The Effects of Nitrogen and Oxygen Atmosphere on the Photoconductivity of Trimethyl Phenyl Diamine Thin Films

Organic materials were previously used as insulators in electrical technology. These materials, however, are currently used as conductors once their photoconductivity is confirmed and studied. From the literature, it has shown that the photoconductivity of trimethyl phenyl diamine (TPD) increases in the air and decreased in the atmosphere of the vacuum. To the best of our knowledge, there is no detailed study of the effects of gas in the air that affect TPD photoconductivity. In this study we investigate the effects of nitrogen (N2) and oxygen (O2) gases on photoconductivity, degradation and residual decay of photoconductivity for thin film TPD. The results of the study show that in the atmosphere of O2, TPD produces about seven times higher photoconductivity compared to N2 conditions. It also shows that, N2 and O2 provide more effective response time during photoconductivity residual decay. Photoconductivity degradation occurs in all conditions and its recovery takes more than 65 hours

Evaluation of patient electrocardiogram datasets using signal quality indexing

Electrocardiogram (ECG) is widely used in the hospital emergency rooms for detecting vital signs, such as heart rate variability and respiratory rate. However, the quality of the ECGs is inconsistent. ECG signals lose information because of noise resulting from motion artifacts. To obtain an accurate information from ECG, signal quality indexing (SQI) is used where acceptable thresholds are set in order to select or eliminate the signals for the subsequent information extraction process. A good evaluation of SQI depends on the R-peak detection quality. Nevertheless, most R-peak detectors in the literature are prone to noise. This paper assessed and compared five peak detectors from different resources. The two best peak detectors were further tested using MIT-BIH arrhythmia database and then used for SQI evaluation. These peak detectors robustly detected the R-peak for signals that include noise. Finally, the overall SQI of three patient datasets, namely, Fantasia, CapnoBase, and MIMIC-II, was conducted by providing the interquartile range (IQR) and median SQI of the signals as the outputs. The evaluation results revealed that the R-peak detectors developed by Clifford and Behar showed accuracies of 98% and 97%, respectively. By introducing SQI and choosing only high-quality ECG signals, more accurate vital sign information will be achieved

Development of Respiratory Rate Estimation Technique Using Electrocardiogram and Photoplethysmogram for Continuous Health Monitoring

Abnormal vital signs often predict a serious condition of acutely ill hospital patients in 24 hours. The notable fluctuations of respiratory rate (RR) are highly predictive of deteriorations among the vital signs measured. Traditional methods of detecting RR are performed by directly measuring the air flow in or out of the lungs or indirectly measuring the changes of the chest volume. These methods require the use of cumbersome devices, which may interfere with natural breathing, are uncomfortable, have frequently moving artifacts, and are extremely expensive. This study aims to estimate the RR from electrocardiogram (ECG) and photoplethysmogram (PPG) signals, which consist of passive and non-invasive acquisition modules. Algorithms have been validated by using PhysioNet’s Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II)’s patient datasets. RR estimation provides the value of mean absolute error (MAE) for ECG as 1.25 bpm (MIMIC-II) and 1.05 bpm for the acquired data. MAE for PPG is 1.15 bpm (MIMIC-II) and 0.90 bpm for the acquired data. By using 1-minute windows, this method reveals that the filtering method efficiently extracted respiratory information from the ECG and PPG signals. Smaller MAE for PPG signals results from fewer artifacts due to easy sensor attachment for the PPG because PPG recording requires only one-finger pulse oximeter sensor placement. However, ECG recording requires at least three electrode placements at three positions on the subject’s body surface for a single lead (lead II), thereby increasing the artifacts. A reliable technique has been proposed for RR estimation

COVID-19 Prediction With Machine Learning Technique From Extracted Features of Photoplethysmogram Morphology

At present, COVID-19 is spreading widely around the world. It causes many health problems, namely, respiratory failure and acute respiratory distress syndrome. Wearable devices have gained popularity by allowing remote COVID-19 detection, contact tracing, and monitoring. In this study, the correlation of photoplethysmogram (PPG) morphology between patients with COVID-19 infection and healthy subjects was investigated. Then, machine learning was used to classify the extracted features between 43 cases and 43 control subjects. The PPG data were collected from 86 subjects based on inclusion and exclusion criteria. The systolic-onset amplitude was 3.72% higher for the case group. However, the time interval of systolic-systolic was 7.69% shorter in the case than in control subjects. In addition, 12 out of 20 features exhibited a significant difference. The top three features included dicrotic-systolic time interval, onset-dicrotic amplitude, and systolic-onset time interval. Nine features extracted by heatmap based on the correlation matrix were fed to discriminant analysis, k-nearest neighbor, decision tree, support vector machine, and artificial neural network (ANN). The ANN showed the best performance with 95.45% accuracy, 100% sensitivity, and 90.91% specificity by using six input features. In this study, a COVID-19 prediction model was developed using multiple PPG features extracted using a low-cost pulse oximeter

Methods of Extracting Feature from Photoplethysmogram Waveform for Non-Invasive Diagnostic Applications

This paper presents a bibliographical survey of recently-published research on different techniques to extract feature from photoplethysmogram (PPG). These techniques and approaches have been implemented for better accuracy in detecting diseases. Moreover, several aspects in analyzing PPG waveform are discussed on the techniques in feature extraction, parameters involved and performance comparisons. This review will serve as a comparative study and reference for researches working on PPG waveform in health care applications

Methods of Extracting Feature from Photoplethysmogram Waveform for Non-Invasive Diagnostic Applications

This paper presents a bibliographical survey of recently-published research on different techniques to extract feature from photoplethysmogram (PPG). These techniques and approaches have been implemented for better accuracy in detecting diseases. Moreover, several aspects in analyzing PPG waveform are discussed on the techniques in feature extraction, parameters involved and performance comparisons. This review will serve as a comparative study and reference for researches working on PPG waveform in health care applications.</p

Thin and Rectangular Die Bond Pick-Up Mechanism to Reduce Cracking During the Integrated Circuit Assembly Process

The demand for small, thin, and lightweight electronic devices is increasing. More advanced design and assembly processes of electronic packaging technology have developed to fulfill this need. The critical processes in semiconductor packaging involved in meeting the ever increasing demands of technology include wafer back grinding, dicing, and die attachment. With low die thickness, the risk of die failure, which can cause functional damage, is high. In the die attachment process, the pin ejector causes an impact during the pick and place process. Those effects can result in a micro indentation or micro crack under the die and would be the weak point throughout the entire process. This study designed and evaluated an ejector system for the die attachment process. The proposed method uses a static pole heated inside the cavity for the platform to die before being ejected. Vacuum stabilizes the die suction. Moreover, heat softens the sawing tape and weakens the die adhesion. For die selection during the die attachment process, the results show that the critical die crack problem for a thin and rectangular die is solved using the proposed method. In summary, the packaging of semiconductors has advanced to accommodate the pick-up technology solution in relation to the challenging material needed for the current miniaturization market trend and demand

Ejectorless Method for Die Attach Pick Up for Cracking Improvement on Thin High-Aspect Ratio Die

The demand for producing small, thin, and light electronic devices is increasing. As a result, the design and assembly of electronic packaging technology have been developed. To meet the ever-increasing technology requirements, the critical process in the semiconductor packaging include wafer back grinding, sawing, and die attach. Given that the die thickness is lower than the previous ones, the risk of die cracking failures, which can lead to device malfunction, becomes high. In the die attach process, the ejector pin has an effect during the pick and place processes. Such impact may result in microdented mark or microcrack underneath the die, which becomes the weakened point throughout the entire process. In this study, an ejectorless system for the die pick and place during the die attach process has been designed and evaluated. The methodology of using ejector pin is replaced by heated static pillar inside cavity for die platform before being picked up. Vacuum is used to stabilize the die, and heat is applied to soften the sawing tape and weaken the adhesion of the die to the sawing tape. Results show that the critical issues of die crack for thin high aspect ratio die are resolved by using the proposed method for the die pick during the die attach process. In conclusion, the semiconductor packaging advances the pick-up technology solution for the challenging material, which is needed for the current miniaturization market trend and demand

Ejectorless Method for Die Attach Pick Up for Cracking Improvement on Thin High-Aspect Ratio Die

The demand for producing small, thin, and light electronic devices is increasing. As a result, the design and assembly of electronic packaging technology have been developed. To meet the ever-increasing technology requirements, the critical process in the semiconductor packaging include wafer back grinding, sawing, and die attach. Given that the die thickness is lower than the previous ones, the risk of die cracking failures, which can lead to device malfunction, becomes high. In the die attach process, the ejector pin has an effect during the pick and place processes. Such impact may result in microdented mark or microcrack underneath the die, which becomes the weakened point throughout the entire process. In this study, an ejectorless system for the die pick and place during the die attach process has been designed and evaluated. The methodology of using ejector pin is replaced by heated static pillar inside cavity for die platform before being picked up. Vacuum is used to stabilize the die, and heat is applied to soften the sawing tape and weaken the adhesion of the die to the sawing tape. Results show that the critical issues of die crack for thin high aspect ratio die are resolved by using the proposed method for the die pick during the die attach process. In conclusion, the semiconductor packaging advances the pick-up technology solution for the challenging material, which is needed for the current miniaturization market trend and demand. </p

Recent Advances in Nondestructive Method and Assessment of Corrosion Undercoating in Carbon&ndash;Steel Pipelines

Carbon&ndash;steel pipelines have mostly been utilized in the oil and gas (OG) industry owing to their strength and cost-effectiveness. However, the detection of corrosion under coating poses challenges for nondestructive (ND) pipeline monitoring techniques. One of the challenges is inaccessibility because of the pipeline structure, which leads to undetected corrosion, which possibly leads to catastrophic failure. The drawbacks of the existing ND methods for corrosion monitoring increase the need for novel frameworks in feature extraction, detection, and characterization of corrosion. This study begins with the explanations of the various types of corrosion in the carbon&ndash;steel pipeline in the OG industry and its prevention methods. A review of critical sensors integrated with various current ND corrosion monitoring systems is then presented. The importance of acoustic emission (AE) techniques over other ND methods is explained. AE data preprocessing methods are discussed. Several AE-based corrosion detection, prediction, and reliability assessment models for online pipeline condition monitoring are then highlighted. Finally, a discussion with future perspectives on corrosion monitoring followed by the significance and advantages of the emerging AE-based ND monitoring techniques is presented. The trends and identified issues are summarized with several recommendations for improvement in the OG industry