110 research outputs found
Parkinson’s Disease Diagnosis in Cepstral Domain Using MFCC and Dimensionality Reduction with SVM Classifier
Get PDFParkinson’s disease (PD) is one of the most common and serious neurological diseases. Impairments in voice have been reported to be the early biomarkers of the disease. Hence, development of PD diagnostic tool will help early diagnosis of the disease. Additionally, intelligent system developed for binary classification of PD and healthy controls can also be exploited in future as an instrument for prodromal diagnosis. Notably, patients with rapid eye movement (REM) sleep behaviour disorder (RBD) represent a good model as they develop PD with a high probability. It has been shown that slight speech and voice impairment may be a sensitive marker of preclinical PD. In this study, we propose PD detection by extracting cepstral features from the voice signals collected from people with PD and healthy subjects. To classify the extracted features, we propose to use dimensionality reduction through linear discriminant analysis and classification through support vector machine. In order to validate the effectiveness of the proposed method, we also developed ten different machine learning models. It was observed that the proposed method yield area under the curve (AUC) of 88%, sensitivity of 73.33%, and specificity of 84%. Moreover, the proposed intelligent system was simulated using publicly available multiple types of voice database. Additionally, the data were collected from patients under on-state. The obtained results on the public database are promising compared to the previously published work
Asset Securitization: A Solution of Non Performing Loans (NPLs) of Commercial Banks in Bangladesh
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The potential and environmental ramifications of palm biodiesel: Evidence from Malaysia
No full text© 2018 Malaysia finds itself in a unique position. The large flourishing palm oil industry could produce enough biodiesel to completely offset Malaysia's entire diesel consumption. Consequently, we employ a dynamic, partial equilibrium model of the Malaysian agricultural sector to predict whether palm biodiesel can offset diesel fuel. The model indicates palm biodiesel cannot compete with diesel's price because of the high cost of palm oil. Nevertheless, the government could subsidize biodiesel production at Malaysian Ringgit (RM) 1.09 per liter (or United States Dollar 0.28/liter) since biodiesel could help the government achieves its greenhouse gas (GHG) emission targets in the Paris Agreement. Furthermore, the government should implement two new regulations to boost the GHG efficiency of its agriculture. First, the palm oil mills should treat their palm oil mill effluents (POME) because POMEs emit methane, a potent GHG gas. Second, the government should prevent deforestation. The destruction of rainforests reduces the carbon storage because oil palm trees store half the carbon as pristine rainforests per hectare. Finally, palm biodiesel could lead to greater agricultural employment but induce higher agricultural prices, loss of export revenue, and rising imports
Do M&As impact firm carbon intensity?
Get PDFWe examine the impact of domestic and cross-border M&As on firm carbon intensity in a sample of firms from 84 countries over the period 2002-2020. We find that M&As only impact the firm-level carbon footprint in the short-term, where the impact is to raise it, but that there is no impact on the carbon footprint over the medium term. As such, the supposedly greater efficiency of acquirer firms does not appear to translate into innovations that reduce carbon intensity in either the acquirer or target firm. This result is robust to several tests, including controlling for the type of M&A (vertical or horizontal), the relative strengths of environmental regulation (as measured by environmental taxes) in acquirer and target firm country, and to alternative measures of firms’ carbon footprint. The results suggest that M&A activity does little to help achieve countries’ climate goals, which would be better achieved if regulators and other firm stakeholders require acquirer firms to make public the likely contribution to those goals of the M&A activity that they are proposing
Big Data Analytics And Predictive Analysis In Enhancing Customer Relationship Management (CRM): A Systematic Review Of Techniques
No full textFeasibility Analysis of AI based Wearable Data-driven Solution for Safety and Health in Sweden
No full textThis thesis investigates the prospects of AI and IoT based wearable solution in order to enhance the occupational safety and health. Thus this study contributes to find the probable use cases that can be suitable for such a technology. Later also investigation has been done to figure out how appropriate the Swedish market will be to target on. At the beginning of the thesis, it includes an overall scenario about the occupational safety/health globally as well as in Sweden. Later to improve the workplace injuries, how AI based wearable solution can be handy has been visualized. The theoretical framework explains the technical features and working mechanism and how it can implement in a real world. The methods that can be applied for such research has been discussed afterwards. Then investigation has been done to find the probable use cases and Swedish market has been analyzed to verify how fit the solution. The result chapter includes the finding of the analysis thereafter. To conclude, it has been figured out that few of the us cases for Swedish industries can certainly be applicable for such AI based wearable solution to improve the workplace safety scenario.Denna avhandling undersöker utsikterna för AI och IoT-baserad bärbar lösning för att förbättra arbetssäkerheten och hälsan. Således bidrar denna studie till att hitta de sannolika användningsfall som kan vara lämpliga för en sådan teknik. Senare har också undersökningar gjorts för att ta reda på hur lämpligt den svenska marknaden ska vara inriktad på. I början av avhandlingen ingår det ett övergripande scenario om arbetssäkerhet / hälsa globalt såväl som i Sverige. Senare för att förbättra arbetsplatsskadorna, hur AI-baserad bärbar lösning kan vara användbar har visualiserats. Den teoretiska ramen förklarar de tekniska funktionerna och arbetsmekanismen och hur den kan genomföras i en verklig värld. De metoder som kan tillämpas för sådan forskning har diskuterats efteråt. Sedan har undersökningen gjorts för att hitta de sannolika användningsfallen och den svenska marknaden har analyserats för att verifiera hur lämplig lösningen är. Resultatet kapitlet innehåller analysen av analysen därefter. Avslutningsvis har det visat sig att få av användningsärenden för svenska industrier säkert kan tillämpas för en sådan AI-baserad bärbar lösning för att förbättra arbetssäkerhetsscenariot
Development of a Fog Computing-Based Real-Time Flood Prediction and Early Warning System Using Machine Learning and Remote Sensing Data
No full textCapital and Liquidity Regulations, Resilience, and Bank Value
No full textIn the business arena, particularly in the field of corporate finance, the scope of valuation is highly significant. There are several value drivers for a firm. However, due to its nature of business, a bank's valuation is affected by several unique drivers including earnings diversification, risk capabilities, assets mix, and a lot of intangible factors. Since banking is a highly regulated sector, this chapter is designed to address the missing links between Basel capital and liquidity regulations, banking system resilience, and bank valuation
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