Energy Consumption, Economic Growth, and Environmental Degradation in OECD Countries

The world is governed by the issues of environmental degradation, climate control, pollutant emissions and other such phenomena due to the increasing dilapidation of environmental resources. For a while now, the focus has been on the production of green technologies, clean energy solutions and the development of a sustainable module that will aid in the restoration and protection of the environment. In this scenario, the dependence on consumption patterns of energy, economic growth (EG), and environmental degradation (ED) have become the focus of many researchers and policymakers. The Organization for Economic Co-operation and Development (OECD) countries are understandably characterized as the fastest developing nations of the world. However, literature evaluating the influence of energy consumption (EC) and economic growth (EG) on environmental degradation has presented conflicting results. This study aims to solve this conflict by presenting a panel dataset comprised of 35 OECD between 2000–2014. The Generalized Method of Moments Panel Vector Autoregression (GMM-PVAR) has been used to estimate the impact and causal relationship between the variables. The results of the study indicate that EG and consumption patterns of energy are vital for the improvement of the environmental performance of the firms. In contrast to other empirical literature, this study finds that the economic development of the country or countries and the patterns of consumption have started to coagulate with set environmental performance parameters. Environmental policies, consumption patterns and plans for EG are all being aligned in OECD countries. The results of this study are robust, as different methods for the evaluation have been used

Characteristics of vertical velocities estimated from drop size and fall velocity spectra of a Parsivel disdrometer

Vertical air velocities were estimated from drop size and fall velocity spectra observed by Parsivel disdrometers during intensive field observations from 13 June to 3 August 2016 around Mt. Jiri (1915ma.s.l.) in the southern Korean Peninsula. Rainfall and wind velocity data measured by Parsivel disdrometers and ultrasonic anemometers, respectively, were analyzed for an orographic rainfall event associated with a stationary front over Mt. Jiri on 1 July 2016. In this study, a new technique was developed to estimate vertical air velocities from drop size and fall velocity spectra measured by the Parsivel disdrometers and investigate characteristics of up-/downdrafts and related microphysics on the windward and leeward sides of the mountain. To validate results from this technique, vertical air velocities between the Parsivel disdrometers and anemometers were compared at different locations and were shown in quite good agreement with each other. It was shown that upward motion was relatively more dominant on the windward side and even during periods of heavy rainfall. In contrast, downward motion was more dominant on the leeward side during nearly the same periods of heavy rainfall. Occurrences of upward and downward motion were digitized as percentage values as they are divided by a total count of occurrences during the entire period. On the windward (leeward) side, the percentages of upward (downward) motion were much larger than those of downward (upward) motion. The mean rainfall intensity on the leeward side was stronger than on the windward side, suggesting that most of the rainfall on the leeward side was relatively more affected by the downward motion. With the estimated vertical air velocities, histogram characteristics of rainfall parameters were also examined between the windward and leeward sides

Calibration-Free Driver Drowsiness Classification based on Manifold-Level Augmentation

Drowsiness reduces concentration and increases response time, which causes fatal road accidents. Monitoring drivers' drowsiness levels by electroencephalogram (EEG) and taking action may prevent road accidents. EEG signals effectively monitor the driver's mental state as they can monitor brain dynamics. However, calibration is required in advance because EEG signals vary between and within subjects. Because of the inconvenience, calibration has reduced the accessibility of the brain-computer interface (BCI). Developing a generalized classification model is similar to domain generalization, which overcomes the domain shift problem. Especially data augmentation is frequently used. This paper proposes a calibration-free framework for driver drowsiness state classification using manifold-level augmentation. This framework increases the diversity of source domains by utilizing features. We experimented with various augmentation methods to improve the generalization performance. Based on the results of the experiments, we found that deeper models with smaller kernel sizes improved generalizability. In addition, applying an augmentation at the manifold-level resulted in an outstanding improvement. The framework demonstrated the capability for calibration-free BCI.Comment: Submitted to 2023 11th IEEE International Winter Conference on Brain-Computer Interfac

Study on Poisson Cluster Stochastic Rainfall Generators

The purpose of this dissertation is to enhance the applicability and the accuracy of the Poisson cluster stochastic rainfall generators. Firstly, the 6 parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall simulation model were regionalized across the contiguous United States. Each of the parameters of MBLRP model estimated at 3,444 National Climate Data Center (NCDC) rain gages was spatially interpolated based on the Ordinary Kriging technique to produce the parameter surface map for each of the 12 months of the year. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the statistics of the observed rainfall for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The estimated parameter values were also used to produce the maps of storm and rain cell characteristics. Secondly, the relative importance of the rainfall statistics in the generation of watershed response characteristics was estimated based on regression analyses using the rainfall time series observed at 1099 NCDC rain gages. The result of the analyses was used to weigh the rainfall statistics differently in the parameter calibration process of MBLRP model. It was observed that synthetic rainfall time series generated weighing the precipitation statistics according to their relative importance outperformed those generated weighing all statistics equally in predicting watershed runoff depths and peak flows. When all statistics were given the same weight, runoff depths and peak flows were underestimated by 20 percent and 14 percent, respectively; while, when the statistics were weighed proportionally to their relative importance, the underestimation was reduced to 4 percent and 3 percent, which confirms the advantage of weighing the statistics differently. In general, the value of the weights depends on the hydrologic process being modeled. Lastly, a stochastic rainfall generation model that can integrate year-to-year variability of rainfall statistics is suggested. The new framework consists of two parts. The first part generates the short-term rainfall statistics based on the correlation between the observed rainfall statistics. The second part generates the rainfall time series using the modified Bartlett-Lewis rectangular pulse model based on the simulated rainfall statistics. The new approach was validated at 104 NCDC gages across the United States in its ability to reproduce rainfall and watershed response characteristics. The result indicates that the new framework outperformed the traditional approach in reproducing the distribution of monthly maximum rainfall depths, monthly runoff volumes and monthly peak flows

Wireless sEMG System with a Microneedle-Based High-Density Electrode Array on a Flexible Substrate

Surface electromyography (sEMG) signals reflect muscle contraction and hence, can provide information regarding a user's movement intention. High-density sEMG systems have been proposed to measure muscle activity in small areas and to estimate complex motion using spatial patterns. However, conventional systems based on wet electrodes have several limitations. For example, the electrolyte enclosed in wet electrodes restricts spatial resolution, and these conventional bulky systems limit natural movements. In this paper, a microneedle-based high-density electrode array on a circuit integrated flexible substrate for sEMG is proposed. Microneedles allow for high spatial resolution without requiring conductive substances, and flexible substrates guarantee stable skin-electrode contact. Moreover, a compact signal processing system is integrated with the electrode array. Therefore, sEMG measurements are comfortable to the user and do not interfere with the movement. The system performance was demonstrated by testing its operation and estimating motion using a Gaussian mixture model-based, simplified 2D spatial pattern.111Ysciescopu

Improving Generalization of Drowsiness State Classification by Domain-Specific Normalization

Abnormal driver states, particularly have been major concerns for road safety, emphasizing the importance of accurate drowsiness detection to prevent accidents. Electroencephalogram (EEG) signals are recognized for their effectiveness in monitoring a driver's mental state by monitoring brain activities. However, the challenge lies in the requirement for prior calibration due to the variation of EEG signals among and within individuals. The necessity of calibration has made the brain-computer interface (BCI) less accessible. We propose a practical generalized framework for classifying driver drowsiness states to improve accessibility and convenience. We separate the normalization process for each driver, treating them as individual domains. The goal of developing a general model is similar to that of domain generalization. The framework considers the statistics of each domain separately since they vary among domains. We experimented with various normalization methods to enhance the ability to generalize across subjects, i.e. the model's generalization performance of unseen domains. The experiments showed that applying individual domain-specific normalization yielded an outstanding improvement in generalizability. Furthermore, our framework demonstrates the potential and accessibility by removing the need for calibration in BCI applications.Comment: Submitted to 2024 12th IEEE International Winter Conference on Brain-Computer Interfac

Comparison of total body irradiation-based or non-total body irradiation-based conditioning regimens for allogeneic stem cell transplantation in pediatric leukemia patients

Purpose : This study aims to compare the outcome of total body irradiation (TBI)- or non-TBI-containing conditioning regimens for leukemia in children. Methods : We retrospectively evaluated 77 children conditioned with TBI (n=40) or non-TBI (n=37) regimens, transplanted at Chonnam National University Hospital between January 1996 and December 2007. The type of transplantation, disease status at the time of transplant, conditioning regimen, engraftment kinetics, development of graft-versus-host disease (GVHD), complications, cause of deaths, overall survival (OS), and event-free survival (EFS) were compared between the 2 groups. Results : Among 34 patients with acute lymphoblastic leukemia (ALL), 28 (82.4%) were in the TBI group, while 72.7% (24/33) of patients with myeloid leukemia were in the non-TBI group. Although the 5-year EFS of the 2 groups was similar for all patients (62% vs 63%), the TBI group showed a better 5-year EFS than the non-TBI group when only ALL patients were analyzed (65% vs 17%&#59; P =0.005). In acute myelogenous leukemia patients, the non-TBI group had better survival tendency (73% vs 38%&#59; P=0.089). The incidence of GVHD, engraftment, survival, cause of death, and late complications was not different between the 2 groups. Conclusion : The TBI and non-TBI groups showed comparable results, but the TBI group showed a significantly higher 5-year EFS than the non-TBI group in ALL patients. Further prospective, randomized controlled studies involving larger number of patients are needed to assess the late-onset complications and to compare the socioeconomic quality of life