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Добірка наукової літератури з теми "D-ECG"

Автор: Grafiati

Опубліковано: 10 січня 2023

Оновлено: 28 січня 2023

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Статті в журналах з теми "D-ECG"

Sayed Ismail, Sharifah Noor Masidayu, Nor Azlina Ab. Aziz, Siti Zainab Ibrahim, Sophan Wahyudi Nawawi, Salem Alelyani, Mohamed Mohana, and Lee Chia Chun. "Evaluation of electrocardiogram: numerical vs. image data for emotion recognition system." F1000Research 10 (May 30, 2022): 1114. http://dx.doi.org/10.12688/f1000research.73255.2.

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Background: The electrocardiogram (ECG) is a physiological signal used to diagnose and monitor cardiovascular disease, usually using 2- D ECG. Numerous studies have proven that ECG can be used to detect human emotions using 1-D ECG; however, ECG is typically captured as 2-D images rather than as 1-D data. There is still no consensus on the effect of the ECG input format on the accuracy of the emotion recognition system (ERS). The ERS using 2-D ECG is still inadequately studied. Therefore, this study compared ERS performance using 1-D and 2-D ECG data to investigate the effect of the ECG input format on the ERS. Methods: This study employed the DREAMER dataset, which contains 23 ECG recordings obtained during audio-visual emotional elicitation. Numerical data was converted to ECG images for the comparison. Numerous approaches were used to obtain ECG features. The Augsburg BioSignal Toolbox (AUBT) and the Toolbox for Emotional feature extraction from Physiological signals (TEAP) extracted features from numerical data. Meanwhile, features were extracted from image data using Oriented FAST and rotated BRIEF (ORB), Scale Invariant Feature Transform (SIFT), KAZE, Accelerated-KAZE (AKAZE), Binary Robust Invariant Scalable Keypoints (BRISK), and Histogram of Oriented Gradients (HOG). Dimension reduction was accomplished using linear discriminant analysis (LDA), and valence and arousal were classified using the Support Vector Machine (SVM). Results: The experimental results show 1-D ECG-based ERS achieved 65.06% of accuracy and 75.63% of F1 score for valence, and 57.83% of accuracy and 44.44% of F1-score for arousal. For 2-D ECG-based ERS, the highest accuracy and F1-score for valence were 62.35% and 49.57%; whereas, the arousal was 59.64% and 59.71%. Conclusions: The results indicate that both inputs work comparably well in classifying emotions, which demonstrates the potential of 1-D and 2-D as input modalities for the ERS.

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Zhang, Yin-Han, Jerry Bryant, Fan-Lin Kong, Dong-Fang Yu, Richard Mendez, E. Edmund Kim, and David J. Yang. "Molecular Imaging of Mesothelioma withT99mc-ECG andG68a-ECG." Journal of Biomedicine and Biotechnology 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/232863.

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We have developed ethylenedicysteine-glucosamine (ECG) as an alternative to18F-fluoro-2-deoxy-D-glucose (18F-FDG) for cancer imaging. ECG localizes in the nuclear components of cells via the hexosamine biosynthetic pathway. This study was to evaluate the feasibility of imaging mesothelioma withT99mc-ECG andG68a-ECG. ECG was synthesized from thiazolidine-4-carboxylic acid and 1,3,4,6-tetra-O-acetyl-2-amino-D-glucopyranose, followed by reduction in sodium and liquid ammonia to yield ECG (52%). ECG was chelated withT99mc/tin (II) andG68a/69Ga chloride forin vitroandin vivostudies in mesothelioma. The highest tumor uptake ofT99mc-ECG is 0.47 at 30 min post injection, and declined to 0.08 at 240 min post injection. Tumor uptake (%ID/g), tumor/lung, tumor/blood, and tumor/muscle count density ratios forT99mc-ECG (30–240 min) were0.47±0.06to0.08±0.01;0.71±0.07to0.85±0.04;0.47±0.03to0.51±0.01, and3.49±0.24to5.06±0.25; forG68a-ECG (15–60 min) were0.70±0.06to0.92±0.08;0.64±0.05to1.15±0.08;0.42±0.03to0.67±0.07, and3.84±0.52to7.00±1.42; for18F-FDG (30–180 min) were1.86±0.22to1.38±0.35;3.18±0.44to2.92±0.34,4.19±0.44to19.41±2.05and5.75±2.55to3.33±0.65, respectively. Tumor could be clearly visualized withT99mc-ECG andG68a-ECG in mesothelioma-bearing rats.T99mc-ECG andG68a-ECG showed increased uptake in mesothelioma, suggesting they may be useful in diagnosing mesothelioma and also monitoring therapeutic response.

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Tanoh, Ian-Christopher, and Paolo Napoletano. "A Novel 1-D CCANet for ECG Classification." Applied Sciences 11, no. 6 (March 19, 2021): 2758. http://dx.doi.org/10.3390/app11062758.

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This paper puts forward a 1-D convolutional neural network (CNN) that exploits a novel analysis of the correlation between the two leads of the noisy electrocardiogram (ECG) to classify heartbeats. The proposed method is one-dimensional, enabling complex structures while maintaining a reasonable computational complexity. It is based on the combination of elementary handcrafted time domain features, frequency domain features through spectrograms and the use of autoregressive modeling. On the MIT-BIH database, a 95.52% overall accuracy is obtained by classifying 15 types, whereas a 95.70% overall accuracy is reached when classifying 7 types from the INCART database.

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McClean, Gavin, Nathan R. Riding, Guido Pieles, Victoria Watt, Carmen Adamuz, Sanjay Sharma, Keith P. George, David Oxborough, and Mathew G. Wilson. "Diagnostic accuracy and Bayesian analysis of new international ECG recommendations in paediatric athletes." Heart 105, no. 2 (September 18, 2018): 152–59. http://dx.doi.org/10.1136/heartjnl-2018-313466.

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ObjectiveHistorically, electrocardiographic (ECG) interpretation criteria for athletes were only applicable to adults. New international recommendations now account for athletes ≤16 years, but their clinical appropriateness is unknown. We sought to establish the diagnostic accuracy of new international ECG recommendations against the Seattle criteria and 2010 European Society of Cardiology (ESC) recommendations in paediatric athletes using receiver operator curve analysis. Clinical context was calculated using Bayesian analysis.Methods876 Arab and 428 black male paediatric athletes (11–18 years) were evaluated by medical questionnaire, physical examination, ECG and echocardiographic assessment. ECGs were retrospectively analysed according to the three criteria.ResultsThirteen (1.0%) athletes were diagnosed with cardiac pathology that may predispose to sudden cardiac arrest/death (SCA/D) (8 (0.9%) Arab and (5 (1.2%) black)). Diagnostic accuracy was poor (0.68, 95% CI 0.54 to 0.82) for 2010 ESC recommendations, fair (0.70, 95% CI 0.54 to 0.85) for Seattle criteria and fair (0.77, 95% CI 0.61 to 0.93) for international recommendations. False-positive rates were 41.0% for 2010 ESC recommendations, 21.8% for Seattle criteria and 6.8% for international recommendations. International recommendations provided a positive (+LR) and negative (−LR) post-test likelihood ratio of 9.0 (95% CI 5.1 to 13.1) and 0.4 (95% CI 0.2 to 0.7), respectively.ConclusionIn Arab and black male paediatric athletes, new international recommendations outperform both the Seattle criteria and 2010 ESC recommendations, reducing false positive rates, while yielding a ‘fair’ diagnostic accuracy for cardiac pathology that may predispose to SCA/D. In clinical context, the ‘chance’ of detecting cardiac pathology within a paediatric male athlete with a positive ECG (+LR=9.0) was 8.3%, whereas a negative ECG (−LR=0.4) was 0.4%.

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Herraiz, Álvaro Huerta, Arturo Martínez-Rodrigo, Vicente Bertomeu-González, Aurelio Quesada, José J. Rieta, and Raúl Alcaraz. "A Deep Learning Approach for Featureless Robust Quality Assessment of Intermittent Atrial Fibrillation Recordings from Portable and Wearable Devices." Entropy 22, no. 7 (July 1, 2020): 733. http://dx.doi.org/10.3390/e22070733.

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Atrial fibrillation (AF) is the most common heart rhythm disturbance in clinical practice. It often starts with asymptomatic and very short episodes, which are extremely difficult to detect without long-term monitoring of the patient’s electrocardiogram (ECG). Although recent portable and wearable devices may become very useful in this context, they often record ECG signals strongly corrupted with noise and artifacts. This impairs automatized ulterior analyses that could only be conducted reliably through a previous stage of automatic identification of high-quality ECG intervals. So far, a variety of techniques for ECG quality assessment have been proposed, but poor performances have been reported on recordings from patients with AF. This work introduces a novel deep learning-based algorithm to robustly identify high-quality ECG segments within the challenging environment of single-lead recordings alternating sinus rhythm, AF episodes and other rhythms. The method is based on the high learning capability of a convolutional neural network, which has been trained with 2-D images obtained when turning ECG signals into wavelet scalograms. For its validation, almost 100,000 ECG segments from three different databases have been analyzed during 500 learning-testing iterations, thus involving more than 320,000 ECGs analyzed in total. The obtained results have revealed a discriminant ability to detect high-quality and discard low-quality ECG excerpts of about 93%, only misclassifying around 5% of clean AF segments as noisy ones. In addition, the method has also been able to deal with raw ECG recordings, without requiring signal preprocessing or feature extraction as previous stages. Consequently, it is particularly suitable for portable and wearable devices embedding, facilitating early detection of AF as well as other automatized diagnostic facilities by reliably providing high-quality ECG excerpts to further processing stages.

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Ullah, Amin, Syed Muhammad Anwar, Muhammad Bilal, and Raja Majid Mehmood. "Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation." Remote Sensing 12, no. 10 (May 25, 2020): 1685. http://dx.doi.org/10.3390/rs12101685.

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The electrocardiogram (ECG) is one of the most extensively employed signals used in the diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture the heart’s rhythmic irregularities, commonly known as arrhythmias. A careful study of ECG signals is crucial for precise diagnoses of patients’ acute and chronic heart conditions. In this study, we propose a two-dimensional (2-D) convolutional neural network (CNN) model for the classification of ECG signals into eight classes; namely, normal beat, premature ventricular contraction beat, paced beat, right bundle branch block beat, left bundle branch block beat, atrial premature contraction beat, ventricular flutter wave beat, and ventricular escape beat. The one-dimensional ECG time series signals are transformed into 2-D spectrograms through short-time Fourier transform. The 2-D CNN model consisting of four convolutional layers and four pooling layers is designed for extracting robust features from the input spectrograms. Our proposed methodology is evaluated on a publicly available MIT-BIH arrhythmia dataset. We achieved a state-of-the-art average classification accuracy of 99.11%, which is better than those of recently reported results in classifying similar types of arrhythmias. The performance is significant in other indices as well, including sensitivity and specificity, which indicates the success of the proposed method.

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Hamad alhussainy, Aqeel M., and Ammar D. Jasim. "ECG signal classification based on Deep Learning by using Convolutional Neural Network (CNN)." Iraqi Journal of Information & Communications Technology 3, no. 3 (December 31, 2020): 12–23. http://dx.doi.org/10.31987/ijict.3.3.106.

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Cardiovascular diseases (CVDs) are consider the main cause of death today According to World Health Organization (WHO),and because that ECG signal is very important tool in monitoring and diagnosis of these disease , different automatic methods were proposed based on this signal. [1]. The manual analysis of ECG signals is suffered different challenges such as differeculty of detecting and classify waveform of this signal, So, many machine learning methods are explored to describe the anomalies ECG signal accurately . Deep learning (DL) can be used in ECG classification, it can improve the quality of the automatic classification system. In this paper , we have proposed a deep learning classification system by using different layers of convolution, rectifier and pooling operations that can be used to increase feature extraction of ECG signal. We have proposed two models, one is used for input signal of 1-D, in which we designed model for classification csv type of data for ECG signal, while in the second proposed system, we used model for 2-D signal after convert it from its csv type . 2-D signal (ECG image) is used in order to augment the two dimensional signal with different methods to increase the accuracy of the model by training it with geometric transformation of the original input images such as rotation, shearing etc.The results are compared with AlexNet and other models based on the metrics, which are used to measure the performance of the proposed work, the result show that, the proposed models improve the efficiency of the classification in the two systems.

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Alvarez, R. H., B. E. Almeida, M. T. C. P. Ribela, F. L. N. Natal, A. J. F. Melo, and P. Bartolini. "211 REVERSED-PHASE HIGH-PERFORMANCE LIQUID CHROMATOGRAPHY AS A TOOL TO ELUCIDATE THE BIOLOGICAL ACTIVITY OF COMMERCIAL EQUINE CHORIONIC GONADOTROPIN (eCG)." Reproduction, Fertility and Development 26, no. 1 (2014): 219. http://dx.doi.org/10.1071/rdv26n1ab211.

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Superovulation in ruminants can be induced with a single injection of equine chorionic gonadotropin (eCG). However, ovarian response is sometimes lower than expected because of, among other factors, the source of eCG used. This study aimed at establishing the physical-chemical profile of commercial eCG, in order to find differences which can be related to their biological activity. Four different commercial eCG products for veterinary use (A, B, C, D) and one eCG chemical reagent from Sigma (St. Louis, MO, USA), here used as reference preparation, were analysed by reversed-phase high-performance liquid chromatography (RP-HPLC) using a C4-Grace Vydac 214 TP 54-column (25 cm × 4.6 mm I.D.), with UV detection at 220 nm. All eCG preparations presented at least three peaks with retention times (tR) of ~27(I), 34(II), and 36(III) minutes, with a peak at tR = 27 min common to A, C, D, and Sigma eCG, whereas preparation B did not present this peak. A bioassay test was carried with all of these preparations. Immature 21- to 25-day-old Wistar female rats received the equivalent to 10 IU of eCG of each one of these preparations. Autopsy was performed 48 h later and ovaries were removed and weighed. The average ovarian weight for preparations A, C, D, and Sigma were ~0.0795 ± 0.0107 g, whereas preparation B was 0.035 ± 0.007 g (P < 0.01). Preparation B was not different from saline (0.034 ± 0.002 g). In order to establish which one of these three peaks presented the highest biological activity, a mass equivalent to 10 IU of eCG from peaks I, II, and III of Sigma and of product A were studied. The average ovarian weight of animals injected with material from peak II and III (~0.0285 ± 0.003 g) were similar to that of the control whereas peak I produced ovarian weights of 0.059 ± 0.007 g and 0.075 ± 0.010 g for Sigma and product A, respectively (P < 0.01). These results suggest that the lack of ovarian response to eCG treatments can be related to differences in the physical-chemical profile of commercial eCG products and that RP-HPLC is a fast and reliable tool for detecting these differences. Supported by FAPESP (Grant 11/13096-0).

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Jamil, Sonain, and MuhibUr Rahman. "A Novel Deep-Learning-Based Framework for the Classification of Cardiac Arrhythmia." Journal of Imaging 8, no. 3 (March 10, 2022): 70. http://dx.doi.org/10.3390/jimaging8030070.

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Cardiovascular diseases (CVDs) are the primary cause of death. Every year, many people die due to heart attacks. The electrocardiogram (ECG) signal plays a vital role in diagnosing CVDs. ECG signals provide us with information about the heartbeat. ECGs can detect cardiac arrhythmia. In this article, a novel deep-learning-based approach is proposed to classify ECG signals as normal and into sixteen arrhythmia classes. The ECG signal is preprocessed and converted into a 2D signal using continuous wavelet transform (CWT). The time–frequency domain representation of the CWT is given to the deep convolutional neural network (D-CNN) with an attention block to extract the spatial features vector (SFV). The attention block is proposed to capture global features. For dimensionality reduction in SFV, a novel clump of features (CoF) framework is proposed. The k-fold cross-validation is applied to obtain the reduced feature vector (RFV), and the RFV is given to the classifier to classify the arrhythmia class. The proposed framework achieves 99.84% accuracy with 100% sensitivity and 99.6% specificity. The proposed algorithm outperforms the state-of-the-art accuracy, F1-score, and sensitivity techniques.

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deNicolo, G., S. T. Morris, P. R. Kenyon, P. C. H. Morel, and T. J. Parkinson. "Out-of-season breeding of Romney sheep using artificially induced long days." Australian Journal of Experimental Agriculture 48, no. 7 (2008): 961. http://dx.doi.org/10.1071/ea07406.

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This experiment investigated the effects of subjecting Romney ewes to artificially induced long days (24 L : 0 D) in spring for 30 days, then abruptly applying 8 hours of darkness (16 L : 8 D) to induce the onset of reproductive activity. The treatment groups were: light + progesterone; light + progesterone + eCG; and progesterone + eCG (ambient photoperiod; control). Blood samples were collected over a 24-h period for analysis of serum melatonin concentrations. Ewes’ ovaries were examined laparoscopically 9 days after progesterone removal. Duration of secretion and maximal concentrations of melatonin were lower in ewes treated with light + progesterone (±eCG) compared with the control ewes. Fewer light + progesterone treated ewes displayed oestrus (66%) and were subsequently identified as being pregnant (28%) compared with ewes treated with light + progesterone + eCG (98% and 53%) and control ewes (97% and 65%, respectively). Conception rates were lower in light + progesterone treated ewes (43%) compared with light + progesterone + eCG (55%) and control ewes (67%). Results obtained indicate that artificially induced long days did not improve the results of out-of-season breeding program beyond that achieved with the use of eCG.

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Більше джерел

Дисертації з теми "D-ECG"

Vaníček, Aleš. "Ambulantní monitor srdečního rytmu." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219463.

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This thesis describes the design and practical realization of a prototype mobile, battery-powered device that is able to periodically recording electrocardiogram and fotopletysmogram or blood pressure. Data from these periodic scanning is processed by microcontroller and stored on a memory card which is part of the proposed device. The device can be connected to a PC via USB like a virtual serial port.

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Chamadiya, Bhavin [Verfasser]. "Applications of textile based capacitive ECG recordings / Bhavin Chamadiya." Lübeck : Zentrale Hochschulbibliothek Lübeck, 2012. http://d-nb.info/102926404X/34.

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Gruetzmann, Anna [Verfasser]. "Wireless ECG Sensor in Surface Acoustic Wave Transponder Technology / Anna Gruetzmann." München : Verlag Dr. Hut, 2010. http://d-nb.info/1009484524/34.

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Khawaja, Antoun [Verfasser]. "Automatic ECG analysis using principal component analysis and wavelet transformation / von Antoun Khawaja." Karlsruhe : Univ.-Verl. Karlsruhe, 2007. http://d-nb.info/985224770/34.

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Campitelli, Marcelo Adrián. "Compressão de sinais ECG utilizando DWT com quantização não-linear e por sub-bandas." reponame:Repositório Institucional da UnB, 2015. http://dx.doi.org/10.26512/2015.12.D.19564.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.
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Com o desenvolvimento cada vez mais intenso da tecnologia de dispositivos biomédicos, há cada vez mais acesso aos sinais bioelétricos, o que permite grande avanço na realização de diagnósticos, planejamento de tratamentos e monitoração de pacientes. Particularmente, o eletrocardiograma (ECG) tem sido usado para muitos propósitos. Além disso, novas formas simples e de baixo custo para adquirir o ECG tem sido descobertas. Entretanto, esses avanços exigem o melhoramento dos processos de codificação do sinal de ECG, de forma a permitir seu armazenamento e transmissão eficientemente em termos de requisitos de memória e consumo de energia. Neste contexto, o presente trabalho propõe duas contribuições. Em primeiro lugar, apresenta um algoritmo de compressão de sinais ECG, utilizando transformadas wavelets, e propondo um processo de quantização novo, não encontrado na literatura. Nesse processo, a transformação é realizada utilizando a transformada discreta de wavelets (DWT) e a quantização consiste em um re-ordenamento não-linear das magnitudes dos coeficientes transformados (correção gamma) em conjunto com uma quantização por sub-bandas. A segunda contribuição consiste num estudo sistemático do desempenho das diferentes famílias de wavelets nos resultados obtidos pelo algoritmo proposto, calculando também os parâmetros ótimos de quantização para cada família wavelet utilizada. Para a análise desses métodos, foram realizados testes avaliando o desempenho do algoritmo proposto e comparando os resultados com outros métodos apresentados na literatura. Nesses testes, foram usados como referências os sinais da base de dados do Instituto de Tecnologia de Massachusetts e do Hospital Beth Israel de Boston (MIT-BIH). Uma parcela do banco de dados foi utilizada para otimizar os parâmetros de cada família wavelet no algoritmo proposto, e o desempenho final foi avaliado com todos os sinais restantes. Especificamente, para o sinal 117 do MIT-BIH, que é o sinal mais utilizado para comparar resultados na literatura, o método proposto levou a um fator de compressão (CR) de 11,40 e uma raiz da diferença média percentual (PRD) de 1,38. Demonstrou-se que o algoritmo gera melhores resultados de compressão quando comparado com a maioria dos métodos do estado-da-arte. Também se destaca a simplicidade na implementação do algoritmo em relação a outros encontrados na literatura.
With the increasing development of biomedical devices technology, there is more access to bioelectrical signals. That allows great advances in reaching diagnostics, planning treatments and monitoring patients. Particularly, the electrocardiogram (ECG) has been used for many purposes. Besides that, simple and low-cost ways to acquire the ECG have been found. Nevertheless, those advances require the improvement of the ECG signal coding processes, in a way that allows its efficient storage and transmission in terms of memory requirements and energy consumption. In this context, this dissertation proposes two contributions. Firstly, it presents an ECG signal compression algorithm, using wavelet transforms, and proposing a novel quantization process, not found in the literature. In said process, the transformation is done using the discrete wavelet transform (DWT) and the quantization consists of a non-linear re-ordering of the transformed coefficients magnitudes (gamma correction) in tandem with a sub-band quantization. The second contribution consists in a systematic study of the performance of the different wavelet families through the results obtained by the proposed algorithm, also calculating the optimum quantization parameters for each wavelet family. For the analysis of these methods, tests were done evaluating the performance of the proposed algorithm, comparing its results with other methods presented in the literature. In said tests, signals from the Massachusetts Institute of Technology and Boston’s Beth Israel Hospital database (MIT-BIH) were used as reference. A part of the database was utilized to optimize the parameters of each wavelet family, and the final performance was evaluated with the remaining signals from the database. Specifically, for signal 117 of the MIT-BIH database, which is the most used signal to compare results in the literature, the proposed method led to a compression factor (CR) of 11,40 and a percentage root-mean-square difference (PRD) of 1,38. It was demonstrated that the algorithm generates better compression results when compared to the majority of state-of-the-art methods. The simplicity of the algorithm’s implementation also stands out in relation to other algorithms found in the literature.

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Herz, Franziska [Verfasser], Matthias [Akademischer Betreuer] Gutberlet, Lukas [Akademischer Betreuer] Lehmkuhl, Thomas [Gutachter] Kahn, and Ardawan [Gutachter] Rastan. "Diagnostic performance of prospectively ECG triggered versus retrospectively ECG gated 64-slice computed tomography coronary angiography in a heterogeneous patient population / Franziska Herz ; Gutachter: Thomas Kahn, Ardawan Rastan ; Matthias Gutberlet, Lukas Lehmkuhl." Leipzig : Universitätsbibliothek Leipzig, 2012. http://d-nb.info/1238020720/34.

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Baumgarten, Kai [Verfasser], Constantin [Akademischer Betreuer] Czekelius, and Klaus [Gutachter] Schaper. "Synthese und Evaluierung von ECG-Derivaten / Kai Baumgarten ; Gutachter: Klaus Schaper ; Betreuer: Constantin Czekelius." Düsseldorf : Universitäts- und Landesbibliothek der Heinrich-Heine-Universität Düsseldorf, 2019. http://d-nb.info/1188882171/34.

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Hofer, Armin [Verfasser]. "Einfluss einer eCG-Applikation im Puerperium auf die Fruchtbarkeit von Fleckvieh-Milchkühen / Armin Hofer." Gießen : Universitätsbibliothek, 2020. http://d-nb.info/1209159783/34.

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Gazbour, Nouha. "Intégration systémique de l’éco-conception dès la phase de R&D des technologies photovoltaïques." Thesis, Université Grenoble Alpes (ComUE), 2019. http://www.theses.fr/2019GREAT018/document.

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Face aux enjeux environnementaux actuels, s’investir dans les énergies renouvelables au nom de la « transition énergétique » est l’alternative la plus adoptée par de nombreux pays. Les énergies renouvelables, en particulier l’énergie photovoltaïque, sont ainsi devenues des secteurs concurrentiels innovants en pleine expansion. Dans ce contexte, il est donc nécessaire de s'assurer que les nouvelles technologies PV, qui sont complexes et issues de plusieurs étapes de fabrication, répondent aux critères d'un produit peu impactant pour l’environnement, dénommé ici éco-conçu. L’état de l’art sur l’éco-conception montre que la prise en compte des contraintes environnementales dans les projets de R&D à échelle TRL « Technology Readiness Level » bas est encore un phénomène émergent, pour les raisons suivantes : d’une part l’évaluation de l’impact environnemental est relativement complexe pour une technologie non mature en cours de développement (TRL bas) ; ses caractéristiques et procédés de fabrication n’étant pas encore tous connus ; d’autre part les outils identifiés présentent plusieurs écueils qui limitent leur intégration dans les organismes PV de R&D.Ce travail de recherche vise donc à développer une méthodologie pour permettre l’intégration pérenne de l’éco-conception dans les organismes de R&D, pour accompagner leurs partenaires industriels dans leur effort d’innovation et de compétitivité.La méthode développée est ainsi basée sur le principe d’estimation des taux d’évolutions techniques, économiques et environnementales d’une nouvelle technologie (TRL bas) par l’intermédiaire d’une base de données de référence. La construction de cette dernière s’appuie sur l’Analyse du Cycle de Vie (ACV) comme outil de pilotage pour fournir des résultats fiables, malgré le faible niveau TRL.Pour intégrer de façon pérenne cette approche au sein des organismes de R&D, la méthode développée a été implémentée dans un outil informatique « ECO PV » dédié aux systèmes PV en silicium cristallin, qui constituent plus de 90% du marché PV actuel. Basé sur le principe de démocratisation des connaissances environnementales et de la capitalisation des informations, cet outil est accessible non seulement aux experts en ACV mais aussi à l’ensemble des ingénieurs du domaine PV.Ce travail de recherche a enfin permis d’une part de générer des premiers résultats à la fois fiables, simples et quantifiés, et de développer une méthodologie d’éco-conception pour orienter les choix technologiques des projets dans les phases amont de R&D, afin de développer des systèmes PV plus respectueux de l’environnement
Faced with current environmental challenges, investing in renewable energies in the name of the "energy transition" is the alternative most adopted by many countries. Renewable energies, in particular photovoltaic solar (PV) energy, have thus become innovative and competitive sectors in full expansion. In this context, it is therefore necessary to ensure that new PV technologies, which are complex and the result of several manufacturing stages, meet the criteria of a product with low environmental impact, referred here as eco-designed.The state of the art on eco-design shows that the consideration of environmental constraints in R&D projects with low TRL "Technology Readiness Level" is still an emerging phenomenon, for two main reasons. On the one hand, environmental impact assessment is relatively complex for a non-mature technology under development (TRL low) because its characteristics and manufacturing processes are not yet fully defined. On the other hand, the identified tools in the literature have several limitations that impede their appropriation in R&D organizations.This research work therefore aims to develop a methodology to enable the sustainable integration of eco-design into R&D organizations, supporting their industrial partners in innovation and competitiveness. Thus, the developed method is based on the estimation of the evolution rate of technical, economic and environmental criteria of a new technology (low TRL) through a specific database of reference. The construction of the database relies on Life Cycle Assessment (LCA), used as a management tool to provide reliable results, despite the low TRL level.To integrate this approach into R&D organizations in a sustainable way, the method developed was implemented in a software "ECO PV" dedicated to crystalline silicon PV systems, which represent more than 94% of the current PV market today. Based on the principle of democratization of environmental knowledge and capitalization of information, this tool is accessible not only to LCA experts but also to all engineers in the PV field.Finally, this research work enabled to generate reliable, simple and quantified results and to develop an eco-design methodology to guide the technological choices of projects in the upstream phases of R&D, in order to develop PV systems more environmentally friendly

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Khodadadian, Sharifabad Mehrdad [Verfasser]. "Einsatz von equinem Choriongonadotropin (eCG) beim Rind post partum zur Förderung der Ovaraktivität / Mehrdad Khodadadian Sharifabad." Gießen : Universitätsbibliothek, 2017. http://d-nb.info/1123931291/34.

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Книги з теми "D-ECG"

1945-, Leonard Charles, ed. European R & D partnerships: How to win EC contracts. Coventry: Coventry University Enterprises, 1994.

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Great Britain. Department of Trade and Industry. EC R&D: A guide to European Community research & development programmes. London]: [DTI], 1994.

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Great Britain. Department of Trade and Industry. EC r&d: A guide to European Community research and development programmes. London: Department of Trade & Industry, 1994.

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U.S.-Japan R & D Management Forum (1990 Washington, D.C.). A study team for exchanging view on cases and experiences in R&D management among Japan, the United States, and Europe: U.S.-Japan R & D Management Forum at Washington, D.C, U.S.A., EC-Japan R & D Management Forum at Paris, France : summary report, 1990. [Alexandria, VA?]: Japan Productivity Center, 1990.

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Nominations of Deanna Tanner Okun, Richard T. Morrison, David D. Gustafson, Elizabeth Crewson Paris, Eric M. Thorson, and Edwin Eck: Hearing before the Committee on Finance, United States Senate, One Hundred Tenth Congress, second session, on the nominations of Deanna Tanner Okun, to be Deputy U.S. Trade Representative, Executive Office of the President; Richard T. Morrison, David D. Gustafson, and Elizabeth Crewson Paris, to be judges on the U.S. Tax Court; Eric M. Thorson, to be Inspector General, U.S. Department of the Treasury, and Edwin Eck, to be a member of the Internal Revenue Service Oversight Board, U.S. Department of the Treasury, April 17, 2008. Washington: U.S. G.P.O., 2008.

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Nelson, Taylor. SY100EL52 - 5V ECL Differential Data and Clock d Flip-Flop. Microchip Technology Incorporated, 2018.

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Laroe, Ross M., and John Charles Pool. Como Comprender Los Conceptos Basicos D/L EC. Grupo Editorial Norma, 1997.

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Dun & Bradstreet., ed. D&B business register.: WC, EC, E, N. High Wycombe: Dun & Bradstreet, 1996.

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Collection of Consolidated Texts - 394 D 0269: 94/269/EC. European Communities / Union (EUR-OP/OOPEC/OPOCE), 1997.

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Building with Europe: Construction industry guide to EC R &D. Watford: Construction Research Communications, 1995.

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Частини книг з теми "D-ECG"

Ferretti, Jacopo, Vincenzo Randazzo, Giansalvo Cirrincione, and Eros Pasero. "1-D Convolutional Neural Network for ECG Arrhythmia Classification." In Progresses in Artificial Intelligence and Neural Systems, 269–79. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5093-5_25.

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He, Jinyuan, Jia Rong, Le Sun, Hua Wang, Yanchun Zhang, and Jiangang Ma. "D-ECG: A Dynamic Framework for Cardiac Arrhythmia Detection from IoT-Based ECGs." In Web Information Systems Engineering – WISE 2018, 85–99. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02925-8_6.

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El Bouny, Lahcen, Mohammed Khalil, and Abdellah Adib. "ECG Heartbeats Classification Based on 1-D Convolutional Neural Networks." In Advanced Intelligent Systems for Sustainable Development (AI2SD’2020), 697–708. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90633-7_58.

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Mourad, Talbi. "ECG Denoising Based on 1-D Double-Density Complex DWT and SBWT." In Signals and Communication Technology, 31–50. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93405-7_2.

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Ginzton, Leonard E., and Michael M. Laks. "Computer Aided ECG Interpretation." In M. D. Computing: Benchmark Papers, 46–53. New York, NY: Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4612-4710-4_6.

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Mark, Roger G., and Kenneth L. Ripley. "Ambulatory ECG Monitoring: Real-Time Analysis Versus Tape Scanning Systems." In M. D. Computing: Benchmark Papers, 55–67. New York, NY: Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4612-4710-4_7.

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Zhang, Shuo, Qianfang Sun, Lingfeng Yao, Aoyu Zhang, and Renmin Zhang. "Feature Detection Algorithm Combined with Machine Learning Applied to Abnormal ECG Diagnosis System." In Proceedings of the World Conference on Intelligent and 3-D Technologies (WCI3DT 2022), 207–16. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-7184-6_17.

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Rigillo, Marina. "Hybridizing Artifice and Nature: Designing New Soils Through the Eco-Systemic Approach." In Regenerative Territories, 281–95. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-78536-9_18.

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AbstractThe chapter outlines the cultural background for applying design strategies consistent with the challenge of circularity. The contribution focuses on ecological thinking as an effective design approach to produce and implement eco-innovative strategies able at facing environmental and societal challenges of our global age. Then the chapter depicts the Repair research experience in promoting a systemic design approach for recycling and reusing C&D waste as new, anthropogenic soils in peri-urban areas. According to the EEA Report n.6/2017, the chapter posits that the major environmental challenges of the present are not about single issues, such as waste reduction or soil-loss, rather they involve systemic change and design processes, linking together economy, social habits and technological responses. Therefore, the transition towards more sustainable urban metabolism deeply depends from creative visions by which breaking the circuit “take-make-dispose” and promote new—and somehow tentative—visions for implementing circularity at local and global scale. Further postulation in the paper is about assuming the concept of Anthropocene as theoretical ground for such eco-innovative design approach. The scientific evidence of living in human-dominated ecosystems makes designers towards a paradigm shift concerning the overcoming of the typical artificial/natural dichotomy by exploring the augmented opportunities in designing sustainable and resilient habitats thanks to a more collaborative, plural and innovative design approach: “What is important and significant here is how ecology and landscape architectural design might invent alternative forms of relationships between people, places and cosmos” (Corner, ‘Ecology and Landscape as agents of Creativity’, 1997, reprint in Reed &Lister (2018), Op. Cit., pp. 40–65, p. 42). Starting from these assumptions, the paper deepens the experience of collaborative design for implementing recycle and reuse of C&D waste for producing new technical soils, according to both the regulatory constraints (and potentials) and the site-specific features. The research goal is to provide new vegetated soils by waste thanks to an innovative design process based on both circular economy principles and collaborative knowledge production. Notably, the capacity of producing creative hybridization between biotic and abiotic component seems to be the new frontier in the field of technological design and material engineering. The term hypernatural, proposed by Blaine Brownell and Marc Swackhamer in 2015, introduces the idea of a co-evolutionary process between nature and science, looking at humans’ technological capacity as an effective opportunity for creating the conditions for making biotic ad abiotic systems working together: “The ultimate aim of technology is not antinatural: it is hypernatural” (Brownell & Swackhamer in Hyper-natural. Architecture’s new relationship with nature. Princeton Architectural Press, New York, p. 18, 2015). The chapter deals with the methodology applied for promoting a sort of protocological architecture (Burke, 2007), by which facilitating the C&D waste recycle and reuse within the construction sector, and notably into the landscape project. The research starts working under the H2020-Repair project, and it has developed within further research programs about C&D waste management in urban regeneration programs developed by the Department of Architecture of University of Naples Federico II.

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Teng, P. S., M. Hossain, and K. S. Fischer. "Developing an R & D model for the humid tropical eco-region in Asia." In Systems Approaches for Sustainable Agricultural Development, 305–30. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0121-9_16.

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Alcidi, Cinzia, Francesco Corti, Daniel Gros, and Alessandro Liscai. "13. Towards a Socially Just Green Transition." In Greening Europe, 187–200. Cambridge, UK: Open Book Publishers, 2022. http://dx.doi.org/10.11647/obp.0328.13.

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Chapter 13 by C. Alcidi, F. Corti, D. Gros, and A. Liscai builds on the issue that finding a balance between the objectives of economic growth, environmental sustainability and social fairness has been one of the key priorities of the EU agenda in the last years. While the link between economic growth and social and ecological objectives has historically received much attention, the socio-environmental nexus has received much less. Some scholars recently attempted to identify the possible functions that the welfare state could perform to accompany the green transition. Based on this recent literature, the authors identify two main functions (activating and buffering) that are not mutually exclusive. An important distinction is made in the logic under which the welfare intervention is carried out. Two different types of logic can underpin eco-social policies: compensatory or integrated. They show that an integrated approach to social and environmental policies seems to be the most suitable solution to achieve green and positive social outcomes.

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Тези доповідей конференцій з теми "D-ECG"

Kanhe, R. K., and S. T. Hamde. "ECG signal compression using 2-D DWT Hermite coefficients." In 2016 International Conference on Signal and Information Processing (IConSIP). IEEE, 2016. http://dx.doi.org/10.1109/iconsip.2016.7857465.

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Zhelong Wang, Pengfu Zhu, and Ying Chen. "A 2-D ECG compression algorithm based on modified SPIHT." In 2008 5th International Summer School and Symposium on Medical Devices and Biosensors. IEEE, 2008. http://dx.doi.org/10.1109/issmdbs.2008.4575080.

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Yining Hu, Lizhe Xie, J. C. Nunes, J. J. Bellanger, M. Bedossa, and C. Toumoulin. "ECG gated tomographic reconstruction for 3-D rotational coronary angiography." In 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010). IEEE, 2010. http://dx.doi.org/10.1109/iembs.2010.5627449.

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Matheus, Justo, Maja Ignova, and Darwin Amaya. "A Medical-Inspired Framework to Classify Downhole Shocks Waveforms While Drilling." In SPE/IADC International Drilling Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/204098-ms.

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Abstract This paper presents a medical approach to classify shock waveforms acquired at 31,250 hertz downhole. The shock signals are treated as drilling electrocardiogram (D-ECG). The D-ECGs are processed using clustering algorithms and merged with drilling incidents to identify an arrhythmic signature pattern that can lead to catastrophic failures. In medicine, the analysis of heartbeat cycles in an electrocardiogram signal is very important for monitoring heart patients. In the drilling industry, downhole shocks are present most of the time. They are present so often that the authors introduce the concept of drilling electrocardiogram (D-ECG) based on shock waveforms acquired at high frequency. The shock module was implemented in hardware using a field programmable gate array (FPGA) and run inside the control unit of an RSS to complement the navigation systems composed. The shock acquisition and processing are performed at 31,250 Hz, providing enough bandwidth to fully reconstruct high-frequency events. A novel methodology combining field incidents with machine learning clustering algorithms is proposed to identify arrhythmic shocks signatures and whirl and bit bounce in real time, preventing failures to the BHA.

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Hu Liang, Zhang Yanfang, He Lesheng, and Wang Weilian. "Non-amplifying ECG signal acquisition system based on Σ-Δ A/D." In Instruments (ICEMI). IEEE, 2011. http://dx.doi.org/10.1109/icemi.2011.6037865.

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Wasimuddin, Muhammad, Khaled Elleithy, Abdelshakour Abuzneid, Miad Faezipour, and Omar Abuzaghleh. "ECG Signal Analysis Using 2-D Image Classification with Convolutional Neural Network." In 2019 International Conference on Computational Science and Computational Intelligence (CSCI). IEEE, 2019. http://dx.doi.org/10.1109/csci49370.2019.00180.

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Xu, Gaowei, Lingyun Zeng, Yao Zou, Jun Han, and Xiaoyang Zeng. "A 12.9-µW 2-D ECG compression core based on NLSPIHT." In 2014 IEEE 12th International Conference on Solid -State and Integrated Circuit Technology (ICSICT). IEEE, 2014. http://dx.doi.org/10.1109/icsict.2014.7021504.

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Nayebi, Somayeh, Mohammad Hosein Miranbeigi, and Ali Motie Nasrabadi. "An improved method for 2-D ECG compression based on SPIHT algorithm." In 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2008. http://dx.doi.org/10.1109/iembs.2008.4649822.

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Mian Qaisar, Saeed, Manel Ben-Romdhane, Omar Anwar, Mariam Tlili, Asma Maalej, Francois Rivet, Chiheb Rebai, and Dominique Dallet. "Time-domain characterization of a wireless ECG system event driven A/D converter." In 2017 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2017. http://dx.doi.org/10.1109/i2mtc.2017.7969682.

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Sahraeian, S. M. E., and E. Fatemizadeh. "Wavelet-Based 2-D ECG Data Compression Method Using SPIHT and VQ Coding." In EUROCON 2007 - The International Conference on "Computer as a Tool". IEEE, 2007. http://dx.doi.org/10.1109/eurcon.2007.4400442.

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Звіти організацій з теми "D-ECG"

Lohr, J., D. Ponce, R. W. Callis, J. L. Doane, H. Ikezi, and C. P. Moeller. Recent developments on the high power ECH installation at the DIII-D tokamak. Office of Scientific and Technical Information (OSTI), September 1998. http://dx.doi.org/10.2172/296750.

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Kuo-Petravic, G. 2-D time evolution of T/sub e/ during sawtooth crash based on fast ECE (electron cyclotron emission) measurements on TFTR. Office of Scientific and Technical Information (OSTI), December 1988. http://dx.doi.org/10.2172/6526244.

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Barash, Itamar, J. Mina Bissell, Alexander Faerman, and Moshe Shani. Modification of Milk Composition via Transgenesis: The Role of the Extracellular Matrix in Regulating Transgene Expression. United States Department of Agriculture, July 1995. http://dx.doi.org/10.32747/1995.7570558.bard.

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Altering milk composition via transgenesis depends on three main factors. (1) The availability of an efficient regulatory sequences for targeting transgene(s) to the mammary gland; (2) a reliable in vitro model to test the expression of transgenes prior to their introduction to the animal genome; and (3) better understanding of the major factors which determine the rate of gene expression and protein synthesis. The current studies provide the necessary means and knowledge to alter milk protein composition via transgenesis. The following specific goals were achieved: a: Identifying regulatory regions in the b-lactoglobulin (BLG) gene and the cross-talk between elements which enabled us to construct an efficient vector for the expression of desirable cDNA's in the mammary gland. b: The establishment of a sheep mammary cell line that serves as a model for the analysis of endogenous and exogenous milk protein synthesis in the mammary gland of livestock. c: An accurate comparison of the potency of the 5' regulatory sequences from the BLG and whey acidic protein (WAP) promoters in directing the expression of human serum albumin (HSA) to the mammary gland in vitro and in vivo. In this study we have also shown that sequences within the coding region may determine a specific pattern of expression for the transgene, distinct from that of the native milk protein genes. d: Characterizing the dominant role of ECM in transgene expression in mammary epithelial cells. e: Further characterization of the BCE-1 enhancer element in the promoter of the b-casein gene as a binding site for the c/EBP-b and Stat5. Identifying its interaction with chromatin and its up regulation by inhibitors of histone deacetylation. f: Identifying a mechanism of translational control as a mediator for the synergistic effect of insulin and prolactin on protein synthesis in the mammary gland.

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NUMERICAL STUDY ON SHEAR BEHAVIOUR OF ENHANCED C-CHANNELS IN STEEL-UHPC-STEEL SANDWICH STRUCTURES. The Hong Kong Institute of Steel Construction, September 2021. http://dx.doi.org/10.18057/ijasc.2021.17.3.4.

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This paper firstly developed a three-dimensional (3D) finite element model (FEM) for enhanced C-channels (ECs) in steel-UHPC-steel sandwich structures (SUSSSs). The FEM was validated by 12 push-out tests on ECs with UHPC. With the validated FEM, this paper performed in-depth parametric studies on shear behaviours of ECs with ultra-high performance concrete (UHPC). These investigated parameters included bolt-hole gap (a), grade (M) and diameter (d) of bolt, core strength (fc), length of C-channel (Lc), and prestressing force ratio on bolt (ρ) in ECs. Under shear forces, the ECs in UHPC exhibited successive fractures of bolts and C-channels. Increasing the bolt-hole gap within 0-2 mm has no harm on the ultimate shear resistance, but greatly improves the slip capacity of ECs. Increasing grade and diameter of bolts improves the shear resistance and ductility of ECs through increasing the PB/PC (shear strength of bolt to that of C-channel) ratio. Increasing the core strength increased the shear resistance, but reduced the ductility of ECs due to the reduced PB/PC ratio. The ECs with Lc value of 50 mm offer the best ductility. Prestressing force acting on the bolts reduced the shear strength and ductility of ECs with UHPC. Analytical models were proposed to estimate the ultimate shear resistance and shear-slip behaviours of ECs with UHPC. The extensive validations of these models against 12 tests and 31 FEM analysis cases proved their reasonable evaluations on shear behaviours of ECs with UHPC.

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