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Giới thiệu mạng TEIN2 và mạng VINAREN

Bài viết giới thiệu mạng TEIN2 và mạng VINAREN; mạng thông tin Khoa học và Công nghệ Việt Nam, mạng EduNet, các Trung tâm vận hành mạng, các thành viên của VINAREN. Để nắm chi tiết nội dung mời các bạn cùng tham khảo bài viết.


Bài tập Pascal: Phần Mảng 2 chiều - Th.S Nguyễn Anh Việt

Tài liệu cung cấp các bài tập của Pascal về mảng 2 chiều bao gồm 8 bài tập với các nội dung như số lớn nhất của mảng, số lớn nhất trong mỗi dòng của mảng, đường chéo chính của ma trận vuông, đường chéo phụ của ma trận vuông, số lớn nhất trên đường chéo phụ của ma trận vuông, số nhỏ nhất trên đường chéo chính của ma trận vuông, tìm số lớn nhất trên mỗi dòng của ma trận vuông và đổi vị trí ra đầu dòng. Mời các bạn cùng tham khảo tài liệu để nắm chi tiết nội dung các bài tập.


A feature based model for nested named entity recognition at VLSP - 2018 ner evaluation campaign

In this paper, we describe our named-entity recognition system at VLSP 2018 evaluation campaign. We formalized the task as a sequence labeling problem using B-I-O encoding scheme and applied a feature-based model which combines word, word-shape features, Brown-cluster-based features, and word-embedding-based features.


Development of high performance and large scale Vietnamese automatic speech recognition systems

In this paper, we first describe our efforts in collecting a large data set that covers all 3 major accents of Vietnam located in the Northern, Center, and Southern regions. Then, we detail our ASR system development procedure utilizing the collected data set and evaluating different model architectures to find the best structure for Vietnamese.


A ciphertext-policy attribute-based searchable encryption scheme in non-interactive model

In this paper, we propose a public-key encryption with keyword search scheme relied on the ciphertext-policy attribute-based encryption scheme. In our system, we consider the model where a user can generate trapdoors by himself/herself, we thus can remove the Trusted Trapdoor Generator which can save the resource and communication overhead.


Novel optimal coordinated voltage control for distribution network 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.


An improvement method for semantic mapping databases to ontology

Enormous amount of available data in relational database (RDB) format creates a demand for automatic transforming them into Web Ontology Language (OWL) ontology to reuse in the Semantic Web. Many approaches have been proposed, however, most of them simply generate output ontology as the same flat structure with the original database and result in redundancy of ontology data.


SLBQT-DSR: Source based load balancing routing algorithm under constraints of quality of transmision for manet

In this paper, we improve the DSR protocol by using the source-based load balancing in combined with the QoT constraint. The simulation results have shown that, the proposed algorithm outperforms the original algorithms in terms of the signal to noise ratio, bit error rate, blocking probability of the data packets and throughput.


Development of Vietnamese speech synthesis system using deep neural networks

In this paper, we present our first Vietnamese speech synthesis system based on deep neural networks. To improve the training data collected from the Internet, a cleaning method is proposed. The experimental results indicate that by using deeper architectures we can achieve better performance for the TTS than using shallow architectures such as hidden Markov model.


Mining Top-K frequent sequential pattern in item interval extended sequence database

Frequent sequential pattern mining in item interval extended sequence database (iSDB) has been one of the interesting tasks in recent years. Unlike classic frequent sequential pattern mining, the pattern mining in iSDB also considers the item interval between successive items; thus, it may extract more meaningful sequential patterns in real life.


Pedestrian activity prediction based on semantic segmentation and hybrid of machine

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.


Product sub-vector quantization for feature indexing

This work addresses the problem of feature indexing to significantly accelerate the matching process which is commonly known as a cumbersome task in many computer vision applications. To this aim, we propose to perform product sub-vector quantization (PSVQ) to create finer representation of underlying data while still maintaining reasonable memory allocation.


A new hybrid fuzzy time series forecasting model based on combing fuzzy C-means clustering and particle swam optimization

In this paper, a novel FTS forecasting model based on fuzzy C-means (FCM) clustering and particle swarm optimization (PSO) was developed to enhance the forecasting accuracy. Firstly, the FCM clustering is used to divide the historical data into intervals with different lengths. After generating interval, the historical data is fuzzified into fuzzy sets.


Simulation of reconfiguration system using Matlab - Simulink environment

Reconfiguration strategy of solar energy has been a challenging task in the energy optimization field, in which the intention is to minimize losses and increase efficiency of the photovoltaic (PV) system under non-homogeneous solar irradiation based on irradiance equalization.


Partition fuzzy domain with multi granularity representation 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.


Transforming extended entity relationship model into OWL ontology in temporal database

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.


Nonstandard finite difference schemes for solving a modified epidemiological model for computer viruse

In this paper we construct two families of nonstandard finite difference (NSFD) schemes preserving the essential properties of a computer virus propagation model, such as positivity, boundedness and stability.


A transformation method for aspect based sentiment analysis

In this paper, we describe our system for this shared task. We employ a supervised learning method based on the Support Vector Machine classifiers combined with a variety of features.


SIR-DL: An architecture of semantic based image retrieval using deep learning technique and RDF triple language

In this paper, we propose the Semantic-Based Image Retrieval (SBIR) system based on the deep learning technique; this system is called as SIR-DL that generates visual semantics based on classifying image contents.


Hupsmt: An efficient algorithm for mining high utility probability sequences in uncertain databases with multiple minimum utility threshold

This paper proposes a framework for mining high utility-probability sequences (HUPSs) in uncertain QSDBs (UQSDBs) with multiple minimum utility thresholds using a minimum utility.


Automatic heart disease prediction using feature selection and data mining techniques

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.


Acceleration in state-of-the-art ASR applied to a Vietnamese transcription system

This paper presents the adoption of state-of-the-art ASR techniques into Vietnamese. To better assess these techniques, speech corpora in the research community are assembled, and expanded, making a unified evaluation material under the name VN-Corpus.


Search for entities based on the implicit semantic relations

The paper presents extracting, clustering, ranking techniques and a model of search for entity based on implicit semantic relation on Vietnamese language domain.


New dissimilarity measures on picture fuzzy sets and applications

The dissimilarity measures between fuzzy sets/intuitionistic fuzzy sets/picture fuzzy sets are studied and applied in various matters. In this paper, we propose some new dissimilarity measures on picture fuzzy sets.


Giáo án Kỹ thuật lập trình PLC

Giáo án biên soạn các bài học như: giới thiệu chung về PLC và bài toán điều khiển, đại cương về điều khiển lập trình, các phép toán nhị phân của PLC, các phép toán nhị phân của PLC, các phép toán số của PLC, xử lý tín hiệu analog, PLC của các hãng khác, lắp đặt mô hình điều khiển bằng PLC.


Bài giảng Microsoft Excel 2016

  • 5/5 (1)

Bài giảng gồm các nội dung: tổng quan về MS Excel 2016, định dạng bảng tính, công thức và hàm, các thao tác với dữ liệu, đồ thị trong Excel, định trang và in ấn. Mời các bạn cùng tham khảo bài giảng để nắm chi tiết nội dung.


Obstacle detection and warning system for visually impaired people based on electrode matrix and mobile Kinect

This system consists of two main components: Environment information acquisition and analysis and information representation. The first component aims at capturing the environment by using a mobile Kinect and analyzing it in order to detect the predefined obstacles for visually impaired people, while the second component tries to represent obstacle’s information under the form of electrode matrix.


Evaluation of educational applications in terms of communication delay between tablets with Bluetooth or Wi-Fi Direct

This study conducted a survey to implement educational applications that can share information even in environments where access points cannot be used. In particular, we investigated whether Bluetooth (widely used for many years) or Wi-Fi Direct (developed recently) is more suitable when creating educational applications using an ad hoc network.


Precomputing architecture for flexible and efficient big data analytics

The rising of big data brings revolutionary changes to many aspects of our lives. Huge volume of data, along with its complexity poses big challenges to data analytic applications. Techniques proposed in data warehousing and online analytical processing, such as precomputed multidimensional cubes, dramatically improve the response time of analytic queries based on relational databases. There are some recent works extending similar concepts into NoSQL such as constructing cubes from NoSQL stores and converting existing cubes into NoSQL stores


Short-term load forecasting in smart meters with sliding window-based ARIMA algorithms

This paper presents two non-seasonal and two seasonal sliding window-based ARIMA (auto regressive integrated moving average) algorithms. These algorithms are developed for short-term forecasting of hourly electricity load at the district meter level.


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