• International Journal of Fluid Machinery and Systems
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• v.8 no.2
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• pp.102-112
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• 2015

In the Nordic grid, a trend observed the recent years is the increase in grid frequency variations, which means the frequency is outside the normal range (49.9-50.1 Hz) more often. Variations in the grid frequency leads to changes in the speed of rotation of all the turbines connected to the grid, since the speed of rotation is closely related to the grid frequency for synchronous generators. When the speed of rotation changes, this implies that the net torque acting on the rotating masses are changed, and the material of the turbine runners must withstand these changes in torque. Frequency variations thus leads to torque oscillations in the turbine, which become dynamical loads that the runner must be able to withstand. Several new Francis runners have recently experienced cracks in the runner blades due to fatigue, obviously due to the runner design not taking into account the actual loads on the runner. In this paper, the torque oscillations and dynamic loads due to the variations in grid frequency are simulated in a 1D MATLAB program, and measured grid frequency is used as input to the simulation program. The maximum increase and decrease in the grid frequency over a 440 seconds interval have been investigated, in addition to an extreme event where the frequency decreased far below the normal range within a few seconds. The dynamic loading originating from grid frequency variations is qualitatively found by a constructed variable $T_{stress}$, and for the simulations presented here the variations in $T_{stress}$ are found to be around 3 % of the mean value, which is a relatively small dynamic load. The important thing to remember is that these dynamic loads come in addition to all other dynamic loads, like rotor-stator interaction and draft tube surges, and should be included in the design process, if not found to be negligible.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.11a
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• pp.95-99
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• 2005

This paper presents a general proposal to design and calculate the performance of a tubular permanent magnet linear generator treated here on the basis of the Finite Element Method. Optimizing the linear generator dimensions reduces the cogging force, which occurs due to the interaction between stator teeth and the permanent magnets. The generated AC voltage is analyzed and evaluated for both no load and load cases to take the armature reaction effects on the air gap flux density. A repetitive routine is followed to calculate the output AC voltage from the change of flux and the speed of the single-phase linear generator. The AC output voltage is calculated for different resistive loads, and hence, the linear generator load characteristic is obtained. The designed linear generator is capable to generate an output power of 5.3kW with AC output voltage of 222V with an efficiency of 96.8% at full load of 23.8A. The full load current is chosen based on the thermal properties of the coil wire insulations.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1015-1024
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• 2003

In [1] we proposed a method to generate a test model (GFSM) from a set of scenarios of embedded software. Each scenario describes the interaction sequences for an external input event. Although these external events are generated and accepted alternatively and concurrently by embedded software, we considered only the alternative relations. In this paper, we describe an improved algorithm to generate GFSM from concurrent scenarios, and propose methods to reduce the number of transitions in the GFSM. The first is the synchronous interpretation of message passing instead of asynchronous one considering the real behavior of tasks in embedded software. The others apply the partial order techniques to the GFSM using independent regions. We apply the method to generate a reduced GFSM of embedded software running on a digital TV.

• Journal of Information Science Theory and Practice
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• v.7 no.3
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• pp.6-20
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• 2019

Learning analytics, or educational data mining, is an emerging field that applies data mining methods and tools for the exploitation of data coming from educational environments. Learning management systems, like Moodle, offer large amounts of data concerning students' activity, performance, behavior, and interaction with their peers and their tutors. The analysis of these data can be elaborated to make decisions that will assist stakeholders (students, faculty, and administration) to elevate the learning process in higher education. In this work, the power of Excel is exploited to analyze data in Moodle, utilizing an e-learning course developed for enhancing the information computer technology skills of school teachers in primary and secondary education in Greece. Moodle log files are appropriately manipulated in order to trace daily and weekly activity of the learners concerning distribution of access to resources, forum participation, and quizzes and assignments submission. Learners' activity was visualized for every hour of the day and for every day of the week. The visualization of access to every activity or resource during the course is also obtained. In this fashion teachers can schedule online synchronous lectures or discussions more effectively in order to maximize the learners' participation. Results depict the interest of learners for each structural component, their dedication to the course, their participation in the fora, and how it affects the submission of quizzes and assignments. Instructional designers may take advice and redesign the course according to the popularity of the educational material and learners' dedication. Moreover, the final grade of the learners is predicted according to their previous grades using multiple linear regression and sensitivity analysis. These outcomes can be suitably exploited in order for instructors to improve the design of their courses, faculty to alter their educational methodology, and administration to make decisions that will improve the educational services provided.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1596-1602
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• 2021

Battery-operated IoT devices in IoT systems require low power consumption. In general, IoT devices enter a sleep state synchronously to reduce power consumption. A problem arises when an IoT device has to handle asynchronous user requests, as the duty cycle must be reduced to enhance response time. In this paper, we propose a new low-power-consumption scheme, called Repetitive Wake-up scheme for IoT systems of asynchronous environments such as indoor lights control. The proposed scheme can reduce power consumption by sending wake-up signals from the smartphone repetitively and by retaining the IoT device in sleep state to the smallest possible duty cycle. In the various environments with IoT devices at home or office space, we showed that the proposed scheme can reduce power consumption by up to five times compared to the existing synchronous interlocking technique.