John Vong

MFIs have a high interest rate burden due to the small amount per transaction of microcredit and inevitably high operating cost per transaction. To ensure financial viability and to expand the depth and breadth of their operations, MFIs have to adopt cost recovery interest rates on microcredit, hence, MFIs have to charge interest rate high enough, usually substantially higher than the bank loan risk free interest rate. The major factors determining the interest rate on microcredit are the cost of funds, operating costs, loan loss cost and capital for business expansion. To illustrate the impacts of the above factors on interest rate, we present a summary of the current cost structures of microfinance institutes (MFIs) in three Southeast Asia countries, Cambodia, Vietnam and Indonesia. Then, we review existing studies and propose new uses of mobile technologies and financial market innovations for lowering the interest burden.

The financial inclusion of women micro entrepreneurs is both important and necessary for the holistic socio-economic development of a nation. This paper aims to address the gap in the study of the processes of financial inclusion by women micro-entrepreneurs in Indonesia. The research will contribute to the pool of academic resources that pertains to financial inclusion, micro credit, and women entrepreneurship, intending to improve the processes and benchmarking for financial inclusion initiatives. There is an extensive literature research plus in situ research conducted in Indonesia. There is also significant evidence of factors pertaining to gender inequality, which is a result of financial inclusion of women. Both desk research and field research found financial exclusion is linked to financial education, cultural norms of rural Indonesia and high banking cost and mobile payments. In conclusion, the authors recommend a better processes in designing financial products, improving financial education, lowering cost of banking especially in the use of mobile payment technology, and instituting micro-insurance. Further research is recommended to generate hypotheses relating to financial inclusion and women entrepreneurship in Indonesia.

The UN has predicted that cell-phone ownership will reach 5 billion in 2010. This proliferation of cell phones and connectivity offers an unprecedented opportunity to access vast populations, including previously hard-to-reach populations in rural areas and mountainous zones and underserved populations. Cell phones now can provide capabilities for the developing world that includes text, image processing and image displays. The available standardized interfaces can be leveraged to create powerful systems. In particular, digital cameras of cell phones provide easy to use interfaces for capturing useful information on the general well-being and emotive features of individuals. However, photographic images contain private and sensitive personal information in its raw form and thus considered unsuitable for online services. Therefore, there is a need for a computational algorithm for extracting anonymous digital features (for example, Hamming distance) from captured facial expression images for estimating different states of well-being. We have developed computer algorithms predicting well-being states from anonymous facial expression features. The research outcome can be used in a variety of online services including suggesting useful health information to improve general well-being.

We propose a mobile collaborative experiential learning system that students can access via mobile devices or any interactive devices connected to the Internet. The approach departs from conventional summative assessment approaches, such as reports submitted at the end of their learning sessions. Students interact with the learning system via mobile devices in order to change the state of a simulated learning lab to a desired state over time anywhere anytime to solve problems or achieve their goals. Students acquire set competency levels during their journey to achieving their goals interacting with the learning environment via mobile devices. The main objectives are to provide ownership of their journey, experiential, contextualized and formative assessment at low cost. The system features SMS/MMS biding of WSDL, SOA 2.0, and Event- Condition-Action (ECA) process modeling for easy integration with existing systems.

Banking is essential to modern economies and nearly half of the world's people are unbanked and underserved by banks. The high operating costs of banks passed on to retail customers are driving them away who otherwise should be in the financial system. Without having access to the financial system the unbanked and rural poor have little means to engage in mainstream economic activities. A mobile phone-based banking system was designed to provide retail banking services to the world's unbanked population and rural poor of 2.2 billion based on a cashless banking system that reduces operating cost and reduces lending risks and therefore can lower the current exorbitant rates charged on retail lending and micro-credit. A core-banking server on a low-cost mobile device (an Android tablet) could serve over 15,000 micro-banking customers. The system definitely appears to be suitable for most retail banks or microfinance institutions.

In this study, we propose to examine facial nerve palsy using Support Vector Machines (SVMs) and Emergent Self-Organizing Map (ESOM). This research seeks to analyze facial palsy domain using facial features and grade the degree of nerve damage according to House-Brackmann score. Traditional evaluation methods involve a medical doctor taking a thorough history of a patient and determines the onset of the paralysis, the rate of progression and etc. The most important step is to assess the degree of voluntary movement present and document the grade of facial paralysis using House-Brackmann score. The significance of this work is that we attempt to apprehend this grading using semi-supervised learning with the aim of automating this grading process. The value of this research stems from the fact that there is a lack of literature seen in this area. The use of automated grading system greatly reduces assessment time and increases consistency because references of all palsy images are stored to provide references and comparison. The proposed automated diagnostics methods are computationally efficient making them ideal for remote assessment of facial palsy, profiling of a large number of facial images captured using mobile phones and digital cameras.