The seizure is a chain of abnormal neurological functions caused by the abnormal electrical discharge of neurons in the brain. The most common is epileptic seizures (ES) which are caused by sudden and uncontrolled ele...
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ISBN:
(纸本)9781728180731
The seizure is a chain of abnormal neurological functions caused by the abnormal electrical discharge of neurons in the brain. The most common is epileptic seizures (ES) which are caused by sudden and uncontrolled electrical discharges in brain cells. A routine 20-minute electroencephalogram (EEG) determines whether the brain's electrical activity is normal, or the presence of an electrical focus leading to epilepsy. However, the only EEG test by itself is not enough to establish a diagnosis of epileptic seizures. Another seizure known as Psychogenic Nonepileptic Seizures (PNES) is not involuntary electrical abnormal discharges results from psychological conditions rather than brain function. PNES can mimic the many manifestations of epilepsy. The similarity of these two types of seizures poses diagnostic challenges that often lead to delayed diagnosis of PNES. The diagnosis of PNES also involves high-cost hospital admission and monitoring using video-electroencephalogram machines (VEM). Due to economic feasibility and the tediousness of VEM, alternative methods are being researched to differentiate PNES and ES. In this study, we present a summary of the methods and obtained results for epileptic and non-epileptic (pseudo) seizure detection in the literature.
Evapotranspiration is the combined processes of evaporation and transpiration that give means the process of water loss to the atmosphere. Reference evapotranspiration (ETo) estimation is of importance in planning and...
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The industrial manipulator is a non-linear, strongly coupled, time-varying system, and it is affected by various uncertain factors such as unmodeled dynamics, parameter changes, external disturbances, and friction. Th...
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ISBN:
(数字)9789881563903
ISBN:
(纸本)9781728165233
The industrial manipulator is a non-linear, strongly coupled, time-varying system, and it is affected by various uncertain factors such as unmodeled dynamics, parameter changes, external disturbances, and friction. These uncertain factors will cause the tracking accuracy of the joints of the manipulator to deteriorate, which will lead to the instability of the entire manipulator system. Therefore, it is of great significance to achieve improved trajectory tracking precision of the manipulator and make the robotic arm have good dynamic performance. A new controller is designed in this paper. The controller uses a low-pass filter to reduce the chattering signal in the sliding mode control. Then, the type-2 fuzzy control is designed to simulate the external disturbance signal and the dynamic uncertain signal, so that the controller can effectively suppress the chattering caused by the sliding mode control algorithm, improve the robustness of the industrial manipulator control system, and effectively realize the high-precision track tracking control of the manipulator.
We present our preliminary results of an international survey on the practical adoption and use of the International Classification of Diseases (ICD) from a visualization and visual analytics perspective. The ICD syst...
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ISBN:
(纸本)9781728124230
We present our preliminary results of an international survey on the practical adoption and use of the International Classification of Diseases (ICD) from a visualization and visual analytics perspective. The ICD system, in different versions, is globally used for coding morbidity and mortality statistics, however, coding practices vary across countries. Our survey includes questions about hospital data collection systems, use of features in ICD, and training of ICD coding specialists. Variations in ICD could hinder comparability and limit generalizability of observed findings. Our preliminary results establish the current state of ICD use and training internationally, and will ultimately be valuable to the World Health Organization to further research on how to improve ICD coding, and enhance international comparisons of health data. From a visualization and visual analytics perspective, the current differences in adoption and use of ICD poses challenges and opportunities. For example, when morbidity-data from two countries differ in their coding, can we still compare data from these countries, and if so, then under which circumstances? We discuss how visualization and visual analytics might help in these situations.
We report a new ICF scheme whereby a capsule is imploded to near ignition conditions and subsequently flooded with hot electrons generated from a short-pulse laser plasma interaction so as to heat the whole assembly b...
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We report a new ICF scheme whereby a capsule is imploded to near ignition conditions and subsequently flooded with hot electrons generated from a short-pulse laser plasma interaction so as to heat the whole assembly by a few hundred eV. The cold dense shell pressure is increased by a larger factor than that of the hot spot at the capsule core, so that further heating and compression of the hot spot occurs. We suggest it may be possible to drive the capsule to ignition by the pressure augmentation supplied by this extra deposition of energy.
The traditional timing discrimination technique for laser rangefinding in remote sensing, which is lower in measurement performance and also has a larger error, has been unable to meet the high precision measurement a...
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The traditional timing discrimination technique for laser rangefinding in remote sensing, which is lower in measurement performance and also has a larger error, has been unable to meet the high precision measurement and high definition lidar image. To solve this problem, an improvement of timing accuracy based on the improved leading-edge timing discrimination(LED) is proposed. Firstly, the method enables the corresponding timing point of the same threshold to move forward with the multiple amplifying of the received signal. Then, timing information is sampled, and fitted the timing points through algorithms in MATLAB software. Finally, the minimum timing error is calculated by the fitting function. Thereby, the timing error of the received signal from the lidar is compressed and the lidar data quality is improved. Experiments show that timing error can be significantly reduced by the multiple amplifying of the received signal and the algorithm of fitting the parameters, and a timing accuracy of 4.63 ps is achieved.
Neural networks have demonstrated strong forecasting and pattern recognition capabilities in many fields, and supply chain performance evaluation has always been a key issue in enterprise management, especially in the...
Neural networks have demonstrated strong forecasting and pattern recognition capabilities in many fields, and supply chain performance evaluation has always been a key issue in enterprise management, especially in the modern complex business environment, the effective management of production-marketing integrated supply chain has become particularly important. The purpose of this study is to explore how to use neural network methods to evaluate the performance of production-marketing integrated supply chains. In this study, we first introduce the concept and importance of the production-marketing integrated supply chain, and then we explore the basic principles of neural networks and their application potential in supply chain management in detail. Neural networks can learn patterns from large amounts of data to better predict various factors in the supply chain, including demand fluctuations, inventory levels, transportation efficiency, and more. Next, we propose a neural network-based supply chain performance evaluation framework that combines several key performance indicators. By feeding these metrics into a neural network model, we can achieve a comprehensive assessment of supply chain performance. The study also includes a case study. We take a real production-marketing integrated supply chain as an example and apply the proposed neural network framework to evaluate the performance. Finally, we summarize the findings and contributions of this study, and emphasize the advantages and application prospects of the neural network-based supply chain performance evaluation method. This method is expected to provide enterprises with more comprehensive, accurate and real-time evaluation of supply chain performance, which will help improve the efficiency and competitiveness of supply chain.
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