CCRIS

A reference signal is the target for a plant to track. When the reference signal is incomplete over a prediction horizon for model predictive control, a constant prediction of a reference is generally used to take place of the unknown reference signal. ...

This paper presents a novel trajectory tracking control method for a manipulator of 6-DOF (6 Degrees of Freedom) based on robust nonlinear predictive control. The design of such control requires the establishment of dynamic nonlinear model of the ...

The paradigm of cloud robotics points out a direction for the future development of robots. By deploying robotic applications in the cloud, the workload and cost of local robots are greatly reduced. The rise of microservices and cloud-native technology ...

Aiming at the problem that traditional target tracking algorithms cannot detect and track specific targets in the real environment (such as airports) due to the given initial frame target position, this article proposes a target tracking algorithm that ...

In the process of engraving three-dimensional (3D) complex shape using manipulators, there are many inflection points and many start-stop operation, which cause shock easily. To resolve these problems, an adaptive NURBS curve interpolation algorithm ...

The research significance of this article is to realize the scene storytelling of animation based on the visualization of UnrealTM game engine. In the scene preview, the characters’ moving speed and path are simulated and controlled to realize the real-...

Change detection is an important task in remote sensing (RS) image analysis. With the development of deep learning and the increase of RS data, there are more and more change detection methods based on supervised learning. In this paper, we improve the ...

Background subtraction algorithm is essential for video processing. such as target tracing, gesture recognition and gait recognition. ViBe has been widely used because of easy implementation and high efficiency. However, the algorithm would produce a ...

This paper proposes a programming class for young children. In order to reduce the burden on teachers and attract students' interest, a robot teaching assistant is used to explain programming knowledge, verify and run programs. Different from writing ...

To solve the problem that the accuracy of transformer fault diagnosis is seriously affected by support vector machine parameters, a transformer fault diagnosis method based on the sparrow search algorithm is proposed. First, through very sparse random ...

A unitary root signal classification (Root-MUSIC) combined with subspace modification for uniform circular microphone arrays is proposed. Firstly, the subspace is modified by eliminating the two undesirable terms in the covariance matrix, which cause ...

The working status of wind turbine can be obtained and fault warning can be given accurately, if the data information mining is efficient. However the existing SCADA data monitoring methods do not take the history and trend into account. A data ...

This research is dedicated to the problem of transforming ”linear” educational systems of higher education institutions into a new paradigm of person-centered, blended and individual education. This paper investigates role, application, and challenges ...

This article proposes a recommendation system for choosing an academic supervisor, based on an assessment of the similarity of student interests and the scientific achievements of the possible mentor from the university faculty. We used a new approach ...

In this work, we address the algorithm selection problem for classification via meta-learning and generative adversarial networks. We focus on the dataset representation question. The matrix representation of classification dataset is not sensitive to ...

This study aimed to apply supervised machine learning techniques to one domain of psychological research: vocational interests. Socio-demographic factors can be considered strong predictors of vocational interests, which might have far-reaching ...

Recent developments in the field of robot grasping have shown great improvements in the grasp success rates when dealing with unknown objects. In this work we improve on one of the most promising approaches, the Grasp Quality Convolutional Neural ...

In this paper we propose to use generative adversarial network (GAN) for respiratory sound data augmentation. We present a GAN based approach that requires moderate amount of time and computing resources and capable to greatly increase performance of ...

We investigate the usage of hybrid convolutional and long- short-term memory neural networks for joint slot filling and intent detection in spoken language understanding. We propose a novel model that combines between convolutional neural networks, for ...

Because data products are characterized by wide variety, large quantity, fast updating and difficult to determine the value, data transaction relies on the credit service provided by the trans-action platform as the core of the credit check not only is ...

With the development of cloud computing, artificial intelligence, big data and other technologies, network systems are facing more and more security risks and threats. The traditional security architecture based on border protection cannot meet the ...

Power Internet of Things is the application of IoT in smart power grid. Once attacked, it will cause huge losses. Therefore, it is necessary to conduct a security assessment to take defensive measures. However, the traditional vulnerability assessment ...

In this paper, we describe the emergency distance teaching at FPT University in Vietnam to deal with emergency social isolation orders due to the outbreak of the COVID-19 virus. There are many theories as well as guidelines for implementing distance ...

Stock price prediction is a challenging financial time-series forecasting problem. In recent years, on account of the rapid progression of deep learning, researchers have developed highly accurate, state-of-the-art time-series models. Long short-term ...

Elastic-search is a distributed search engine which is used to process large amount of data widely. It has a vast number of configuration parameters which are extremely difficult to manually tune to achieve optimal throughput and latency. This paper ...

To accurately express the fuzzy relation between word features and texts, and fuzzy relation between word features and categories respectively. A text classification method is proposed based on Fuzzy Relation and Feature Distribution Variance (FRFDV). ...

Error correction for automatic speech recognition text is an indispensable part of artificial intelligence. At present, speech to text (STT) has widely requirements for the processing of pragmatic information. The text correct rate in STT is the ...

In addition to bringing us knowledge, books also bring us emotional experiences. How do the emotional fluctuations brought by books affect readers’ evaluation of them? What is the difference in emotional fluctuations between books of different ...

This survey talks about Automatic Text Summarization. Information explosion, the problem caused by the rapid growth of the internet, increased more and more necessity of powerful summarizers. This article briefly reviews different methods and ...