Although Smart Grid (SG) transformation brings many advantages to electric utilities, the longstanding challenge for all them is to supply electricity at the lowest cost. In addition, currently, the electric utilities...
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Although Smart Grid (SG) transformation brings many advantages to electric utilities, the longstanding challenge for all them is to supply electricity at the lowest cost. In addition, currently, the electric utilities must comply with new expectations for their operations, and address new challenges such as energy efficiency regulations and guidelines, possibility of economic recessions, volatility of fuel prices, new user profiles and demands of regulators. In order to meet all these emerging economic and regulatory realities, the electric utilities operating SGs must be able to determine and meet load, implement new technologies that can effect energy sales and interact with their customers for their purchases of electricity. In this respect, load forecasting which has traditionally been done mostly at city or country level can address such issues vital to the electric utilities. In this paper, an artificial neural network based energy consumption forecasting system is proposed and the efficiency of the proposed system is shown with the results of a set of simulation studies. The proposed system can provide valuable inputs to smart grid applications.
Emphysema is a chronic lung disease that causes breathlessness. HRCT is the reliable way of visual demonstration of emphysema in patients. The fact that dangerous and widespread nature of the disease require immediate...
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ISBN:
(纸本)9781467379120
Emphysema is a chronic lung disease that causes breathlessness. HRCT is the reliable way of visual demonstration of emphysema in patients. The fact that dangerous and widespread nature of the disease require immediate attention of a doctor with a good degree of specialized anatomical knowledge. This necessitates the development of computer-based automatic identification system. This study aims to investigate the deep learning solution for discriminating emphysema subtypes by using raw pixels of input HRCT images of lung. Convolutional Neural Network (CNN) is used as the deep learning method for experiments carried out in the Caffe deep learning framework. As a result, promising percentage of accuracy is obtained besides low processing time.
Due to the networking expertise, services and technical support of telecommunications operators, Smart Grid (SG) operators prefer telecommunications operators for their communications needs instead of creating private...
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Due to the networking expertise, services and technical support of telecommunications operators, Smart Grid (SG) operators prefer telecommunications operators for their communications needs instead of creating private networks. In this paper, the use of Next Generation Networks (NGNs) by telecommunications operators to provide services to transnational SG operators for SG applications is evaluated. NGNs are all IP networks which are packet based and use IP to transport the various types of traffic such as data, voice, video, and signalling over converged fixed and mobile networks. The main idea of transnational SG operators is simple. By creating a huge single infrastructure for energy, more than one countries and nations can be powered at once. For this, it is not needed to install very huge power plants. Simply creating a complex network of power grid connections to each participating country is enough. The results of a set of simulation studies are given to show the efficiency of the NGN-based communication infrastructure for SG applications in terms of important network performance metrics. The results show that NGN-based communication infrastructures can carry packets based on their priority levels and bandwidth allocations in order to meet the specific requirements of SG applications.
Water is an inescapable necessity for all forms of life on Earth. Therefore, both man-made reservoirs and natural reservoirs play critical roles for several purposes. Evaporation is an important factor that should be ...
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The overwhelming acceptance of social media creates opportunities to learn about facts and events that are echoed in posts, tweets and messages uploaded by users. Analysis of these data can lead to interesting observa...
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The overwhelming acceptance of social media creates opportunities to learn about facts and events that are echoed in posts, tweets and messages uploaded by users. Analysis of these data can lead to interesting observations and conclusions. Of special importance are aspects related to temporal and dynamic nature of these findings. This paper presents a simple fuzzy-based approach of pre-processing and analyzing Twitter hashtags. The obtained fuzzy clusters are further examined in order to gain insight related to temporal trends and patterns of hashtags' popularity.
Automated decision systems for emboli detection is a crucial need since it is being done by visual determination of experts which causes excess time consumption and subjectivity. This work presents an emboli detection...
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Work-life balance (WLB) can be described as the fulfillment of the duties and responsibilities of workers in their private and business lives in addition to minimizing the conflicts between business and private lives....
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Work-life balance (WLB) can be described as the fulfillment of the duties and responsibilities of workers in their private and business lives in addition to minimizing the conflicts between business and private lives. This can be achieved with self-scheduling of workers only by allocating fair time for private life as well as work life. In enterprises, the workers demand, starting time and working hours of a job can vary according to the nature of the job done and quantitative and qualitative characteristics of workers. The main idea of this study is to develop a method which is balancing between work and private life by considering a self-scheduled working plan regulated systematical as far as weekly or monthly determining qualities and quantities of doctors and nurses to fulfill the needs for different departments of a hospital, considering the number of patients at different hours of a day. In this study, a prototype software was developed to fulfil the requirement of workers and enterprises for balancing work-life considering demands of workers and employers. The developed software can record the numbers and attributes of required personnel to a database according to daily, weekly or monthly demands. The current numbers and attributes of workers then requirements of the employer are entered into the database. Then, workers can choose their work times by considering day and hours from this database. The developed software reconciles the needs of the enterprise and personnel demands with synchronizing the needed working hours of enterprise and selection of personnel. Work assignments are done by personnel requests. Personnel decides their own working time so that monthly and weekly schedules can be obtained. The software is coded in Ms C# programming language and is applied in a hospital. The personnel demands which changes monthly, weekly and different working hours in a day can be assigned by considering doctors and nurses requests' with the help of developed so
In this study, propagation prediction models based on ray tracing in coverage estimation for broadcasting systems are compared with respect to computation time and accuracy. Uniform Theory of Diffraction (UTD), Slope ...
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ISBN:
(纸本)9781934142288
In this study, propagation prediction models based on ray tracing in coverage estimation for broadcasting systems are compared with respect to computation time and accuracy. Uniform Theory of Diffraction (UTD), Slope Diffraction (S-UTD) and Slope UTD with Convex Hull (S-UTD-CH) models are compared for computation time and propagation path loss. Moreover in this study, effects of transmitter height to relative path loss at the receiver are analyzed. S-UTD-CH model is optimum model with respect to computation time and relative path loss.
In this paper, 2-steps software using image processing and enhancement technologies is developed to obtain a scoliosis patient's spine pattern from 2D coronal X-Ray images without manual land marking. Then, a Rule...
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Cardiotocography is one of the most widely used technique for recording changes in fetal heart rate (FHR) and uterine contractions. Assessing cardiotocography is crucial in that it leads to iden- tifying fetuses which...
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Cardiotocography is one of the most widely used technique for recording changes in fetal heart rate (FHR) and uterine contractions. Assessing cardiotocography is crucial in that it leads to iden- tifying fetuses which suffer from lack of oxygen, i.e. hypoxia. This situation is defined as fetal dis- tress and requires fetal intervention in order to prevent fetus death or other neurological disease caused by hypoxia. In this study a computer-based approach for analyzing cardiotocogram in- cluding diagnostic features for discriminating a pathologic fetus. In order to achieve this aim adaptive boosting ensemble of decision trees and various other machine learning algorithms are employed.
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