title: Using classification to evaluate the output of confidence-based association rule mining

authors: Mutter, Stefan

subjects: computer science

abstract: Association rule mining is a data mining technique that reveals interesting relationships in a database. Existing approaches employ different parameters to search for interesting rules. This fact and the large number of rules make it difficult to compare the output of confidence-based association rule miners. This paper explores the use of classification performance as a metric for evaluating their output. Previous work on forming classifiers from association rules has focussed on accurate classification, whereas we concentrate on using the properties of the resulting classifiers as a basis for comparing confidence-based association rule learners. Therefore, we present experimental results on 12 UCI datasets showing that the quality of small rule sets generated by Apriori can be improved by using the predictive Apriori algorithm. We also show that CBA, the standard method for classification using association rules, is generally inferior to standard rule learners concerning both running time and size of rule sets.

text: Using classification to evaluate the output of confidence-based association rule mining Association rule mining is a data mining technique that reveals interesting relationships in a database. Existing approaches employ different parameters to search for interesting rules. This fact and the large number of rules make it difficult to compare the output of confidence-based association rule miners. This paper explores the use of classification performance as a metric for evaluating their output. Previous work on forming classifiers from association rules has focussed on accurate classification, whereas we concentrate on using the properties of the resulting classifiers as a basis for comparing confidence-based association rule learners. Therefore, we present experimental results on 12 UCI datasets showing that the quality of small rule sets generated by Apriori can be improved by using the predictive Apriori algorithm. We also show that CBA, the standard method for classification using association rules, is generally inferior to standard rule learners concerning both running time and size of rule sets.

year: 2005

title: The profitability of banking sectors in the Asia-Pacific region and their contributions to economic growth

authors: Kumar, Vijay

subjects: Non-performing loans

abstract: The banking sector plays an important role in national economies by directing funds from savers to investors who create additional wealth in the economy. Dietrich and Wanzenried (2011) argue that a country’s economic activities cannot run smoothly if its banking sector is not efficient. Athanasoglou, Brissimis, and Delis (2008) argue that a profitable banking sector is necessary to overcome economic shocks. 
This study focuses on ten countries in the Asia-Pacific region which are at different stages of economic development. These countries are of particular interest because of their institutional and regulatory characteristics. The banks in these countries are all subject to similar regulations. For example, they are required to maintain minimum capital adequacy ratios according to the Basel Accords. Furthermore, banks in most of the countries are required to maintain certain proportions of their deposits as cash reserves that cannot be lent out. Based on their stage of economic development, each of the ten countries is classified as belonging to one of three categories: small emerging economies, large emerging economies and developed economies.  
Our study focuses on two important aspects of the banking sector. First, we investigate the extent to which profitable banks make a positive contribution to economic growth. Second, we investigate the determinants of bank profitability. 
The first part of the thesis investigates the relationship between the profitability of banks and economic growth. In order to investigate this relationship, we use data from ten countries in the Asia-Pacific region for the period from 2004 to 2014. In order to address the research questions, we use different econometric techniques such as linear regressions, nonlinear regressions and Granger causality tests. Our results highlight that a profitable banking sector is an important contributor to economic growth. In contrast to our expectations, we find a negative relationship between the size of the banking sector and economic growth. Further, we find that the influence of bank profitability on economic growth decreases when the size of the banking sector increases. The results of our causality tests suggest that causality runs from bank profitability to economic growth but economic growth also has a delayed feedback on bank profitability. 
The second part of this thesis has four empirical chapters that focus on the factors influencing the profitability of banks. First, we investigate the determinants of the profitability of banks in all countries together. Second, we identify the factors influencing the profitability of Islamic and conventional banks in small emerging economies. Third, we investigate the factors affecting the profitability of banks in large emerging markets, and finally, we investigate the determinants of the profitability of banks in developed economies. We use annual data sets of banks for the period from 2004 to 2014 which was gathered from different sources. We use different econometric techniques such as linear regressions and Wald tests to address the research questions. Overall, our results suggest that credit quality, bank size, capital adequacy ratio and cost management are the key factors influencing the profitability of banks in the Asia-Pacific. Cost-efficient banks with superior credit quality are more profitable than their competitors. We find that the impacts of some of the variables vary across regions and countries.

text: The profitability of banking sectors in the Asia-Pacific region and their contributions to economic growth The banking sector plays an important role in national economies by directing funds from savers to investors who create additional wealth in the economy. Dietrich and Wanzenried (2011) argue that a country’s economic activities cannot run smoothly if its banking sector is not efficient. Athanasoglou, Brissimis, and Delis (2008) argue that a profitable banking sector is necessary to overcome economic shocks. 
This study focuses on ten countries in the Asia-Pacific region which are at different stages of economic development. These countries are of particular interest because of their institutional and regulatory characteristics. The banks in these countries are all subject to similar regulations. For example, they are required to maintain minimum capital adequacy ratios according to the Basel Accords. Furthermore, banks in most of the countries are required to maintain certain proportions of their deposits as cash reserves that cannot be lent out. Based on their stage of economic development, each of the ten countries is classified as belonging to one of three categories: small emerging economies, large emerging economies and developed economies.  
Our study focuses on two important aspects of the banking sector. First, we investigate the extent to which profitable banks make a positive contribution to economic growth. Second, we investigate the determinants of bank profitability. 
The first part of the thesis investigates the relationship between the profitability of banks and economic growth. In order to investigate this relationship, we use data from ten countries in the Asia-Pacific region for the period from 2004 to 2014. In order to address the research questions, we use different econometric techniques such as linear regressions, nonlinear regressions and Granger causality tests. Our results highlight that a profitable banking sector is an important contributor to economic growth. In contrast to our expectations, we find a negative relationship between the size of the banking sector and economic growth. Further, we find that the influence of bank profitability on economic growth decreases when the size of the banking sector increases. The results of our causality tests suggest that causality runs from bank profitability to economic growth but economic growth also has a delayed feedback on bank profitability. 
The second part of this thesis has four empirical chapters that focus on the factors influencing the profitability of banks. First, we investigate the determinants of the profitability of banks in all countries together. Second, we identify the factors influencing the profitability of Islamic and conventional banks in small emerging economies. Third, we investigate the factors affecting the profitability of banks in large emerging markets, and finally, we investigate the determinants of the profitability of banks in developed economies. We use annual data sets of banks for the period from 2004 to 2014 which was gathered from different sources. We use different econometric techniques such as linear regressions and Wald tests to address the research questions. Overall, our results suggest that credit quality, bank size, capital adequacy ratio and cost management are the key factors influencing the profitability of banks in the Asia-Pacific. Cost-efficient banks with superior credit quality are more profitable than their competitors. We find that the impacts of some of the variables vary across regions and countries.

year: 2018

title: Wearable technology for hazardous remote environments: Smart shirt and Rugged IoT network for forestry worker health

authors: Hinze, Annika

subjects: software engineering

abstract: This paper introduces the architecture and details of our wearable IoT solution for workplace health and safety in rugged outdoor environments. We focus on the specific requirements defined by the New Zealand forestry environment as it is the industry with the most fatalities and highest accident rate in New Zealand. Neither consumer-level products nor professional wearables have been found to be suitable for forestry conditions. Furthermore, forestry workplaces cannot rely on existing networking infrastructure, and due to their remote and rugged nature, no permanent setup is possible.

We describe the Hakituri project in which we integrate wearable devices, networking, data analytics, and a buddy system into a novel monitoring solution for worker health and safety. Our wearable IoT solution includes a dynamic network set-up, wearables suitable for forestry conditions, contextual rule-based data analytics, and real-time alerts. A wearable smart shirt carries sensors for collecting personal data from forestry workers, while further environmental sensors capture contextual data. The IoT network is set up for communication in unreliable and rugged outdoor environments. We explore a variety of setups to achieve the best quality outcomes for health and safety in the forestry domain.

text: Wearable technology for hazardous remote environments: Smart shirt and Rugged IoT network for forestry worker health This paper introduces the architecture and details of our wearable IoT solution for workplace health and safety in rugged outdoor environments. We focus on the specific requirements defined by the New Zealand forestry environment as it is the industry with the most fatalities and highest accident rate in New Zealand. Neither consumer-level products nor professional wearables have been found to be suitable for forestry conditions. Furthermore, forestry workplaces cannot rely on existing networking infrastructure, and due to their remote and rugged nature, no permanent setup is possible.

We describe the Hakituri project in which we integrate wearable devices, networking, data analytics, and a buddy system into a novel monitoring solution for worker health and safety. Our wearable IoT solution includes a dynamic network set-up, wearables suitable for forestry conditions, contextual rule-based data analytics, and real-time alerts. A wearable smart shirt carries sensors for collecting personal data from forestry workers, while further environmental sensors capture contextual data. The IoT network is set up for communication in unreliable and rugged outdoor environments. We explore a variety of setups to achieve the best quality outcomes for health and safety in the forestry domain.

year: 2022