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This paper presents a decision support system for classification of hotel guests in the terms of additional spending. The research is conducted on three stars medium-sized hotel. Guests are classified on arrival, during check-in, in one of the two groups: low spending group or high spending group. A low spending group consists of visitors that are anticipated to spend less than 25 Euros per day for...
This paper introduces five similarity measures, very well known in literature, but not because of using them to compare rules between themselves and choose the most similar one. Rules in knowledge bases are a very specific type of data representation and it is necessary to compare them carefully. The goal of the paper is to analyze the influence of using different similarity measures on the number...
A sense tagged corpus is important resources to word sense disambiguation and word sense identification. However, the sense tagging process should be conducted manually that it is a time consuming and expensive process. Therefore, the semi-automatic construction of sense tagged corpora is studied to reduce the cost of word sense tagging. This construction should contain two important phases that are...
A sufficient data length can play an important role in a proper estimation drought index, leading to a better appraisal for drought risk reduction. The South Central Region of Vietnam is one of drought prone areas but it has poor data conditions. A collection of meteorological data in the study area during a period of 38 years 1977–2014 found out a fact that there existed missing values in 10 out...
Visual tracking has become a hot research topic in the field of computer vision at present. The tracking process can be converted into a dynamic optimization problem. In this article, an image fitness metric which named the Structural Similarity Index (SSIM) is used to estimate the object location in the experiments. In addition, DE (differential evolution), a population based stochastic meta-heuristic...
The prediction of stock price movements is considered as a challenging task for financial time series analysis. The difficulty of predicting the trends lies in the dynamic temporality and noise in the stock data. The Echo State Network (ESN) is a popular time series prediction model that considers the temporality of the stock time series, but ESN often falls into the dilemma of over-fitting due to...
In the research and development of wind turbine generator systems, it is necessary to predict the responses of the system for various wind conditions. Hence, a laboratory-size wind turbine simulator that can simulate the dynamic performances of actual wind turbine generator systems is very useful. However, there are few studies on such simulators. In this paper, a simulation method for actual MW class...
We propose and demonstrate a coupled optoelectronic oscillator (COEO) based on enhanced spatial hole burning (SHB) effect in an unpumped erbium-doped fiber (EDF). A novel structure is designed to form strong standing waves in the unpumped EDF, which enables large SHB effect to improve the side-mode suppression and ensure stable operation. A proof-of-concept experiment is carried out. A 10-GHz stable...
Using received signal strength (RSS) fingerprints from nearby Wi-Fi access points is a common approach to indoor localization in modern applications, in part due to its relatively low hardware cost and computational complexity. We present a sequential detection approach to RSS-based positioning that employs a Bayesian metric to identify the most likely path, given a time series of RSS measurements,...
This paper addresses the problem of phase noise mitigation in communications links utilizing DFT-S-OFDM waveforms. The paper discusses use of two different pilot configurations to do the compensation of the common phase error part of the phase noise. The pilot configurations are inserting pilots as logical symbols before the DFT spreading and inserting frequency domain pilots as subcarriers as in...
In this paper, we investigate the recovery of a sparse weight vector (parameters vector) from a set of noisy linear combinations. However, only partial information about the matrix representing the linear combinations is available. Assuming a low-rank structure for the matrix, one natural solution would be to first apply a matrix completion to the data, and then to solve the resulting compressed sensing...
To date, automatic target recognition (ATR) techniques in synthetic aperture radar (SAR) imagery have largely focused on features that use only the magnitude part of SAR's complex valued magnitude-plus-phase history. While such techniques are often very successful, they inherently ignore the significant amount of discriminatory information available in the phase. This paper describes a method for...
Operation of any type of industrial or commercial facility depends on the use of electrical energy. To that end, facilities are connected to the power grid in order to have access to continuous electrical power supply. Therefore, analysis of power consumption at the grid's nodal level may provide information about the consumers connected to the node. In this paper, a new intelligent system for detecting...
To leverage multiplexing gain, a hybrid beamforming architecture transmitting multiple data streams is widely adopted for Millimeter wave (mmWave) channel. However, for ultra-low latency mmWave communication, the hybrid design must require the development of instantaneous channel estimation. In this paper, we reveal a novel idea of progressive channel estimation through iteratively refining multiple...
We consider the channel estimation for millimeter-wave (mmWave) cellular systems in this paper. Because of the limitation of the hybrid RF/digital beamforming and the adoption of large-scale antennas, the acquisition of channel state information (CSI) is challenging. By exploiting the joint spatially sparse nature of practical mmWave channels, we develop a novel channel estimation algorithm based...
This paper introduces a new method for the quantification and analysis of functional connectivity from electroencephalogram (EEG) by implementing cross-correlation method. The recorded clinical EEG signals are segmented and categorized into three types of epileptiform discharges (ED), interictal spike, spike and slow wave complex, and repetitive spike and slow wave complexes. The extracted EEG functional...
The topic of this paper is low-complexity yet high-precision phase-noise mitigation in a realistic cm-wave radio link. The proposed algorithm for phase-noise induced intercarrier interference mitigation works in time domain. We propose a filtering solution that is computationally very simple to implement on silicon. Noise from initial phase-noise estimate is removed with cumulative sum filtering instead...
Investigation of Electroencephalogram (EEG) has been made during the spontaneous breathing and paced breathing control (9 breaths/minute) conditions in eight young healthy college students (Male=4, Female=4). Their selected 5-minute EEG segments were transformed into 3 frequency bands (Delta Wave: 0.5–4Hz, Theta Wave: 4–8Hz and Alpha Wave: 8–13Hz). The power in each band were compared between two...
This paper presents a DC-DC converter to be embedded in the pixel front-end of detectors in Large Hadron Collider (LHC) experiment at CERN. The DC-DC converter has to operate in a hostile environment due to the radiation. Under radiation, the value of the resistances, Ron, of the MOS switches changes. In addition, the load current, Iout, can change, ranging around the nominal value of 400mA from 200mA...
Providing financial e-services in the all areas involves taking decisions processes. Existing systems, also multi-agent systems, usually include only one of the earlier mentioned areas, and they are closed systems, available only to a small group of users. In addition, agents' knowledge in these systems is characterized by a certain degree of heterogeneity. Since in the decisive process one final...
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