The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A smart wearable electrocardiographic (ECG) processor is presented for secure ECG-based biometric authentication and cardiac monitoring, including arrhythmia and anomaly detection. Data-driven Lasso regression and low-precision techniques are developed to compress the neural networks by 24.4X. The prototype chip fabricated in 65 nm LP CMOS consumes 1.06 μW at 0.55 V for real-time ECG authentication...
An effective and fast face recognition method that is capable of dealing with faces under variable pose and illumination conditions has been proposed in this paper. First, the face is detected and the eyes are located automatically by the two cameras, eyes located in the two cameras are matched and the pose angle of the face is calculated. Then, the frontal face is generated according to the pose...
Emotion recognition from physiological signals has aroused great concern recently as its objective. In this paper, the recognition system from physiological signals is introduced, and important topics on emotion models, databases for analysis, feature extraction and selection methods, different classification techniques and performance issues are studied. Finally, the research challenges and trend...
The past few years have witnessed an exponential growth in the volume of data on digital forensics leading to big data issues. Digital forensics data is complex and heterogeneous in that it can be structured, unstructured and semi-structured. Traditional relational database management systems (RDBMS) typically expose a query interface based on SQL (Structured Query Language). However, the RDBMS are...
This paper proposes a novel anomaly detection method of network worms. The algorithm detects unknown worms by multidimensional worm abnormal detection technology, extracts its feature string via analyzing worm data with leap-style and creates new rules to detect the corresponding worm in case that the unknown worm attacks again. The paper has realized the automatic detection of unknown worms. Experiment...
The CSNS (China Spallation Neutron Source) RCS (rapid cycling proton synchrotron) RF (Radio Frequency) remote control system is a DCS (distributed control system) system based on the EPICS (Experimental Physics and Industrial Control System). This system is used to remotely control and monitor the accelerating cavities and their accessory equipments of the rapid cycling proton synchrotron (RCS) for...
PLM (product lifecycle management) is the management of the enterprise's products all the way across their lifecycles in the most effective way. However, at present, the PLM system in the market is not very appropriate to the small and medium-size enterprises. This paper presents a workflow engine-driven universal PLM system framework, which is constructed by four layers: client layer, application...
In this paper, we propose a novel approach SDR-CS (Sparse Dimensionality Reduction based on CS) based on compressed sensing to reduce dimensionality. With certain constraint of objective function, our semi-supervised learning method utilizes instance to construct the optimally sparse dictionary in the training dataset, employs K-SVD and OMP algorithms to improve the convergence rate of learning, and...
Celebrated fingerprinting techniques localize users by statistically learning the signal to location relations. However, collecting a lot of labelled data to train an accurate localization model is expensive and labour-intensive. In this paper, an economic and easy-to-deploy indoor localization model suitable for ubiquitous smartphone platforms is established. The method processes embedded inertial...
Storage is an important research direction of the data management of the Internet of Things. Massive and heterogeneous data of the Internet of Things brings the storage huge challenges. Based on the analysis of the IoT data characteristics, this paper proposed a storage management solution called IOTMDB based on NoSQL as current storage solutions are not well support storing massive and heterogeneous...
This work addresses the problem of constructing an effective training set at minimal labeling cost by selecting some images to build a subset from the whole database. This problem occurs in situations that the number of categories is large or the cost of obtaining labeled images is extremely high, because the images selected by uniform sampling do not reflect the desired training distribution and...
In recent years, disastrous earthquake assault the human frequently. The evaluation and estimate of the loss and damage in seismic disaster is an important factor for earthquake emergence and post-earthquake reconstruction decision-making. This paper synthetically designs a set of disaster real-time evaluation system based on the seismic networking of things. This paper firstly collects real-time...
In this paper, we focus on the issue of building up a training set for the task of image classification at minimal labeling costs. It is a topic that has attracted the considerable attention in the recent years. We propose a novel active learning algorithm with optimal distribution. In order to solve the problems of the noisy distribution and the sampling bias in the actively sampling process, the...
This paper focuses on the design and development of Municipal Facilities Management System (MFMS). Street images and videos were collected by Wuhan LD2000-R Mobile Mapping System, and real-time videos on site under emergency conditions were captured by Wireless Transmission System. In MFMS, any street can be queried and located, visual information of facilities on the streets can be viewed, as well...
Emotion recognition from speech plays an important role in developing affective and intelligent systems. This study investigates sentence-level emotion recognition. We propose to use a two-step approach to leverage information from subsentence segments for sentence level decision. First we use a segment level emotion classifier to generate predictions for segments within a sentence. A second component...
Analysis about EST data usually starts with EST clustering, the process of grouping fragments according their original consensus long sequence. The similarity between ESTs always means that part of the sequences match with each other in some way. Accurate clustering is quadratic in time in average EST length and numbers, and the number of ESTs in public EST database is increasing exponentially. With...
With the rapid development of network technology and the increasing expansion of its size, there are more and more services need to be provided by network, so modern users have an increasing demand for making servers that operate and provide these services highly available. Obviously, stand-alone system is unappeasable, we must use the cluster as the server that operate those services especially the...
In view of the problems of features in face recognition, a new face image feature extraction and recognition method----Fractal Locality Preserving Projections (FLPP) is proposed in this paper. FLPP first gets the high order statistic information by calculating the fractal codes of face images. Based on manifold learning theories, LPP takes into account the inter-class information, and extract the...
Particle swarm optimization (PSO) is an algorithm modelled on swarm intelligence that finds a solution to an optimization problem in a search space. In this paper, a PSO-based artificial neural network algorithm is proposed to automatically grading the learning results. Basically, the PSO algorithm is utilized to adjust the connection weights of the selected ANN topology. Taken mandarin learning as...
Wireless sensor network (WSN) has been considered to be the next generation paradigm of structural health monitoring (SHM) systems due to its low cost, high scalability and flexibility. However, some inherent limitations of WSN such as low-bandwidth wireless communication, limited resources on wireless sensor nodes, must be addressed to meet the generally high requirements of SHM. Distributed in-network...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.