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We present a density-based Data Pruning method for Deep Reinforcement Learning (DRL) to improve learning stability and long-term memory in rare situations. The method controls density distribution in the experience pool by discarding high correlation data and preserving rare and unique data. We apply our method to Deep Q-networks (DQN) and Deep Deterministic Policy Gradients (DDPG) for testing in...
In this paper, we investigate the coexistence problem between Wi-Fi and a pre-standard form of LTE over unlicensed bands, namely, LTE-Unlicensed (LTE-U). We address two coexistence problems. First, the different access mechanisms for Wi-Fi and LTE-U can lead to an increase in the collision rate and higher latency for both systems. We propose a modified Wi-Fi operation mode, whereby Wi-Fi stations...
Identifying influential spreaders in online social networks (OSNs) has long been an important but difficult problem to be addressed. Distinguished from previous works that mainly focused on the stationary features of users' influence, we systematically study the variations of users' spreading capability given the fact that influential spreaders are more likely to be the targets of various cyber attacks...
The divergence similarity between two color images is presented based on the Jensen-Shannon divergence to measure the color-distribution similarity. Subjective assessment experiments were developed to obtain mean opinion scores (MOS) of test images. It was found that the divergence similarity and MOS values showed statistically significant correlations.
Structural similarity index (SSIM) considers the loss of structural information as a degradation of quality. Structure of original and distorted images are compared by using low order moments, which are mean, variance and correlation. In this paper, we extend the SSIM by incorporating shape parameters of distributions, which are the higher order moments based skewness and kurtosis. We show that skewness...
Sustainable development requires the transformation of societies into knowledge societies. ICTs are increasingly becoming repositories of knowledge and information, which has implications for the field of knowledge management. In this paper, we attempt to conduct a preliminary analysis to identify the factors that influence the sustainability of knowledge societies. A Knowledge Societies Index (KSI)...
The paper presents issues related to developing methods for fundamental analysis used to expand capabilities of multi-agent trading system, to better predict the financial market. The fundamental analysis indicators can be used as confirmation of decisions generated by other strategies of the system. The first part of the article discusses briefly the fundamental analysis issues in relation to the...
The exploration of a data set consists in grouping similar data. The classical statistical methods often fail when there is is no minimal assumption on the clusters. Our approach is based on the links between data, but the pairwise comparison between data and the importance of the links depend heavily on context where data lies. We propose to analyze a dataset through methods of the social choice...
An ECG signal contains important information required for diagnosis and analysis of heart diseases. So if there is noise induced in an ECG signal then scrutinizing of that signal for pathological, anatomical and physiological aspects goes worthless. Noises can be introduced by various sources, but a common source for high frequency noise is due to forces acting on the electrodes. In this paper noise...
In order to evaluate the energy production of a solar system, the tilted global radiation is needed. Generally, only the global horizontal radiation data are available. To calculate a tilted global radiation, it is necessary to estimate the diffuse or the direct component of the horizontal solar radiation. In this article, a statistical procedure has been employed to develop correlations between the...
The spatial clustering of highway traffic is of great interest to researchers and policy makers. In this paper, instead of using the microscopic traffic parameters in the traditional clustering methods, we introduce a new heterogeneity index clustering the sections of a highway based on differences in the content, a.k.a. “Heterogeneity”, in their flow, which can be used as a universal guideline for...
Existing Ml-reference image quality assessment models first compute a full image quality-predictive feature map followed by a spatial pooling scheme, thereby producing a single quality score. Here we study spatial sampling strategies that can be used to more efficiently compute reliable picture quality scores. We develop a random sampling scheme on single scale full-reference image quality assessment...
The problem of data deluge is prevailing everywhere. Analyzing voluminous and variety of data is a great challenge to the researchers. The MapReduce framework is adapted to many computational methodologies to overcome these issues. Clustering is one of the most commonly used data mining techniques in various pattern analysis applications. This paper is mainly focuses on quality based data clustering...
There are many similarities on fluctuations between clothing styles and finance so that many theorists approach to analyze the relationship of them, the best known of which is the Hemline Index Theory. When the economy is flourishing, hemlines increase, and when the economic situation is deteriorating, the hemlines drop, perhaps even to the floor. In contrast with measuring the illustrations from...
This paper evaluates the effect of energy trading networks on the volatility of coal, oil, natural gas, and electricity. This research conducts a longitudinal analysis using a time series of static coal trading networks to generate a dynamic trading network, and uses the component causality index as a leading indicator of systemic risk. This research finds out that the component causality index, based...
Trying to PM2.s as the independent variable to establish the “beam-diffuse radiation separated” model, factor analysis showed that, PM2.5 and diffuse ratio have positive correlation. Based on the clearness index Kt and sunshine hours n/N as variables, the polynomial model and the BP neural network algorithm model containing PM2.5 as the independent variable is proposed, the polynomial model is fitted...
This work analyses consumption obtained from high-power appliances in order to determine it characteristic curve. Due it high consumption, induction cooker, washer and dryer were studied. Meter FLUKE 1735 was used to acquire a samples per second. Acquired data as: voltage, current, voltage and current harmonics. Principal components analysis was used to reduce the size of each load data matrix and...
Natural disasters have destructive impacts on individuals and communities globally, particularly for most densely populated countries/regions. Governments must have intervention strategies in place to minimize the disruptive effects of a natural disaster, for instance: the vulnerability assessment. This type of assessment supplies government with a compulsory tool for pre-hazard baseline health surveillance,...
This presentation adds to the social cognitive career theory (SCCT)[1, 2] research in engineering[3–10] to understand factors associated with Latino/a engineering students' engineering self-efficacy and engineering outcome expectations. We highlight findings from one empirical study about the associations among perceived support in engineering, perceived barriers in engineering, engineering-related...
PM2.5 concentration can have significant impacts on solar irradiation and thus on photovoltaic (PV) power output. This paper presents a method to model impacts of PM2.5 concentration on PV power. A non-parametric kernel density estimation is used to fit the probability distribution of PM2.5 concentration. An incremental relation between the increase of PM2.5 concentration and the decrease of solar...
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