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Data assimilation method in flood forecasting for red river system using high performent computer

This paper demonstrates the efficiency of the method to identify time-dependent parameter: inflow discharge with a real complex case Red River. Firstly, we briefly discuss about current methods for determining flow rate which encompasses the new technologies, then present the ability to recover flow rate of this method.


Phần mềm quản lý đối tượng cho công an các xã thị trấn

Phần mềm quản lý đối tượng cho công an các xã thị trấn bao gồm: Lưu lý lịch một đối tượng có tiền án và tiền sự, lưu đối tượng có kèm hình ảnh của một đối tượng, sao lưu và phục hồi dữ liệu được lập trình chuẩn, phần mềm chạy ổn định trên tất cả các hệ điều hành. Mời các bạn tham khảo!


Bài giảng Phương pháp chỉ số dẫn báo và ứng dụng - PSG.TS. Đỗ Văn Thành

Bài giảng Phương pháp chỉ số dẫn báo và ứng dụng do PSG.TS. Đỗ Văn Thành biên soạn nhằm giới thiệu cho người học những nội dung sau: Chỉ số báo trước, chỉ số báo đồng thời và phương pháp xác định các chỉ số này; Mô hình dự báo được xây dựng dựa trên các chỉ số báo trước, chỉ số báo đồng thời; Phân tích thông tin rút ra từ mô hình; Case Study: Ứng dụng chỉ số báo trước, báo đồng thời trong việc dự báo chỉ số kinh tế vĩ mô/cảnh báo kinh tê theo quý cho Việt Nam; Case Study: Ứng dụng chỉ số báo trước trong việc xây dựng mô hình dự báo không điều kiện chỉ số VNINDEX. Để nắm vững những kiến thức trong bài giảng, mời các bạn cùng tham khảo.


Những nội dung ôn tập java core

Tài liệu "Những nội dung ôn tập java core" trình bày các tính Chất Của Java OOPs, các kiểu dữ liệu, các từ khóa (static, final, abstract , Interface , override, overload…) và xử lý ngoại lệ trong java. Mời các bạn tham khảo!


Some new de morgan picture operator triples in picture fuzzy logic

Some basic operators of fuzzy logic as negation, t-norms, t-conorms for picture fuzzy sets firstly are defined and studied in [6, 9]. This paper is devoted to some classes of representable picture fuzzy t-norms and representable picture fuzzy t-conorms on PFS and a basic algebra structure of Picture Fuzzy Logic De Morgan triples of picture operators.


Automatic heart disease prediction using feature selection and data mining technique

This paper presents an automatic Heart Disease (HD) prediction method based on feature selection with data mining techniques using the provided symptoms and clinical information assigned in the patients dataset. Data mining which allows the extraction of hidden knowledges from the data and explores the relationship between attributes, is the promising technique for HD prediction.


A grasp +vnd algorithm for the multiple traveling repairmen problem with distance constraints

In our work, we propose a metaheuristic algorithm which is mainly based on the principles of Greedy Randomized Adaptive Search Procedure (GRASP) and Variable Neighborhood Descent (VND) to solve the problem. The GRASP is used to build an initial solution which is good enough in a construction phase.


A solution to detect and prevent wormhole attacks in mobile ad hoc network

This article proposes a valid route testing mechanism (VRTM) and integration of VRTM into AODV protocol to make DWAODV which is able to detect and prevent the wormhole attacks. Using Network Simulator (NS2), we evaluate the security effectiveness of DWAODV protocol on random movement network topology at high speed.


Minimizing makespan of personal scheduling problem in available time -windows with split min and setup time constraints

This paper deals with personal scheduling problem in available time-windows with splitmin and setup-time constraints. The jobs are splittable into sub-jobs and a common lower bound on the size of each sub-job is imposed. The objective function aims to find a feasible schedule that minimizes the total completion time of all jobs.


Taxonomic assignment for large scale metagenomic data on high perfomance systems

This study proposes a parallel algorithm for the taxonomic assignment problem, called SeMetaPL, which aims to deal with the computational challenge. The proposed algorithm is evaluated with both simulated and real datasets on a high performance computing system. Experimental results demonstrate that the algorithm is able to achieve good performance and utilize resources of the system efficiently


Partition fuzzy domain with multi granularity representation of data based on hedge algebra approach

This paper presents methods of dividing quantitative attributes into fuzzy domains with multi-granularity representation of data based on hedge algebra approach. According to this approach, more information is expressed from general to specific knowledge by explored association rules. As a result, this method brings a better response than the one using usual single-granularity representation of data. Furthermore, it meets the demand of the authors as the number of exploring rules is higher.


B-codes and their relationship with alternative codes

Codes of bounded words (b-codes, ♦-codes), an extension of the notion of ordinary codes, have been first introduced and considered by P. T. Huy et al. in 2009. In this note, we consider some new subclasses of b-codes. In particular, characteristic properties of such codes are established. Also, relationships between b-codes, alternative codes and their subclasses are considered.


GMM for emotion recognition of Vietnamese

The results showed that the recognition scores are rather high with the case for which there is a full combination of parameters as MFCC and its first and second derivatives, fundamental frequency, energy, formants and its correspondent bandwidths, spectral characteristics and F0 variants.


Congestion control algorithm for message routing in structured peer to peer networks

This paper proposes a congestion control algorithm for message routing in structured P2P networks by changing the routing table of nodes in the network to route the packet to the destination without going through congested nodes. The performance of the proposed the method has been evaluated and compared with the conventional Chord protocol.


Solving min max capacitated vehicle routing problem by local search

This paper investigates local search approach for solving the min-max capacitated vehicle routing problem with different neighborhood structures. We also propose a combined function instead of the objective function itself for controlling the local search. Experimental results on different datasets show the efficiency of our proposed algorithms compared to previous techniques.


Some algorithms related to consistent decision table

In this paper, we propose an algorithm finding object reducts of consistent decsion table. On the other hand, we also show an algorithm to find some attribute reducts and the correctness of our algorithms is proof-theoretical. These algorithms of ours have polynomial time complexity. Our finding object reduct helps other algorithms of finding attribute reducts become more effective, especially as working with huge consistent decision table.


Theoretical analysis of picture fuzzy clustering

Recently, picture fuzzy clustering (FC-PFS) has been introduced as a new computational intelligence tool for various problems in knowledge discovery and pattern recognition. However, an important question that was lacked in the related researches is examination of mathematical properties behind the picture fuzzy clustering algorithm such as the convergence, the boundary or the convergence rate, etc. In this paper, we will prove that FC-PFS converges to at least one local minimum. Analysis on the loss function is also considered.


Pedestrian activity prediction based on semantic segmentation and hybrid of machines

The article presents an advanced driver assistance system (ADAS) based on a situational recognition solution and provides alert levels in the context of actual traffic. The solution is a process in which a single image is segmented to detect pedestrians’ position as well as extract features of pedestrian posture to predict the action.


Novel optimal coordinated voltage control for distribution networks using differential evolution technique

This paper investigates a Distributed Generators (DG) connected to distribution networks offering multiple benefits for grids and environments in the case of renewable sources used. Nevertheless, this task requires an appropriate planning and control strategy, if not several drawbacks can issue, including voltage rise problems and increased power losses. To overcome such disadvantages, this paper proposes a coordinated voltage control CVC method for distribution networks with multiple distributed generators.


A novel algorithm based on trust authentication mechanisms to detect and prevent malicious nodes in mobile ad hoc network

The simulation results in NS2 show that TAM can successfully detect and prevent to 100% malicious nodes using fake keys and above 99% (the mistaken rate below 1.0%) wormhole nodes under hide mode for all mobility scenarios where there are nodes move with 30m/s maximum speeds and variable tunnel lengths.


Transforming extended entity relationship model into owl ontology in temporal databases

The objective of W3C is to transform the current Web into a Semantic Web to reuse the previous system. Many previous systems were built based on the ER model, so the upgradation and transformation of the ER model into ontology in order to reduce cost is really necessary. There are various studies aiming at transforming from ER and EER model into ontology; however, the studies have not still mentioned the transforming from the temporal databases into OWL ontology. Therefore, this paper proposes the rules for transforming the temporal components in TimeER model into OWL.


Hướng dẫn chấm thi thử trung học phổ thông quốc gia lần 3 môn Ngữ Văn năm học 2016 - 2017

Mời qúy thầy cô và các bạn cùng tham khảo tài liệu "Hướng dẫn chấm thi thử trung học phổ thông quốc gia lần 3 môn Ngữ Văn năm học 2016 - 2017" dưới đây để có thêm tài liệu học tập và kinh nghiệm chấm thi.


Algorithm to build fuzzy decision tree for data classification problem based on fuzziness intervals matching

The precise data classification cannot solve all the requirements. Thus, the fuzzy decision tree classification problem is important for the fuzzy data mining problem. The fuzzy decision classification based on the fuzzy set theory has some limitations derived from its innerself. The hedge algebra with many advantages has become a really useful tool for solving the fuzzy decision tree classification.


A genetic algorithm based method for university course timetabling problems and application in Hanoi open university

In this paper, we propose a method based on genetic algorithms for university course timetabling problems with some modifications and apply it to real-world datasets in Hanoi Open University.


Quality of transmission aware routing in ad hoc networks based on cross layer model combined with the static agent

This paper focused on investigating the routing techniques in ad hoc networks taking into account the quality of transmission. Thence, we proposed an improved routing algorithm of DSR based on the cross-layer model in combination with the static agent. The objective of the proposed algorithm is to improve the quality of the transmission signal, reduce the blocking probability of the data packets due to the unguaranteed quality of transmission.


Using sum match kernel with balanced label tree for large scale image classification

In addition, a feature map is used to reformulate the sum-match kernel function as a dot product of two mean feature vectors in a mapped-feature space. Furthermore, we proposed an algorithm for learning a balanced tree which gains the computational efficiency in classification. We carried out experiments on benchmark datasets including Caltech-256, SUN-397, and ImageNet-1K. The evaluation results indicated that our method achieves a significant improvement in terms of accuracy and efficiency compared to other methods. In particular, our method achieved 14.52% in accuracy on ImageNet-1K, compared to 6.51% of the Bengio et al.’s method.


Password encryption based on dynamic graph labeling priority generation (D.G.L.P.G.) technique

In this paper we propose a password encryption technique based on the “Dynamic Graph Labeling Priority Generation (D.G.L.P.G.) Technique” and “Dynamic False Node Insertion (D.F.N.I) Technique” for dynamic password. The algorithm has achieved very low space complexity and time complexity which is O(log n). The emerged technique fits itself in the boundary of the present requisition and is flexible enough to expand its magnitude with the amplifying needs up to the boundary mark of the presented algorithm.


An evaluation method for unsupervised anomaly detection algorithms

In this paper, the authors introduce a method for evaluating the performance of unsupervised anomaly detection techniques. The method is based on the application of internal validation metrics in clustering algorithms to anomaly detection. The experiments were conducted on a number of benchmarking datasets. The results are compared with the result of a recent proposed approach that shows that some proposed metrics are very consistent when being used to evaluate the performance of unsupervised anomaly detection algorithms.


Real - time table plane detection using accelerometer information and organized point cloud data from kinect sensor

In this paper, the authors propose a table plane detection method using information coming from a Microsoft Kinect sensor. The contribution of the paper is three-fold. First, for plane detection step, the dedicated down-sampling algorithms to original point cloud thereby representing it as the organized point cloud structure in are applied to get real-time computation. Second, the acceleration information provided by the Kinect sensor is employed to detect the table plane among all detected planes. Finally, three different measures for the evaluation of the table plane detector are defined.


Improving bottleneck features for Vietnamese large vocabulary continuous speech recognition system using deep neural networks

In this paper, the pre-training method based on denoising auto-encoder is investigated and proved to be good models for initializing bottleneck networks of Vietnamese speech recognition system that result in better recognition performance compared to base bottleneck features reported previously. The experiments are carried out on the dataset containing speeches on Voice of Vietnam channel (VOV).


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