Making Free Trade Fair

Philosophers have done very little work on what makes trade fair. Perhaps the most extensive discussion is Malgorzata Kurjanska and Mathias Risse’s article, “Fairness in Trade II: export subsidies and the fair trade movement.”2 In their article, Kurjanska and Risse consider the case for trade subsidies and the Fair Trade movement. They suggest that it is not permissible for developed countries to give their producers subsidies because doing so does not strike an appropriate balance between meeting the needs of the global poor and protecting domestic workers (Kurjanska and Risse, 2008: 34). Kurjanska and Risse also argue that the case for Fair Trade hinges, primarily, on whether or not it is part of the best development strategy for poor countries. They do not think Fair Trade is part of the best development strategy and, so, they believe purchasing Fair Trade certified goods is only acceptable because doing so does not constitute a large share of the market in traded goods. This chapter argues that the case against subsidies and Fair Trade Kurjanska and Risse present is much weaker than they make out. To the contrary, it argues that giving some subsidies and purchasing some Fair Trade certified goods may even be necessary to make trade fair. Section 11.2 starts by saying a few words about the normative framework Kurjanska and Risse adopt

Development of a Spectral Feature Extraction using Enhanced MFCC for Respiratory Sound Analysis

Chronic illnesses such as respiratory diseases are among the most persistent health threats in our society nowadays. Fortunately, the emergence of state-of-the-art technologies like Internet of Things (IoT), Machine Learning, and Artificial Intelligence (AI) are available to make monitoring and pre-diagnosis of human health conditions fast and convenient. Nowadays, health services that are accurate, accessible, and convenient are amongst the in-demand in modern medical applications. In this study, an efficient design for a lung sound classifier is explored that utilizes enhanced-Mel frequency cepstral coefficients (eMFCC). Spectral feature extraction based on MFCC is implemented and optimized using MATLAB. MFCC parameters such as frame duration, frameshift, number of filterbank channels, number of cepstral coefficients, and the frequency range are included in this study. The enhanced MFCC feature vectors were extracted using a histogram and were subjected to different machine learning algorithms such as Support Vector Machine (SVM) and K-Nearest Neighbors (KNN). Results show the evaluation of the enhanced MFCC based on sensitivity, specificity, and overall accuracy is higher than the conventional MFCC

Performance Evaluation of an Intelligent Lung Sound Classifier Based on an Enhanced MFCC Model

The rate at which technology grew in the past years is unbelievably fast and astounding. However, chronic illnesses like respiratory diseases remains a common and widely experienced problem globally. The emergence of infectious respiratory health issues such as the coronavirus (COVID-19) had only made this enigma more harmful, causing an increase in the number of death due to respiratory illnesses. Hence, the development of modern and accurate methods to improve medical diagnosis is one of the simple step’s humans can perform to overcome such problems. In this study, the researchers proposed an enhanced model for lung sound classification using Mel Frequency Cepstral Coefficient (MFCC). The design will classify four different lung sounds, with data input taken and classified one at a time. The goal of which is to augment human intelligence and not to replace the existing lung sound classification methods. The pre-recorded lung sounds were characterized, and the researcher proposed four enhanced MFCC models with three varying designs. The data collected from feature extraction and data mining were evaluated by the machine learning algorithms Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). Measures like sensitivity, specificity, and accuracy were tested to determine which model was superior. Results showed that in terms of performance metrics, KNN performed better than SVM in classifying lung sounds. Tested in three designs where the pre-emphasis was removed, and the original 44.1kHz data resampled. Model 3 using KNN sampled at a frequency of 12000Hz has reached an average accuracy of 96.92% and a blind-data accuracy of 93.33%. A specificity of 97.94% and a sensitivity of 93.83%, achieving a performance that is comparable with existing studies on lung sound classification

Performance Evaluation of Markerless 3D Skeleton Pose Estimates with Pop Dance Motion Sequence

The evaluation of markerless pose estimation performed by OpenPose has been getting much attention from researchers of human movement studies. This work aims to evaluate and compare the output joint positions estimated by the OpenPose with a marker-based motion-capture data recorded on a pop dance motion. Although the marker-based motion capture can accurately measure and record the human joint positions, this particular set-up is expensive. The framework to compare the outputs of the markerless method to the ground truth marker-based joint remains unknown, especially for complex body motion. Synchronization, camera calibration, and 3D reconstruction by fusing the outputs of the markerless method (OpenPose) are discussed. In this case study, the comparison results illustrate that the mean absolute errors for each key points are less than 700 mm. Contribution: This work contributes for human movement science by evaluating the OpenPose markerless 3D reconstruction pose with the marker-based motion-capture data recorded on pop dance motion

Cotas tarifárias e o impacto sobre as exportações agrícolas brasileiras na União Européia

Este trabalho tem como objetivo avaliar os efeitos de cotas tarifárias adicionais para as exportações brasileiras de produtos agrícolas, com base na proposta européia de maio de 2004 no âmbito das negociações para um acordo de livre-comércio Mercosul- União Européia. A análise teórica do funcionamento dos três instrumentos da cota tarifária (seu volume e as tarifas intra e extracota) revela que, dependendo da demanda, apenas um deles efetivamente restringe as importações. Assim, a oferta de cotas adicionais não implica necessariamente um aumento equivalente na quantidade exportada. Na estimativa de ganho de receita deve ser considerada também a variação na renda da cota. Além disso, a administração da cota terá um papel crucial na alocação dessa renda. Caso seja o Mercosul a fazê-la, as estimativas indicam um aumento de US$728 milhões na receita de divisas, bastante próximo do valor da cota total oferecida a preços correntes, sendo US$ 252 milhões resultantes da apropriação das rendas das cotas e US$476 milhões do incremento nas exportações. Se o controle das cotas for realizado pela União Européia, o ganho do Brasil decorrerá exclusivamente do aumento das exportações, atingindo apenas 63,7$ 728 million in exports, of which US$525 million result from the appropriation of the quota rents and US$ 476 million from exports. The sum of both is indeed close to the value of the additional quotas at current prices. If the administration goes to the EU, the gains will derive exclusively from the expansion in exports, which corresponds to 63.7% to the value of the quota