This paper presents the application program of fingerprint detection using wavelet transform for authentication. Fingerprints are obtained from the site of crime, old documents and excavated things. This paper propose...
详细信息
It is recognized that the semantic space of knowledge is a hierarchical concept network. This paper presents theories and algorithms of hierarchical concept classification by quantitative semantic relations via machin...
详细信息
ISBN:
(纸本)9781509038473
It is recognized that the semantic space of knowledge is a hierarchical concept network. This paper presents theories and algorithms of hierarchical concept classification by quantitative semantic relations via machine learning based on concept algebra. The equivalence between formal concepts are analyzed by an Algorithm of Concept Equivalence Analysis (ACEA), which quantitatively determines the semantic similarity of an arbitrary pair of formal concepts. This leads to the development of the Algorithm of Relational Semantic Classification (ARSC) for hierarchically classify any given concept in the semantic space of knowledge. Experiments applying Algorithms ACEA and ARSC on 20 formal concepts are successfully conducted, which encouragingly demonstrate the deep machine understanding of semantic relations and their quantitative weights beyond human perspectives on knowledge learning and natural language processing.
This paper investigates the performance of a three phase permanent magnet synchronous machine (PMSM) drive operating under a single fault, adopting a fault tolerant (FT) control, based on deadbeat - direct torque and ...
详细信息
ISBN:
(纸本)9781509007387
This paper investigates the performance of a three phase permanent magnet synchronous machine (PMSM) drive operating under a single fault, adopting a fault tolerant (FT) control, based on deadbeat - direct torque and flux control (DB-DTFC). DB-DTFC offers an independent regulation of the electromagnetic torque and the stator flux linkage by using a control law based on an inverse discrete time physical model. During fault conditions, the PMSM drive requires very limited hardware and software reconfigurations. The drive model equations result very similarly to those adopted for the healthy electric drive just by using a different matrix transformation set when the drive operates under a faulty condition. The proposed fault tolerant DB-DTFC ensures satisfactory faulty operations and drive stability, without increasing the computational efforts.
There has been an increasing need of technologies to manufacturing chemical and biological sensors for various applications ranging from environmental monitoring to human health monitoring. Currently, manufacturing of...
详细信息
There has been an increasing need of technologies to manufacturing chemical and biological sensors for various applications ranging from environmental monitoring to human health monitoring. Currently, manufacturing of most chemical and biological sensors relies on a variety of standard microfabrication techniques, such as physical vapor deposition and photolithography, and materials such as metals and semiconductors. Though functional, they are hampered by high cost materials, rigid substrates, and limited surface area. Paper based sensors offer an intriguing alternative that is low cost, mechanically flexible, has the inherent ability to filter and separate analytes, and offers a high surface area, permeable framework advantageous to liquid and vapor sensing. However, a major drawback is that standard microfabrication techniques cannot be used in paper sensor fabrication. To fabricate sensors on paper, low temperature additive techniques must be used, which will require new manufacturing processes and advanced functional materials. In this work, we focus on using aerosol jet printing as a high-resolution additive process for the deposition of ink materials to be used in paper-based sensors. This technique can use a wide variety of materials with different viscosities, including materials with high porosity and particles inherent to paper. One area of our efforts involves creating interdigitated microelectrodes on paper in a one-step process using commercially available silver nanoparticle and carbon black based conductive inks. Another area involves use of specialized filter papers as substrates, such as multi-layered fibrous membrane paper consisting of a poly(acrylonitrile) nanofibrous layer and a nonwoven poly(ethylene terephthalate) layer. The poly(acrylonitrile) nanofibrous layer are dense and smooth enough to allow for high resolution aerosol jet printing. With additively fabricated electrodes on the paper, molecularly-functionalized metal nanoparticles are d
The security of information in this global era is increasingly becoming a vital need in various aspects of life. An information will have a higher value when it comes to aspects of business decisions. This study prese...
The security of information in this global era is increasingly becoming a vital need in various aspects of life. An information will have a higher value when it comes to aspects of business decisions. This study presents a learning application to explain how to secure data using cryptographic techniques. This study aims to design a prototype learning application of cryptographic techniques using algorithm RC4 method. Based on the results of data analysis and after completing the design of RC4 algorithm cryptographic learning software, the authors found this software shows every step and stages of the processes (data input process (Plaintext or Ciphertext string), Key padding process (U), formation process in S-Box table, the Key-Flow formation process (K-keystream), encryption process and decryption process) contained in RC4 algorithm cryptography, so it can help understanding or learning work procedures of algorithms in the cryptographic method. Microsoft Visual Basic 2008 is an IDE (Integrated Development Environment) application that is used to create and develop software. In this application there were various features that facilitate programming such as compilation, debugging, project settings, designing and editing visual interfaces, and so on.
We present the first analysis of the Euclid Early Release Observations (ERO) program that targets fields around two lensing clusters, Abell 2390 and Abell 2764. We use imaging data from the Visible instrument (VIS) an...
详细信息
We present the first analysis of the Euclid Early Release Observations (ERO) program that targets fields around two lensing clusters, Abell 2390 and Abell 2764. We use imaging data from the Visible instrument (VIS) and the Near-Infrared Spectrometer and Photometer (NISP) to produce photometric catalogs for a total of ∼500 000 objects. The imaging data reach a typical depth of 5 σ in the range 25.1–25.4 AB in the NISP bands and 27.1–27.3 AB in the VIS band. Using the Lyman-break method in combination with photometric redshifts, we searched for high-redshift galaxies. We identified 30 Lyman-break galaxy (LBG) candidates at z > 6 and 139 extremely red sources (ERSs), most of which likely lie at lower redshift. The VIS imaging is deeper than the NISP imaging, which means that we can routinely identify high-redshift Lyman-break galaxies at about a magnitude of 3, which reduces contamination by brown dwarf stars and low-redshift galaxies. The difficulty of spatially resolving most of these sources in 0′′ . 3 pix−1 imaging means that it is difficult to distinguish between galaxies and quasars. Spectroscopic follow-up campaigns of these bright sources will help us to constrain the bright end of the ultraviolet galaxy luminosity function and the quasar luminosity function at z > 6, and it will constrain the physical nature of these objects. Additionally, we performed a combined strong- and weak-lensing analysis of A2390, and we show that Euclid will contribute to constraining the virial mass of galaxy clusters better. We also identify optical and near-infrared counterparts of known z > 0.6 clusters in these data. These counterparts exhibit strong-lensing features. This establishes that Euclid can characterize high-redshift clusters. Finally, we provide a glimpse of the ability of Euclid to map the intracluster light out to larger radii than current facilities, which enables us to understand the cluster assembly history better and to map the dark matter distribution. This ini
Human preference choice suffers curious contextual effects: the relative preference between two multi-attribute options (e.g. cars with differing safety and economy ratings) can dramatically shift, depending on the pr...
详细信息
Many graph mining and network analysis problems rely on the availability of the full network over a set of nodes. But inferring a full network is sometimes non-trivial if the raw data is in the form of many small patc...
详细信息
ISBN:
(纸本)9781509045518
Many graph mining and network analysis problems rely on the availability of the full network over a set of nodes. But inferring a full network is sometimes non-trivial if the raw data is in the form of many small patches or subgraphs, of the true network, and if there are ambiguities in the identities of nodes or edges in these patches. This may happen because of noise or because of the nature of data;for instance, in social networks, names are typically not unique. Graph assembly refers to the problem of reconstructing a graph from these many, possibly noisy, partial observations. Prior work suggests that graph assembly is essentially impossible in regimes of interest when the true graph is Erdos-Rényi. The purpose of the present paper is to show that a modest amount of clustering is sufficient to assemble even very large graphs. We introduce the G(n,p;q) random graph model, which is the random closure over all open triangles of a G(n,p) Erdos-Rényi, and show that this model exhibits higher clustering than an equivalent Erdos-Rényi . We focus on an extreme case of graph assembly: the patches are small (1-hop egonets) and are unlabeled. We show that in realistic regimes, graph assembly is fundamentally feasible, because we can identify, for every edge e, a subgraph induced by its neighbors that is unique and present in every patch containing e. Using this result, we build a practical algorithm that uses canonical labeling to reconstruct the original graph from noiseless patches. We also provide an achievability result for noisy patches, which are obtained by edge-sampling the original egonets.
Affective computing, particularly emotion and personality trait recognition, is of increasing interest in many research disciplines. The interplay of emotion and personality shows itself in the first impression left o...
详细信息
ISBN:
(纸本)9781509048489
Affective computing, particularly emotion and personality trait recognition, is of increasing interest in many research disciplines. The interplay of emotion and personality shows itself in the first impression left on other people. Moreover, the ambient information, e.g. the environment and objects surrounding the subject, also affect these impressions. In this work, we employ pre-trained Deep Convolutional Neural Networks to extract facial emotion and ambient information from images for predicting apparent personality. We also investigate Local Gabor Binary Patterns from Three Orthogonal Planes video descriptor and acoustic features extracted via the popularly used openSMILE tool. We subsequently propose classifying features using a Kernel Extreme Learning Machine and fusing their predictions. The proposed system is applied to the ChaLearn Challenge on First Impression Recognition, achieving the winning test set accuracy of 0.913, averaged over the “Big Five” personality traits.
暂无评论