Search results for "vector"
showing 10 items of 2660 documents
Electron–phonon coupling in degenerate silicon-on-insulator film probed using superconducting Schottky junctions
2002
Abstract Energy flow rate in degenerate n-type silicon-on-insulator (SOI) film is studied at low temperatures. The electrons are heated above the lattice temperature by electric field and the electron temperature is measured via semiconductor–superconductor quasiparticle tunneling. The energy flow rate in the system is found to be proportional to T 5 , indicating that electron–phonon relaxation rate and electron–phonon phase breaking rate are proportional to T 3 . The electron–phonon system in the SOI film is in the “dirty limit” where the electron mean free path is smaller than the inverse of the thermal phonon wave vector.
Highly sensitive superconducting circuits at ∼700 kHz with tunable quality factors for image-current detection of single trapped antiprotons
2016
We developed highly-sensitive image-current detection systems based on superconducting toroidal coils and ultra-low noise amplifiers for non-destructive measurements of the axial frequencies (550$\sim$800$\,$kHz) of single antiprotons stored in a cryogenic multi-Penning-trap system. The unloaded superconducting tuned circuits show quality factors of up to 500$\,$000, which corresponds to a factor of 10 improvement compared to our previously used solenoidal designs. Connected to ultra-low noise amplifiers and the trap system, signal-to-noise-ratios of 30$\,$dB at quality factors of > 20$\,$000 are achieved. In addition, we have developed a superconducting switch which allows continuous tu…
The explicative power of the vector potential for superconductivity: a path for high school
2014
In the classroom practice the notion of the magnetic vector potential is never introduced, both because it is not contained in secondary school textbooks and because teachers usually associate this concept with complex topics they dealt with in their university courses. In our experience instead, we have found that the introduction of the vector potential can be of great help in students’ understanding of electromagnetism and modern physics topics. In this paper we will show how the use of the vector potential allows a phenomenological and consistent explanation of superconductivity at a level suitable for high school students. We will deal with the two main aspects of superconductivity: th…
Vector Potential at High School: A Way to Introduce Superconductivity and to Review Electromagnetism
2014
Superconductivity is a rich and complex topic that generates great interest and curiosity in high school students. Most of the presentations of superconductivity give a great importance to magnetism. But typically in these presentations the physical role is played by the magnetic field B while the magnetic vector potential A is never mentioned. Moreover the explanation of the quantum phenomena at the base of the superconductivity are often not enough developed and generally given only at a popular level. We think that the key point for a meaningful presentation at high school is the vector potential. In this paper we present a teaching path on the vector potential and a pilot experimentatio…
Classification and Automated Interpretation of Spinal Posture Data Using a Pathology-Independent Classifier and Explainable Artificial Intelligence (…
2021
Clinical classification models are mostly pathology-dependent and, thus, are only able to detect pathologies they have been trained for. Research is needed regarding pathology-independent classifiers and their interpretation. Hence, our aim is to develop a pathology-independent classifier that provides prediction probabilities and explanations of the classification decisions. Spinal posture data of healthy subjects and various pathologies (back pain, spinal fusion, osteoarthritis), as well as synthetic data, were used for modeling. A one-class support vector machine was used as a pathology-independent classifier. The outputs were transformed into a probability distribution according to Plat…
An Ensemble Learning Method for Emotion Charting Using Multimodal Physiological Signals
2022
Emotion charting using multimodal signals has gained great demand for stroke-affected patients, for psychiatrists while examining patients, and for neuromarketing applications. Multimodal signals for emotion charting include electrocardiogram (ECG) signals, electroencephalogram (EEG) signals, and galvanic skin response (GSR) signals. EEG, ECG, and GSR are also known as physiological signals, which can be used for identification of human emotions. Due to the unbiased nature of physiological signals, this field has become a great motivation in recent research as physiological signals are generated autonomously from human central nervous system. Researchers have developed multiple methods for …
Internet of Things with Deep Learning-Based Face Recognition Approach for Authentication in Control Medical Systems
2022
Internet of Things (IoT) with deep learning (DL) is drastically growing and plays a significant role in many applications, including medical and healthcare systems. It can help users in this field get an advantage in terms of enhanced touchless authentication, especially in spreading infectious diseases like coronavirus disease 2019 (COVID-19). Even though there is a number of available security systems, they suffer from one or more of issues, such as identity fraud, loss of keys and passwords, or spreading diseases through touch authentication tools. To overcome these issues, IoT-based intelligent control medical authentication systems using DL models are proposed to enhance the security f…
Effectively Predicting the Presence of Coronary Heart Disease Using Machine Learning Classifiers
2022
Coronary heart disease is one of the major causes of deaths around the globe. Predicating a heart disease is one of the most challenging tasks in the field of clinical data analysis. Machine learning (ML) is useful in diagnostic assistance in terms of decision making and prediction on the basis of the data produced by healthcare sector globally. We have also perceived ML techniques employed in the medical field of disease prediction. In this regard, numerous research studies have been shown on heart disease prediction using an ML classifier. In this paper, we used eleven ML classifiers to identify key features, which improved the predictability of heart disease. To introduce the prediction …
Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia
2020
Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signals may provide broader information about the brain status during anesthesia. Appropriate parameter selection and combination to a single index is crucial to take advantage of this potential. The field of machine learning offers algorithms for both parameter selection and combination. In this study, several established machine learning approaches including a method for the selection of suitable signal parameters and classification algorithms are a…
An affordable contactless security system access for restricted area
2016
International audience; We present in this paper a security system based on identity verification process and a low-cost smart camera , intended to avoid unauthorized access to restricted area. The Le2i laboratory has a longstanding experience in smart cameras implementation and design [1], for example in the case of real-time classical face detection [2] or human fall detection [3]. The principle of the system, fully thought and designed in our laboratory, is as follows: the allowed user presents a RFID card to the reader based on Odalid system [4]. The card ID, time and date of authorized access are checked using connection to an online server. In the same time, multi-modality identity ve…