Oil Rents And Democracy In Iran 1997-2010: Re-Visiting The Rentier State Theory

Iran, negara yang kaya dengan sumber tetapi mengalami masalah sistem demokrasi yang amat teruk. Penyelidikan ini bertujuan mengkaji kesan daripada pulangan minyak terhadap demokrasi di Iran, dalam tempoh 1997 – 2010. Justeru, penulis meneliti semula teori kerajaan dan menerapkannya dalam keadaan semasa di Iran untuk menjelaskan bagaimana kekayaan atau kemewahan minyak telah membantutkan atau menghalang proses demokerasi di Iran. Satu penyelidikan kualitatif dijalankan dengan menggunakan pendekatan kajian kes dan analisis konteks. Data sekunder dikumpul daripada laporan rasmi kerajaan Iran dan juga laporan daripada pertubuhan antarabangsa yang boleh dipercayai. Dalam seksyen pertama kajian ini, terbukti bahawa Iran dapat dikategorikan sebagai negara penyewa, berdasarkan definisi teori dan keperluan utamanya. Syer perolehan atau pendapatan minyak dalam ekonomi Iran, peranan marginal daripada sistem percukaian, dan pemilikan industri minyak diketengahkan dalam konteks ini. Iran is a resource-rich country that severely suffers from a lack of democracy. The purpose of the present research is to study the effect of oil revenues on democracy in Iran from 1997 to 2010. In order to do so, the author re-visited the rentier state theory and applied it to Iran’s present condition to explain how oil wealth has hindered the democratization process in Iran. A qualitative research was conducted using the case study approach and content analysis. The secondary data was collected from official reports of the Iranian government as well as from reports of reliable international organizations. In the first section of this study it is evidenced that Iran can be categorized as a rentier state, based on the definition of the theory and its vital requirements. The share of oil income in Iran’s economy, marginal role of taxation system, and government ownership of the oil industry were highlighted in this context

Entrepreneurial refugees and the city: brief encounters in Beirut

Lebanon is hosting more than 1 million Syrian refugees. For a country of its size, and a population of around 4 million, this influx of Syrians into Lebanon has exposed many of its already established ailments. A prevailing perception is that Syrians are establishing businesses and competing with the Lebanese, leading to violent reactions on the part of host communities. In this article, we seek to debunk the reductionist framing of ‘the Syrian refugee’ as a burden, and showcase the economic contribution that some Syrian entrepreneurs have been making to urban neighbourhoods. While entrepreneurs certainly represent a minority of the refugees in Lebanon, we argue that, rather than being competition, Syrian entrepreneurs are complementary to Lebanese businesses in urban areas, and that Syrian businesses are enriching spatial practices in the city. As such, we claim their experiences are significant to document as they can inform useful policy interventions that can render Syrian self-employment an opportunity for local economic development in cities and towns

Las tensiones sobre la ayuda tras la explosión del puerto de Beirut en 2020

Las tensiones pueden intensificarse en contextos de crisis superpuestas: los actores humanitarios deben reconocer los diferentes tipos de tensión resultantes de la distribución de la ayuda y responder en consecuencia

Philanthropic Fundraising of Higher Education Institutions: A Review of the Malaysian and Australian Perspectives

Currently, higher education institutions are facing rapidly rising costs and limitations in governmental funding. Accordingly, higher education institutions need sustainable forms of funding to operate effectively and remain competitive. In their attempts to identify causes and initiatives, world universities have paid more attention to philanthropic support. In their effort to raise funds, many institutions have grappled with questions of why donors give and what motivates donors to give. To address these questions, scholars must consider the influence of demographic and socio-economic characteristics, as well as internal and external motivational parameters on successful giving behaviour. However, much more attention has been paid to universities in Western countries and the United States. This study aims to review the factors influencing organizational philanthropic fundraising success and to gain an understanding of factors affecting donors’ giving decisions and perceptions of giving. This work focuses on donors’ giving to Malaysian and Australian public universities

Feature Extraction and Selection in Automatic Sleep Stage Classification

Sleep stage classification is vital for diagnosing many sleep related disorders and Polysomnography (PSG) is an important tool in this regard. The visual process of sleep stage classification is time consuming, subjective and costly. To improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. The automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. In this research work, we focused on feature extraction and selection steps. The main goal of this thesis was identifying a robust and reliable feature set that can lead to efficient classification of sleep stages. For achieving this goal, three types of contributions were introduced in feature selection, feature extraction and feature vector quality enhancement. Several feature ranking and rank aggregation methods were evaluated and compared for finding the best feature set. Evaluation results indicated that the decision on the precise feature selection method depends on the system design requirements such as low computational complexity, high stability or high classification accuracy. In addition to conventional feature ranking methods, in this thesis, novel methods such as Stacked Sparse AutoEncoder (SSAE) was used for dimensionality reduction. In feature extration area, new and effective features such as distancebased features were utilized for the first time in sleep stage classification. The results showed that these features contribute positively to the classification performance. For signal quality enhancement, a loss-less EEG artefact removal algorithm was proposed. The proposed adaptive algorithm led to a significant enhancement in the overall classification accuracy