to the highly variable terete to blade-like thalli among the members of this genus that usually leads to misidentification. Molecular systematics has been applied to classify Grateloupia sensu lato so that the taxonomists acquire a better understanding of the species diversity in general. The plastid gene encoding the large subunit of ribulose-1,5-bisphosphate-carboxylase-oxygenase (rbcL) was the focus of numerous marine algal studies concerning phylogeny and molecular evolution. However, using the full length of rbcL showed disadvantages such as cost and time consuming due to two times of sequencing and two times of PCR. In the present study, the shorter sequence, fragment 773 bp at 5’ end and fragment 579 bp at 3’ end of rbcL were applied and compared for the phylogenetic analysis of Halymeniaceae members. The results indicated there are no differences of topological phylogenetic trees, species resolution within genus and genus resolution within the family between fragment 773 bp at 5’ and the full length of rbcL. Therefore, we conclude that fragment 773 bp at 5’ should be used as DNA barcodes for the Halymeniaceae to reduce the cost and time during phylogenetic analysis. Two taxa Grateloupia newly collected in Vietnam were grouped to the known Phyllymenia, a new genus in Vietnam

A Structured SVM Semantic Parser Augmented by Semantic Tagging with Conditional Random Field

PACLIC 19 / Taipei, taiwan / December 1-3, 200

Optimizing Boiler Efficiency by Data Mining Teciques: A Case Study

In a fertilizer plant, the steam boiler is the most important component. In order to keep the plant operating in the effective mode, the boiler efficiency must be observed continuously by several operators. When the trend of the boiler efficiency is going down, they may adjust the controlling parameters of the boiler to increase its efficiency. Since manual operation usually leads to unex-pectedly mistakes and hurts the efficiency of the system, we build an information system that plays the role of the operators in observing the boiler and adjusting the controlling parameters to stabilize the boiler efficiency. In this paper, we first introduce the architecture of the information system. We then present how to apply K-means and Fuzzy C-means algorithms to derive a knowledge base from the historical operational data of the boiler. Next, recurrent fuzzy neural network is employed to build a boiler simulator for evaluating which tuple of input values is the best optimal and then automatically adjusting controlling inputs of the boiler by the optimal val-ues. In order to prove the effectiveness of our system, we deployed it at Phu My Fertilizer Plant equipped with MARCHI boiler having capacity of 76-84 ton/h. We found that our system have improved the boiler efficiency about 0.28-1.12% in average and brought benefit about 57.000 USD/year to the Phu My Fertilizer Plant

Unsupervised Detection of Anomalous Sound for Machine Condition Monitoring using Fully Connected U-Net

Anomaly detection in the sound from machines is an important task in machine monitoring. An autoencoder architecture based on the reconstruction error using a log-Mel spectrogram feature is a conventional approach for this domain. However, because of the non-stationary nature of some sounds from the target machine, such a conventional approach does not perform well in those circumstances. In this paper, we propose a novel approach regarding the choice of used features and a new auto-encoder architecture. We created the Mixed Feature, which is a mixture of different sound representations, and a new deep learning method called Fully-Connected U-Net, a form of autoencoder architecture. With experiments on the same dataset as the baseline system, using the same architecture for all types of machines, the experimental results showed that our methods outperformed the baseline system in terms of the AUC and pAUC evaluation metrics. The optimized model achieved 83.38% AUC and 64.51% pAUC on average overall machine types on the developed dataset and outperformed the published baseline by 13.43% AUC and 8.13% pAUC

Vietnamese Word Segmentation with CRFs and SVMs: An Investigation

PACLIC 20 / Wuhan, China / 1-3 November, 200

On the Dynamical Symmetry Breaking of the Electroweak Interactions by the Top Quark

We discuss the electroweak gauge symmetry breaking triggered by a new strong attractive interaction to condensate fermion-antifermion, and topcolor is a prototype. To deal with the fermion pairing, a general method based on the Hubbard-Stratonovich transformation in the functional integral approach is used. We derive a formula which relates the $W^\pm$, $Z^0$ weak boson masses to that of the condensated fermion, thus generalizing the Pagels-Stokar formula obtained in QCD. The custodial SU(2) electroweak symmetry turns out to be systematically violated, the deviation of $\rho\equiv M_W^2/(M_Z^2\cos^2\theta_W)$ from unity is related to the new physics scale $\Lambda$. Some phenomenological consequences of the top-pair condensation models are discussed. Distinctive signatures of the $\bar{t}t$ scalar bound state, a Higgs boson like denoted by $H_t$, are the dominant decay modes $H_t\to \Upsilon +\gamma ,$ $H_t\to \Upsilon +Z^0$, and $H_t \to B^* +\bar{B}^*$.Comment: Latex2e 9 pages, 2 postscript figures, 1 postscript log

Performance Analysis of Hybrid ALOHA/CDMA RFID Systems with Quasi-decorrelating Detector in Noisy Channels

In this paper we investigate the performance of a hybrid Aloha/CDMA radio frequency identification (RFID) system with quasi-decorrelating detector (QDD). Motivated by the fact that the QDD outperforms the conventional decorrelating detector (DD) in noisy network scenarios, we study and propose using QDD as one of the most promising candidates for the structure of RFID readers. Performance analysis in terms of bit error rate and the RFID system efficiency is considered considering CDMA code collision and detection error. Computer simulations are also performed, and the obtained results of QDD-based structure are compared with those of DD-based one to confirm the correctness of the design suggestion in different practical applications of tag identification and missing-tag detection

A Target Threat Assessment Method for Application in Air Defense Command and Control Systems

Introduction. This paper presents a solution for threat assessment of air targets using the fuzzy logic inference method. The approach is based on the Sugeno fuzzy model, which has multiple inputs representing target trajectory parameters and a single output representing the target threat value. A set of IF–THEN fuzzy inference rules, utilizing the AND operator, is developed to assess the input information.Aim. To develop and test an algorithm model to calculate the threat value of an air target for use in real-time automated command and control systems.Materials and methods. An algorithm model was developed using a fuzzy model to calculate the threat value of a target. The model is presented in the form of a flowchart supported by a detailed stepwise implementation process. The accuracy of the proposed algorithm was evaluated using the available toolkit in MATLAB. Additionally, a BATE software testbed was developed to assess the applicability of the algorithm model in a real-time automated command and control system.Results. The efficiency of the proposed fuzzy model was evaluated by its simulation and testing using MATLAB tools on a set of 10 target trajectories with different parameters. Additionally, the BATE software was utilized to test the model under various air defense scenarios. The proposed fuzzy model was found to be capable of efficiently computing the threat value of each target with respect to the protected object.Conclusion. The proposed fuzzy model can be applied when developing tactical supporting software modules for real-time air defense command and control systems.Introduction. This paper presents a solution for threat assessment of air targets using the fuzzy logic inference method. The approach is based on the Sugeno fuzzy model, which has multiple inputs representing target trajectory parameters and a single output representing the target threat value. A set of IF–THEN fuzzy inference rules, utilizing the AND operator, is developed to assess the input information.Aim. To develop and test an algorithm model to calculate the threat value of an air target for use in real-time automated command and control systems.Materials and methods. An algorithm model was developed using a fuzzy model to calculate the threat value of a target. The model is presented in the form of a flowchart supported by a detailed stepwise implementation process. The accuracy of the proposed algorithm was evaluated using the available toolkit in MATLAB. Additionally, a BATE software testbed was developed to assess the applicability of the algorithm model in a real-time automated command and control system.Results. The efficiency of the proposed fuzzy model was evaluated by its simulation and testing using MATLAB tools on a set of 10 target trajectories with different parameters. Additionally, the BATE software was utilized to test the model under various air defense scenarios. The proposed fuzzy model was found to be capable of efficiently computing the threat value of each target with respect to the protected object.Conclusion. The proposed fuzzy model can be applied when developing tactical supporting software modules for real-time air defense command and control systems

Review and Evaluation of Agricultural Policies in Years 2015-2017

This journal article describes main results of the OECD Annual Report published in 2018, titled “Review and evaluation of agricultural policy in 2017” for 51 selected countries in the world, including Vietnam. The report is closely prepared by MARD and OECD experts. The journal article emphasizes more on Vietnam by updating and adjusting data, information and policies in 2017 and 2018. The description presents the changing trend of agricultural policies applied in the world, considering whether this trend is in the direction of achieving sustainable productivity growth, environmental protection, and adaptation to climate change. On average in the last 20 years, trend of world policies has been better but far to catch above purposes. The development of international trade has made the commodity movement more freely and price gaps narrowed between countries and regions. This trend made agricultural markets developed more toward reflecting the scarcity of good and services. Average level of total agricultural supports has been reducing. Consequently, the world price indices and the total support have been converted between countries and commodities. However, the total agricultural support reduction is mainly in developed countries like OECD countries. Emerging and developing countries have increased their agricultural supports. Relative to GDP, the level of the total agriculture support in Vietnam has been reducing.Inside the total agricultural support, producer supports accounted 78% while general service support accounted only for 14%. Inside the producer support, market price support accounted for more than 50% in many countries. Payments based on outputs and inputs also accounted more than 50% in many countries. In Vietnam, the producer support is very small, negative level in 2015 and 2016 and became positive in 2017 and 2018. The agricultural producer support in 2017 is about 900 million USD. In the overall service support, many countries mainly invest in infrastructure construction, for example in Japan and Vietnam over 70%, while investments in other items are too small, for example that in Vietnam is only about 16%.In conclusion, OECD suggests that market price support should be reduced and finally eliminated. Similarly, output and input payments should be reduced and eliminated. Future policies should focus on general support service that helps producers to achieve sustainable productivity growth in the context of a changing and uncertain climate. OECD especially emphasizes on appropriate investments in research, together with efforts to ensure that the outputs of this research reach farmers. OECD also emphasizes on research that help producers to better manage risks including business risk, weather risk, and climate changes. Agricultural production and climate changes are strongly interacted. Future research should be the better co-operation between public and private sectors with the leading role of public sector. The future research should be co-operated more strongly between countries and regions because of the differences in histories, cultures, geology and climate