Nowadays the public transport systems play a main role in the advanced societies. How to evaluate the quality of the public transport is a critic task of the transport regulatory agencies. One indicator used to measur...
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ISBN:
(纸本)9783319487991;9783319487984
Nowadays the public transport systems play a main role in the advanced societies. How to evaluate the quality of the public transport is a critic task of the transport regulatory agencies. One indicator used to measure this quality is the fulfilment of the scheduled operation by the transport operators, specially scheduled arrival times and frequencies at stops. In this paper, an automatic system to estimate arrival times in the context of road public transport is proposed. the system works autonomously, acquiring massive vehicle position readings, registering and processing them automatically in order to estimate arrival times. this autonomous behaviour is achieved using patternrecognition and statistical techniques. To illustrate the application of the system, the estimation of arrival times at a bus stop is presented.
World wide web (WWW) generates a huge number of unstructured data and information. the information is stored in weblog file. Weblogs information can be analyzed and visualized by various clustering algorithm. In this ...
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Printing massive, large-scale, and customized documents requires compatible printing machines which are expensive and insufficient sometimes. Users such as staff, instructors, and marketers sometimes need to print doc...
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ISBN:
(纸本)9781665422956
Printing massive, large-scale, and customized documents requires compatible printing machines which are expensive and insufficient sometimes. Users such as staff, instructors, and marketers sometimes need to print documents utilizing their existing printing resources from different brands. However, there is not a software that connects existing resources. In addition, some operations are complex which require optimizing and customizing printing tasks such as organizing, separating, assembling, composing, specifying quantities, choosing different colors, selecting paper tray amongst other preferences. Although these requirements might be feasible by specific printing machines, these machines are usually expensive and usually only available in press centers and institutes. Moreover, these machines might not be affordable in small and medium-sized enterprises (SMEs). Furthermore, employees face difficulty in using these machines at work. therefore, we propose an innovative solution that will help IT professionals increase productivity, efficiency, automation, and investments significantly. the approach of the solution was designed and developed as a useful software that helps to cope with manpower shortage and the lack of advanced resources.
Frequent Subgraph Mining (FSM) is an active research field and is considered as the essence of graph mining. FSM is extensively used in graph clustering, classification and building indices in the databases. In litera...
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ISBN:
(纸本)9781450363532
Frequent Subgraph Mining (FSM) is an active research field and is considered as the essence of graph mining. FSM is extensively used in graph clustering, classification and building indices in the databases. In literature, different FSM approaches are suggested such as AGM, FSG, SPIN, SUBDUE, gSpan, FFSM, CloseGraph, FSG, GREW. Most of these FSM techniques perform very well for small to medium size graph datasets, but the computational cost of FSM becomes very critical when the graph size is increased. In accession to this, the number of frequent subgraphs patterns grows exponentially withthe increasing size of graph datasets. Consequently, in this research work, a conceptual framework called A RAnked Frequent pattern-growth Framework (A-RAFF) is proposed. A-RAFF achieved efficiency by embedding the ranking of discovered frequent subgraphs during the mining process. the experiments on real and synthetic graph datasets demonstrated that the mining results of A-RAFF are very promising as compared to the existing FSM techniques.
In the new era, withthe increase of users' demand for Internet content, Software and resources have been released and accessed as services. the service mode "IT resources should be treated as water and elect...
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In the new era, withthe increase of users' demand for Internet content, Software and resources have been released and accessed as services. the service mode "IT resources should be treated as water and electricity" has put forward higher requirements for the data center construction, which determines that the traditional data center construction model and programs are no longer able to meet the needs of innovative applications of the new era. therefore, the integration and innovation of new and old technologies is required. the high reliability, scalability, security, flexibility, greenness and resource customization of cloud computing technology enable more and more campuses to use cloud computing platforms to build campus networks. this paper mainly elaborates the use of virtualization technology and cloud computing technology to build campus cloud platform. (C) 2021the Authors. Published by Elsevier B.V.
the paper addresses the problem of using Japanese candlestick methodology to analyze stock or forex market data by neural nets. Self organizing maps are presented as tools for providing maps of known candlestick forma...
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ISBN:
(纸本)9783642132070
the paper addresses the problem of using Japanese candlestick methodology to analyze stock or forex market data by neural nets. Self organizing maps are presented as tools for providing maps of known candlestick formations. they may be used to visualize these patterns, and as inputs for more complex trading decision systems. in that case their role is preprocessing, coding and pre-classification of price data. An example of a profitable system based on this method is presented. Simplicity and efficiency of training and network simulating algorithms is emphasized in the context of processing streams of market data.
Steady-state visually evoked potentials (SSVEPs) occur due to a repetitive visual stimulus, which results in periodic responses from the visual cortex at the stimulus frequency and its harmonics. Prior studies show th...
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ISBN:
(纸本)9781728143378
Steady-state visually evoked potentials (SSVEPs) occur due to a repetitive visual stimulus, which results in periodic responses from the visual cortex at the stimulus frequency and its harmonics. Prior studies show that the fundamental SSVEP frequency response can be used to produce a visual reconstruction of what is shown to the human eye. However, due to interference coming from the source and the sensing device, the resulting captured image contains salt-and-pepper noise and random value noise. this study investigates whether information present in the SSVEP harmonics is useful in denoising and enhancing the captured visual reconstruction. the proposed convolutional neural network architecture methods are compared against the SSVEP fundamental and naive additive reconstructions. the results show that combining harmonics and reconstructions from different signal processing methods into the neural network architecture enhances the resulting image.
Image steganography is a convenient candidate for information hiding withthe upsurge of using images on social media platforms and the internet. It is equally important that detecting these images through steganalysi...
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the two volumes set LNCS 10913-10914 of SCSM 2018 constitutes the proceedings of the 10thinternationalconference on Social computing and Social Media, SCSM 2018, held as part of the internationalconference on Huma...
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ISBN:
(数字)9783319914855
ISBN:
(纸本)9783319914848
the two volumes set LNCS 10913-10914 of SCSM 2018 constitutes the proceedings of the 10thinternationalconference on Social computing and Social Media, SCSM 2018, held as part of the internationalconference on Human-Computer Interaction, HCII 2018, held in Las Vegas, NV, USA, in July 2018. the total of 1171 papers and 160 posters presented at the 14 colocated HCII 2018 conferences.
Human emotional states can be detected by various ways such as analysingthe brain signals (EEG), speech, skin responses, facial expressions, body gestures etc. But facial expressions recognition is one of the popular ...
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