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.
Cloud Computing is a new technology that has rapidly established itself in computer science since it allows the usage of huge computing resources that are dynamically allocated in order to satisfy user's needs and...
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Cloud Computing is a new technology that has rapidly established itself in computer science since it allows the usage of huge computing resources that are dynamically allocated in order to satisfy user's needs and that are accessible as a service through a remote interface, such as a web browser. Cloud resources can be distributed in different places and such distribution is made transparent to the user;this one does not need to worry about data replication and/or maintenance of the infrastructure but he/she benefits only of the required services, by exploiting the Pay-Per-Use business model. In this context, the interoperability among different providers becomes critical due to the vendor lock-in problem. Here we present a multi agent system that accesses, on behalf of the user, the utility market of Cloud computing to maintain the best resources configuration that satisfies the application requirements. It also offers management and monitoring facilities for the Cloud infrastructure in order to guide the user in all the phases of the application's lifecycle. Together with the platform, we present client-side tools that can be used to orchestrate agents' based services.
In this work, classification of cellular structures in the high resolutional histopathological images and the discrimination of cellular and non-cellular structures have been investigated. The cell classification is a...
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In this work, classification of cellular structures in the high resolutional histopathological images and the discrimination of cellular and non-cellular structures have been investigated. The cell classification is a very exhaustive and time-consuming process for pathologists in medicine. The development of digital imaging in histopathology has enabled the generation of reasonable and effective solutions to this problem. Morever, the classification of digital data provides easier analysis of cell structures in histopathological data. Convolutional neural network (CNN), constituting the main theme of this study, has been proposed with different spatial window sizes in RGB color spaces. Hence, to improve the accuracies of classification results obtained by supervised learning methods, spatial information must also be considered. So, spatial dependencies of cell and non-cell pixels can be evaluated within different pixel neighborhoods in this study. In the experiments, the CNN performs superior than other pixel classification methods including SVM and k-Nearest Neighbour (k-NN). At the end of this paper, several possible directions for future research are also proposed.
Sum of squares (SOS) optimization has been a powerful and influential addition to the theory of optimization in the past decade. Its reliance on relatively large-scale semidefinite programming, however, has seriously ...
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Sum of squares (SOS) optimization has been a powerful and influential addition to the theory of optimization in the past decade. Its reliance on relatively large-scale semidefinite programming, however, has seriously challenged its ability to scale in many practical applications. In this paper, we introduce DSOS and SDSOS optimization as more tractable alternatives to sum of squares optimization that rely instead on linear programming and second order cone programming. These are optimization problems over certain subsets of sum of squares polynomials and positive semidefinite matrices and can be of potential interest in general applications of semidefinite programming where scalability is a limitation.
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