Search results for "Markov model"
showing 10 items of 113 documents
Cartels Uncovered
2018
How many cartels are there? The answer is important in assessing the efficiency of competition policy. We present a Hidden Markov Model that answers the question, taking into account that often we do not know whether a cartel exists in an industry or not. Our model identifies key policy parameters from data generated under different competition policy regimes and may be used with time-series or panel data. We take the model to data from a period of legal cartels - Finnish manufacturing industries 1951 - 1990. Our estimates suggest that by the end of the period, almost all industries were cartelized.
Obstacle Detection in an Unstructured Industrial Robotic System: Comparison of Hidden Markov Model and Expert System
2012
Abstract This paper presents a comparison of two approaches for detecting unknown obstacles inside the workspace of an industrial robot using a laser rangefinder for 2-D measurements. The two approaches are based on Expert System (ES) and Hidden Markov Model (HMM). The results presented in the paper demonstrate that both approaches are able to correctly detect and classify unknown objects. The ES is characterised by low computational requirements and an easy setup when relatively few known objects are to be included inside the workspace. HMMs are characterised by a higher flexibility and the ability to handle a larger amount of known objects inside the workspace. Another significant benefit…
On the error sequences of M-ary FSK modulation schemes over Nakagami-m fading channels
2012
In this paper, we have studied some important statistical properties of error sequences of M-ary orthogonal frequency-shift keying (FSK) modulation schemes over Nakagami-m fading channels. We have derived the joint probability density function (PDF) of error sequences of arbitrary length. From the joint PDF, we have found an analytical solution for the autocorrelation function (ACF) of the error sequences. The correctness of the analytical expression for the ACF of error sequences has been confirmed by simulations, where the simulation results are obtained by using the sum-of-sinusoids principle. The derived joint PDF of error sequences is useful for the development of first-order and highe…
Do Women Prefer More Complex Music around Ovulation?
2012
The evolutionary origins of music are much debated. One theory holds that the ability to produce complex musical sounds might reflect qualities that are relevant in mate choice contexts and hence, that music is functionally analogous to the sexually-selected acoustic displays of some animals. If so, women may be expected to show heightened preferences for more complex music when they are most fertile. Here, we used computer-generated musical pieces and ovulation predictor kits to test this hypothesis. Our results indicate that women prefer more complex music in general; however, we found no evidence that their preference for more complex music increased around ovulation. Consequently, our f…
Real-Time Assembly Support System with Hidden Markov Model and Hybrid Extensions
2022
This paper presents a context-aware adaptive assembly assistance system meant to support factory workers by embedding predictive capabilities. The research is focused on the predictor which suggests the next assembly step. Hidden Markov models are analyzed for this purpose. Several prediction methods have been previously evaluated and the prediction by partial matching, which was the most efficient, is considered in this work as a component of a hybrid model together with an optimally configured hidden Markov model. The experimental results show that the hidden Markov model is a viable choice to predict the next assembly step, whereas the hybrid predictor is even better, outperforming in so…
CArDIS : A Swedish Historical Handwritten Character and Word Dataset
2022
This paper introduces a new publicly available image-based Swedish historical handwritten character and word dataset named Character Arkiv Digital Sweden (CArDIS) (https://cardisdataset.github.io/CARDIS/). The samples in CArDIS are collected from 64, 084 Swedish historical documents written by several anonymous priests between 1800 and 1900. The dataset contains 116, 000 Swedish alphabet images in RGB color space with 29 classes, whereas the word dataset contains 30, 000 image samples of ten popular Swedish names as well as 1, 000 region names in Sweden. To examine the performance of different machine learning classifiers on CArDIS dataset, three different experiments are conducted. In the …
Comparison of Attention Behaviour Across User Sets through Automatic Identification of Common Areas of Interest
2020
Eye tracking is used to analyze and compare user behaviour within numerous domains, but long duration eye tracking experiments across multiple users generate millions of eye gaze samples, making th ...
An Intra-Subject Approach Based on the Application of HMM to Predict Concentration in Educational Contexts from Nonintrusive Physiological Signals in…
2021
Previous research has proven the strong influence of emotions on student engagement and motivation. Therefore, emotion recognition is becoming very relevant in educational scenarios, but there is no standard method for predicting students’ affects. However, physiological signals have been widely used in educational contexts. Some physiological signals have shown a high accuracy in detecting emotions because they reflect spontaneous affect-related information, which is fresh and does not require additional control or interpretation. Most proposed works use measuring equipment for which applicability in real-world scenarios is limited because of its high cost and intrusiveness. To tackle this…
An Automatic Sleep Scoring Toolbox : Multi-modality of Polysomnography Signals’ Processing
2019
Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. To speed up the process of sleep scoring without compromising accuracy, this paper develops an automatic sleep scoring toolbox with the capability of multi-signal processing. It allows the user to choose signal types and the number of target classes. Then, an automatic process containing signal pre-processing, feature extraction, classifier training (or prediction) and result correction will be performed. Finally, the application interface displays predicted sleep structure, related sleep parameters and the sleep quality index for reference. To improve the identification accuracy of minority stages, a layer-w…
A case study on feature sensitivity for audio event classification using support vector machines
2016
Automatic recognition of multiple acoustic events is an interesting problem in machine listening that generalizes the classical speech/non-speech or speech/music classification problem. Typical audio streams contain a diversity of sound events that carry important and useful information on the acoustic environment and context. Classification is usually performed by means of hidden Markov models (HMMs) or support vector machines (SVMs) considering traditional sets of features based on Mel-frequency cepstral coefficients (MFCCs) and their temporal derivatives, as well as the energy from auditory-inspired filterbanks. However, while these features are routinely used by many systems, it is not …