The success of a contestant in the IOI certainly depends too much on the talent of the pupil, the qualification of her/his teachers and additional work with an individual coach. The success of a national team in the I...
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In this paper, we develop a mechanism to detect, model and track the shape of a contaminant cloud boundary using air borne sensor swarms. The cloud consists of a transparent gas of nuclear, biological or chemical cont...
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The gramian-based approach is proposed for estimation of control costs. The inputs of object are considered to be finite-dimensional. Authors proposed to consider the norm of control vector as a measure of system powe...
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As the mobile robots and various robot contests became very popular in the last few years, we developed the concept of a novel event for the students of our master module "Mechatronics and Robotics" - a virt...
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ISBN:
(纸本)9780889868137
As the mobile robots and various robot contests became very popular in the last few years, we developed the concept of a novel event for the students of our master module "Mechatronics and Robotics" - a virtual robot contest. The main idea was to allow them to participate in a robot competition and to design control strategies for various robot tasks without having a real robot. Instead, they can use a simulation and a virtual model of a mobile robot F.A.A.K., which was designed at our department. After preparatory stage, the students compete in an online contest with their robot models via Internet. In our contribution, the organization of the robot contest and developed simulation as well as communication tools are presented.
This paper informs about an international initiative of benchmarking introductory programming courses within various higher education institutions. It is based on comparisons of student performance in the final examin...
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Many countries of the world are actively researching and developing a large number of marine equipment for the study and development of the oceans. Along with the classical methods of ocean exploration, autonomous pla...
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The survival rate of lung cancer relies significantly on how far the disease has spread when it is detected, how it reacts to the treatment, the patient’s overall health, and other factors. Therefore, the earlier the...
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The survival rate of lung cancer relies significantly on how far the disease has spread when it is detected, how it reacts to the treatment, the patient’s overall health, and other factors. Therefore, the earlier the lung cancer diagnosis, the higher the survival rate. For radiologists, recognizing malignant lung nodules from computed tomography (CT) scans is a challenging and time-consuming process. As a result, computer-aided diagnosis (CAD) systems have been suggested to alleviate these burdens. Deep-learning approaches have demonstrated remarkable results in recent years, surpassing traditional methods in different fields. Researchers are currently experimenting with several deep-learning strategies to increase the effectiveness of CAD systems in lung cancer detection with CT. This work proposes a deep-learning framework for detecting and diagnosing lung cancer. The proposed framework used recent deep-learning techniques in all its layers. The autoencoder technique structure is tuned and used in the preprocessing stage to denoise and reconstruct the medical lung cancer dataset. Besides, it depends on the transfer learning pre-trained models to make multi-classification among different lung cancer cases such as benign, adenocarcinoma, and squamous cell carcinoma. The proposed model provides high performance while recognizing and differentiating between two types of datasets, including biopsy and CT scans. The Cancer Imaging Archive and Kaggle datasets are utilized to train and test the proposed model. The empirical results show that the proposed framework performs well according to various performance metrics. According to accuracy, precision, recall, F1-score, and AUC metrics, it achieves 99.60, 99.61, 99.62, 99.70, and 99.75%, respectively. Also, it depicts 0.0028, 0.0026, and 0.0507 in mean absolute error, mean squared error, and root mean square error metrics. Furthermore, it helps physicians effectively diagnose lung cancer in its early stages and allows spe
In this paper we propose a flux and position observer for permanent magnet synchronous motors when voltages, currents and rotor speed are available for measurement. We prove that this observer converges under weaker a...
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Tunable linear time-varying filters are widely used in many adaptive and signal processing applications. In this paper we consider a problem of stability analysis of tunable time-varying band-pass filters and prove th...
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Existing information systems often lack support to crisis and emergency situations. In such scenarios, the involved actors often engage in ad hoc collaborations necessary to understand and respond to the emerging even...
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ISBN:
(纸本)9783540928300
Existing information systems often lack support to crisis and emergency situations. In such scenarios, the involved actors often engage in ad hoc collaborations necessary to understand and respond to the emerging events. We propose a collaboration model and a prototype aiming to improve the consistency and effectiveness of emergent work activities. Our approach defends the requirement to construct shared situation awareness (SA). To support SA, we developed a collaborative artifact named situation matrixes (SM), which relates different situation dimensions (SD) of the crisis/emergency scenario. A method was also developed to construct and evaluate concrete SM and SD. This method was applied in two organizations' IT service desk teams, which often have to deal with emergency situations. The target organizations found our approach very relevant in organizing their response to emergencies.
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