This paper proposes a machine learning-based electric vehicle (EV) reserved charging service system, which takes into consideration the impacts from both the power system and transportation system. The proposed framework of charging network operation ...

The impact of Hyper-Parameter optimization on the performance of a machine learning algorithm has been proved both theoretically and empirically by many studies reported in the literature. It is a tedious and a time-consuming task if one goes for Manual ...

With the development of society, the number of vehicles increases rapidly. The vehicle plays an important role in people's life, however the problem of traffic safety caused by vehicles has also become increasingly prominent. In China, the high crash ...

Arabic topic detection (ATD) has become an attractive research field. It is used in many applications, such as Arabic documents classification, web search, social media, and security. ATD uses machine learning algorithms with ultimate aim to classify ...

Cross-site scripting (XSS) is a scripting attack targeting web applications by injecting malicious scripts into web pages. Blind XSS is a subset of stored XSS, where an attacker blindly deploys malicious payloads in web pages that are stored in a ...

The ultra-precision grinding process of brittle and hard fused silica is very complex. In order to monitor the grinding process accurately, it's necessary to de-noise the acoustic emission (AE) signals generated in this process and extract useful ...

The present research was aimed to find out EEG potentials related to movement in exercise-induced fatigue task using brain function network analysis, so that future researchers can find more accurate mutual informations between these potentials to ...

As new gadgets that interact with the user through voice become accessible, the importance of not only the content of the speech increases, but also the significance of the way the user has spoken. Even though many techniques have been developed to ...

In this paper, a comprehensive error calibration method is proposed for non-uniform dual circular arrays in the presence of gain-phase errors, position errors and mutual coupling errors. By rotating the platform, only one auxiliary calibration source is ...

With the development of artificial intelligence, pedestrian detection has become an important research topic in the field of intelligent video surveillance. Fish-eye camera is a useful tool for video monitoring. However, due to the edge distortion of ...

Autonomous vehicles are widely accepted as one of the most potential technologies in alleviating traffic problems. In most existing autonomous vehicles for object detection and distance measurement, compared with radar or LIDAR which obviously increases ...

The paper is dedicated to development of effective tools of multidimensional digital signal processing on irregular meshes. ANN-based method of irregular mesh generation for intra-frame video coding is developed. The method described is based on ...

Deaf or hard-of-hearing people mostly rely on lip-reading to understand speech. They demonstrate the ability of humans to understand speech from visual cues only. Automatic lip reading systems work in a similar fashion - by obtaining speech or text from ...

Hashing algorithm projects the vector of features onto the binary space that generate the binary codes to reduce calculating time. Thus Hashing Algorithm is widely used to improve retrieval efficiency in traditional image retrieval methods based on Deep ...

Target depth estimation can facilitate classification of surface ships or water-column targets thus reducing the false rates in active surveillance systems. Active sonar mainly determines the distance of the target by measuring the roundtrip time of the ...

Assessment of skeletal maturity plays an essential role in the clinical management of the adolescent disease. This task is very challenging when using machine learning method due to the limited data and large anatomical variations among different ...

Contrast-enhancement is very essential and ideal to produce a maximum contrast of many computer-vision and image-processing applications with minimum brightness error. Moreover, there is no mechanism to control the brightness error, contrast in ...

Video object tracking is an important task with a broad range of applications. In this paper, we propose a novel visual tracking algorithm based on deep activation feature maps in correlation filter framework. Deep activation feature maps are generated ...

We proposed a novel method that selects an optimal classifier model's parameter status through the uncertainty measure evaluation of the estimated class boundaries instead of an estimation of the classification error probability. A key feature of our ...

Regarding shape matching, we present a novel method of determining a correspondence between shapes that is applicable to existing local descriptors and somewhat enhances them. In our method, we determine the correspondence of a focusing point of a shape,...

Feature selection is an important preprocessing stage in signal processing and machine learning. Feature selection methods choose the most informative feature subset for classification. Mutual information and conditional mutual information are used ...

This paper proposes an early faults diagnosis method for bearings based on Variational Mode Decomposition (VMD) and Entropy Theory to monitor the working state of the key components of the high-speed train axle box. Firstly, the box vibration signal is ...

Online transfer learning aims to attack an online learning task on a target domain by transferring knowledge from some source domains, which has received more attentions. And most online transfer learning methods adapt the classifier according to its ...

The ability of software systems adapting to human's input is a key element in the symbiosis of human-system co-adaptation, where human and software-based systems work together in a close partnership to achieve synergetic goals. This seamless integration ...

Based on instrumental sensors, a cascade calibration method of the near-field source is proposed. The method can not only uses multiple independent near-field signals operating at different times and different locations calibrate the gain and phase ...

Aiming at the problem that the wireless signal in coal mine is vulnerable to interference and the positioning accuracy of the node is low when moving, a positioning algorithm based on location fingerprint downhole mobile node is proposed. Firstly, based ...

In this paper, we present an unsupervised learning based approach to conduct depth estimation for monocular camera video images. Our system is formed by two convolutional neural networks (CNNs). A Depth-net is applied to estimate the depth information ...

This paper is based on CRNN model to recognize the text in the images of football matches scene, and two improvements are proposed. Considering the edge feature of text is strong, this paper adds MFM layers into CRNN model aiming to enhance the ...