In this paper, we present an extension to MS Office that enables users to search and retrieve document content units (e.g., paragraphs, images, tables, slides, etc.) from documents, which are stored on user's indi...
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The automatic programming system has been considered by means of which it becomes easier to carry out traditional programming stages. There is discussed both recursive forms: parallel, interrecursion and recursion of ...
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The automatic programming system has been considered by means of which it becomes easier to carry out traditional programming stages. There is discussed both recursive forms: parallel, interrecursion and recursion of high level that exist for functional programming languages and induction methods for the purpose of their verification. The way how to present imperative languages easy and double cycles by means of recursion forms is shown, the possibility of verification has been studied for each recursion form.
Recent work into knowledge-mining algorithms has found that second order models can be used to approximate the inputs to systems by first calculating their time trajectories, and then obtaining the causal parameters o...
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This paper presents a decision procedure for a certain class of sentences of first order logic involving integral polynomials and the exponential function in which the variables range over the real numbers. The inputs...
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ISBN:
(纸本)9781595939043
This paper presents a decision procedure for a certain class of sentences of first order logic involving integral polynomials and the exponential function in which the variables range over the real numbers. The inputs to the decision procedure are prenex sentences in which only the outermost quantified variable can occur in the exponential function. The decision procedure has been implemented in the computer logic system REDLOG. Closely related work is reported in [2, 7, 16, 20, 24].
Up to now many different definitions of agents were presented and several different approaches describing agency can be distinguished. Reactive agents are one of a kind;basically, they rely on reactivity and they have...
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ISBN:
(纸本)9780980326727
Up to now many different definitions of agents were presented and several different approaches describing agency can be distinguished. Reactive agents are one of a kind;basically, they rely on reactivity and they have to react to some changes which have occurred and have been registered. Active database management system is a conventional database system capable of reacting to some events of interest as well. Up to now it has been recognized that both types of systems rely on reactivity, but only a few general papers were written on the subject. That is why we will compare these two fields in a detail in order to determine whether active databases are suitable to implement reactive agents (or not).
Recent work into knowledge-mining algorithms has found that second order models can be used to approximate the inputs to systems by first calculating their time trajectories, and then obtaining the causal parameters o...
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Recent work into knowledge-mining algorithms has found that second order models can be used to approximate the inputs to systems by first calculating their time trajectories, and then obtaining the causal parameters of these trajectories. In this paper a new method of text analysis is proposed, and the application of knowledge-mining algorithms to text analysis is investigated. Mathcad is used to model relevant knowledge mining algorithms and test their performance with signals derived from ASCII codes of text excerpts. For the first time, time-varying signals relating to a series of input values have been analysed with knowledge mining algorithms. The Mathcad program which does this has been embedded into a user interface in MS Access to allow ease of text selection by users and automatic calculation of ASCII values for analysis.
In this paper, we introduce the approach of adaptive neuro-fuzzy sliding mode control to the vector control of induction motor, in order to overcome the chattering problem. After determining the decoupled model of the...
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Embodied Conversational Agents (EGAs) are life-like computer generated characters that interact with human users in face-to-face multi-modal conversations. ECA systems are generally complex and difficult for individua...
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Wireless communications and modern machine learning techniques have jointly been applied in the recent development of vehicle health monitoring (VHM) systems. The performance of rail vehicles running on railway tracks...
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ISBN:
(纸本)9781601320728
Wireless communications and modern machine learning techniques have jointly been applied in the recent development of vehicle health monitoring (VHM) systems. The performance of rail vehicles running on railway tracks is governed by the dynamic behaviors of railway bogies especially in the cases of lateral instability and track irregularities. In this study we have proposed a system to monitor the vertical displacements of railway wagons attached to a moving locomotive. The system uses a classical linear regression machine learning technique with real wagon body acceleration data to predict vertical displacements of vehicle body motion. The system is then able to generate precautionary signals and system status which can be used by the locomotive driver for necessary actions. This VHM system provides forward-looking decisions on track maintenance that can reduce maintenance costs and inspection requirements of railway systems.
Advances in modern machine learning techniques has encouraged interest in the development of vehicle health monitoring (VHM) systems. These techniques are useful for the reduction of maintenance and inspection require...
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ISBN:
(纸本)1601320620
Advances in modern machine learning techniques has encouraged interest in the development of vehicle health monitoring (VHM) systems. These techniques are useful for the reduction of maintenance and inspection requirements of railway systems. The performance of rail vehicles running on a track is limited by the lateral instability and track irregularities of a railway wagon. In this study, a forecasting model has developed to investigate vertical acceleration behavior of railway wagons attached to a moving locomotive using different regression algorithms. Front and rear vertical acceleration conditions have predicted using ten popular learning algorithms. Different types of models can be built using a uniform platform to evaluate their performances. This study was conducted using ten different regression algorithms with five different datasets. Finally best suitable algorithm to predict vertical acceleration of railway wagons have suggested based on performance metrics of the algorithms that includes: correlation coefficient, root mean square (RMS) error and computational complexity.
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