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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.


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.


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.


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.


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.


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.


Aggregative context-aware fitness functions based on feature selection for evolutionary learning of characteristic graph patterns

We propose aggregative context-aware fitness functions based on feature selection for evolutionary learning of characteristic graph patterns. The proposed fitness functions estimate the fitness of a set of correlated individuals rather than the sum of fitness of the individuals, and specify the fitness of an individual as its contribution degree in the context of the set.


A hybrid mobile call fraud detection model using optimized fuzzy C-means clustering and group method of data handling-based network

A novel two-stage fraud detection system in mobile telecom networks has been presented in this paper that identifies the malicious calls among the normal ones in two stages. Initially, a genetic algorithm-based optimized fuzzy c-means clustering is applied to the user’s historical call records for constructing the calling profile. Thereafter, the identification of the fraudulent calls occurs in two stages.


A new multilevel reversible bit-planes data hiding technique based on histogram shifting of efficient compressed domain

In this paper, we proposed a new technique for reversible data hiding based on efficient compressed domain with multiple bit planes. We conducted a sequence of experiments to use block division scheme to appraise the result with different parameters and amended the probability of zero point in every block of histogram.


Using internal evaluation measures to validate the quality of diverse stream clustering algorithms

Measuring the quality of a clustering algorithm has shown to be as important as the algorithm itself. It is a crucial part of choosing the clustering algorithm that performs best for an input data. Streaming input data have many features that make them much more challenging than static ones.


Genetic algorithm as self-test path and circular self-test path design method

The paper presents the use of Genetic Algorithm to search for non-linear Autonomous Test Structures (ATS) in Built-In Testing approach. Such structures can include essentially STP and CSTP and their modifications. Non-linear structures are more difficult to analyze than the widely used structures such as independent Test Pattern Generator and the Test Response Compactor realized by Linear Feedback Shift Registers.


A bitwise-based indexing and heuristic-driven on-the-fly approach for Web service composition and verification

The work in this paper addresses the problem by proposing various approaches for handling the state-space exploration, including (i) an introduction of an LTS-based model known as LTS4WS, which can avoid generating full schema of Web service composition and allow on-the-fly verification on the state space; (ii) heuristics strategies to find the best potential composition, and (iii) a bitwise-based indexing mechanism for fast location of suitable Web services.


A scalable distributed architecture for client and server-side software agents

This paper describes recent developments of the Siebog agent middleware regarding performance. This middleware supports both server-side and client-side agents. Server side agents exist as EJB session beans on the JavaEE application server, while client-side agents exist as JavaScript Worker objects in the browser


Ebook Computer networks and internets (6/E): Part 1

(BQ) Part 1 book "Computer networks and internets" has contents: Introduction and overview, internet trends, internet applications and network programming, traditional internet applications, information sources and signals,... and other contents.


Mô tả công việc Quản trị viên website

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Quản trị viên website cần chịu trách nhiệm về các công việc như: tối ưu hệ thống Website, quản lý Website & Backup dữ liệu hệ thống Website, chỉnh sửa các module sẵn có trên website theo yêu cầu, nhân bản các Website của hệ thống dựa trên source code sẵn có... Ngoài ra, các bạn có thể tham khảo thêm về công việc của các vị trí khác trong khối phòng Công nghệ thông tin - IT qua Bộ Tài Liệu Hệ Thống Mô Tả Công Việc Dành Cho Nhân Viên IT trên trang TaiLieu.VN. Chúc các bạn thành công!


Mô tả công việc nhân viên định mức sản phẩm

Nhân viên định mức sản phẩm cần chịu trách nhiệm về các đầu việc như: tính hệ số sản phẩm chuẩn cho sản phẩm mẫu, tính định mức nguyên phụ liệu, sản phẩm mẫu mới và mẫu kinh doanh, cung cấp hệ số sản phẩm chuẩn cho nhân viên tính giá và kinh doanh, tính định mức sản phẩm mẫu mới... Ngoài ra, các bạn có thể tham khảo thêm về công việc của các vị trí khác trong khối phòng Công nghệ thông tin - IT qua Bộ Tài Liệu Hệ Thống Mô Tả Công Việc Dành Cho Nhân Viên IT trên trang TaiLieu.VN. Chúc các bạn thành công!


Tìm kiếm câu hỏi có ý nghĩa từ các trang web hỏi đáp cộng đồng

Nghiên cứu thực hiện trích rút những đặc trưng quan trọng từ mỗi luồng hỏi - đáp cũng như thông tin của người sử dụng và xây dựng mô hình phân loại để xác định được những câu hỏi có ý nghĩa. Các thực nghiệm được xây dựng trên tập dữ liệu trích rút từ trang web hỏi đáp cộng đồng Yahoo! Answer đã chỉ ra tính hiệu quả của phương pháp đề xuất.


Áp dụng kỹ thuật phân cụm dữ liệu mờ trong khai phá dữ liệu Web

Bài viết này trình bày tổng quan về khai phá dữ liệu Web, các hướng tiếp cận phân cụm tài liệu Web. Qua đó, bài viết giới thiệu mô hình tiếp cận phân cụm tài liệu Web bằng kỹ thuật phân cụm dữ liệu mờ và trình bày cụ thể quá trình tìm kiếm và phân cụm tài liệu Web bằng kỹ thuật phân cụm dữ liệu mờ với thuật toán Fuzzy C-Means.


Exploring web mining for auditing social networking: A clustering approach

In light of this the paper put forth the metrics for analysis followed by carving the database using a web based online tool. Results are indicative enough to showcase usefulness of the approach adopted herein for improving the websites.


An open source implementation of mapreduce using RF algorithm

The past situation's altogether centered on single errand parallelism, where as each assignments just has a solitary stage. Moderate execution of the MapReduce workload. Our essential test is to decrease the time finish of informational collections of the MapReduce assignments.


SVD based dimensionality reduction for efficient web page classification

This study implements word count function of Vector Space Model and singular value decomposition (SVD) technique of feature extraction based on dimensionality reduction. The proposed system presents an effective pre-processing and dimensionality reduction techniques which help the document classify by using naïve byes algorithm. The experimental results show that the proposed method enhances the performance of document classification.


A survey on web page de duplication using web mining techniques

The presence of duplicate web pages affects the speed of searching, the relevant documents to be retrieved and thereby the search engine performance. Web mining is the application of data mining techniques to discover patterns from the World Wide Web. Web mining can be divided into three different types.


Virtual teams in the digital age

This study is secondary research combining some practices to explore the issue. On the one hand, virtual teams enable to cooperate with members from different geography and time zones. On the other hand, organizations have to deal with many challenges when applying them.


Reliable and efficient storage solution using multiple cloud services

In this scenario, the service cost is higher than that of utilizing individual cloud but the efficiency and reliability is far more superior as compared to single cloud service. The experimentation was performed in local environment.


Analysis of a social data visualization web site: Youtube

This research discusses and analyzes the idea of data visualization, it’s characteristics, important elements and the concept behind it. The ideal data visualization model must be visually appealing, expandable and accessible, also develop the accurate information. Many challenges found that face analysts such as the complexity of data, lack of knowledge and over-relying from the users.


Design and implementation an online location based services using google maps for android mobile

This paper introduces an application for android mobile, which is implemented to provide the android mobile user to add, remove and review specific locations on the online map. The proposed applications also presents the basics navigation operations like showing directions with the optimal path between source and destination and calculating the distance and expected driving time.


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