Increase in traffic over internet by large number of mobile devices results into high energy consumption on network devices. In this paper, we address the necessity to reduce the energy consumption in a campus network...
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ISBN:
(纸本)9781509009800
Increase in traffic over internet by large number of mobile devices results into high energy consumption on network devices. In this paper, we address the necessity to reduce the energy consumption in a campus network that includes both wired and wireless network devices. Specifically, we propose dynamic link rate adaptation mechanism on Software Defined Network (SDN) switches and control power consumption on Access Points (APs) by using users association to an AP. Moreover, our online flow routing approach dynamically routes user traffic in order to decrease the overall energy consumption of whole network while taking in consideration Quality of Service (QoS), acceptance ratio on forwarding table and link BandWidth (BW) constraints. Our simulation result shows that our approach results in 3.69% less power consumption, and furthermore, there is no congested links nor overflow in flow table as compared to Dijkstra Ant colony Power (DAPower) that has 2 congested links for 150 users in a network, each generating 34 flows.
This paper presents the application program of fingerprint detection using wavelet transform for authentication. Fingerprints are obtained from the site of crime, old documents and excavated things. This paper propose...
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ISBN:
(纸本)9781509041060
This paper presents the application program of fingerprint detection using wavelet transform for authentication. Fingerprints are obtained from the site of crime, old documents and excavated things. This paper proposes a fingerprint recognition technique based on wavelet-based texture pattern recognition method. By collecting incomplete fingerprints of 2 people with 6 images each. The original seven of uncompleted fingerprint images were undetected and only one was detected. After enhancing image quality using wavelet transform method, it was found that those of seven images were completed. The comparison method was a matching technique. This work focuses on the ability of the program and knowledge of image processing by studying algorithms of image processing. In design algorithm process, different technique enhancements were employed as well as the study of different of filters and algorithms based on existing research results from literature.
Choosing the ideal spot to set up an Access Point (AP) in a given plant is no simple task. This paper proposes a mathematical model and computational solution to the following problem: given the plant of an indoor env...
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Choosing the ideal spot to set up an Access Point (AP) in a given plant is no simple task. This paper proposes a mathematical model and computational solution to the following problem: given the plant of an indoor environment, a number of reception points and properly characterized obstacles, locate where the access point should be installed, so as to minimize the propagation losses within the environment and ensure a minimum signal level in all receivers. The model proposed differs from others in the literature by treating each obstacle individually and taking into account the material from which it is made. The proposed design minimizes the sum of the attenuations of the signal generated by the AP as the signal traverses the fewest possible obstacles whose attenuation is large (e.g., concrete walls and metal cabinets). To validate the proposed model simulations were performed in an indoor environment with a certain distribution of obstacles of different kinds. The experiments show that the location of the access point varies significantly in the environment according to the materials composing the obstacles. In the most critical case, with obstacles made of concrete, the optimization algorithm could find no location for the AP so that all receptors received a minimum signal level to establish a connection.
Fall detection systems have been proposed to prevent additional injuries following fall accidents. This paper introduces an easily learnable fall detection system based on the data of an individual patient in a hospit...
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Fall detection systems have been proposed to prevent additional injuries following fall accidents. This paper introduces an easily learnable fall detection system based on the data of an individual patient in a hospital room. The improvement of low performance using a single accelerometer at wrists and the inconvenience of sensor attached to a waist in the conventional approach was concentrated on by integrating heart rate signals to the conventional acceleration approach and changing the sensor location from a waist to wrists. As for the optimal heart rate feature selection, we proposed a four-feature vector combination (root mean square of successive differences, standard deviation of successive differences, normal to normal 50, normal to normal 20) with correlation and mutual information analysis in addition to mean absolute deviation selected as an accelerometer feature. To easily acquire and train the patients' fall data, our system was based on unsupervised learning approaches using Gaussian mixture models for optimal classifiers with the optimal cluster number decided by cluster validation index of square error sum. A 10-fold cross validation was applied for a final performance evaluation where each threshold for separating fall state from non-fall state was automatically decided in several comparison groups, which were created on the basis of fusion timing and used sensors. As a result, despite sensors attached to the wrist, the wearable inconvenience of the conventional is overcome using the feature-level fused approach between heart rates and accelerations with the accuracy up to 98.39 %, which is closest to 99.34 % of the case using a single accelerometer located at the waist.
Optogenetics has emerged as an exciting tool for manipulating neural activity, which in turn, can modulate behavior in live organisms. However, detecting the response to the optical stimulation requires electrophysiol...
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Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factor...
Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a
Background: Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the ...
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We compare three approaches to learning numerical parameters of discrete Bayesian networks from continuous data streams: (1) the EM algorithm applied to all data, (2) the EM algorithm applied to data increments, and (...
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In practice, Mobile Ad Hoc Networks (MANETs) must operate efficiently under a wide range of node mobility and link quality regimes. Stateful protocols such as OLSR are suitable for networks connected by stable paths, ...
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In practice, Mobile Ad Hoc Networks (MANETs) must operate efficiently under a wide range of node mobility and link quality regimes. Stateful protocols such as OLSR are suitable for networks connected by stable paths, but are outperformed by stateless flooding in sparse and rapidly changing networks. Neither routing nor flooding alone perform well in heterogeneous networks comprised of both stable and highly dynamic components. Rather than design a new protocol for routing in heterogeneous mobile networks from scratch, we use an approach that leverages prior work by operating nodes individually as routers or flooders and switching mode in response to changing network conditions. We present two greedy algorithms, k-flood and adaptive-flood, that dynamically classify nodes as routers or flooders. Our simulations show that nodes can effectively adapt their individual operation as routers/flooders, achieving performance equivalent to, and in some cases significantly better than, that of network-wide routing or flooding alone.
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