Issi

This study aimed to analyze the effect of macroeconomic variables on Indonesian Islamic stock index. Macroeconomic variables used is the interest rate of Bank Indonesia (BI-rate), inflation, exchange rate, Bank Indonesia Certificates Sharia (SBIS) and world oil prices. The data used in this research is secondary data during the period May 2011 until September 2015 using a model error correction model (ECM) where the end result is going to measure the effect of macroeconomic variables on Indonesian Sharia Stock Index in the short term and long term.

In this paper we propose a new model to detect multiple objects of various intensities in images having maximum, minimum, or middle-intensity background by evolving only one level set function. In this model, a new signed pressure force function based on novel generalized averages is used for segmentation of images with maximum or minimum intensity background. For images with middle-intensity backgrounds, which are indeed challenging for 2-phase models, we propose a new product generalized signed pressure force function. Finally, to give experimental and qualitative evidence, our model is tested on both synthetic and real images with the Jaccard similarity index. The experimental and qualitative results reveal that the proposed method is efficient in both global and selective segmentation. Our new model is also tested on color images and the results are compared with the state-of-the-art models.

We argue in favour of artificial neural networks for exploratory data analysis, clustering and mapping. We propose the Kohonen self-organizing map (SOM) for clustering and mapping according to a multi-maps extension. It is consequently called Multi-SOM. Firstly the Kohonen SOM algorithm is presented. Then the following improvements are detailed: the way of naming the clusters, the map division into logical areas, and the map generalization mechanism. The multi-map display founded on the inter-maps communication mechanism is exposed, and the notion of the viewpoint is introduced. The interest of Multi-SOM is presented for visualization, exploration or browsing, and moreover for scientific and technical information analysis. A case study in patent analysis on transgenic plants illustrates the use of the Multi-SOM. We also show that the inter-map communication mechanism provides support for watching the plants on which patented genetic technology works. It is the first map. The other four related maps provide information about the plant parts that are concerned, the target pathology, the transgenic techniques used for making these plants resistant, and finally the firms involved in genetic engineering and patenting. A method of analysis is also proposed in the use of this computer-based multi-maps environment. Finally, we discuss some critical remarks about the proposed approach at its current state. And we conclude about the advantages that it provides for a knowledge-oriented watching analysis on science and technology. In relation with this remark we introduce in conclusion the notion of knowledge indicators.

The relationship between democracy and science has long been discussed by scholars. However, the question has not been adequately addressed empirically at the international level. Using panel data on 161 countries over a seven-year period, we estimate the effects of democracy on scientific influence, controlling for globalization, population size, publication output, and level of international research collaboration. The results show that countries with higher levels of democracy tend to have higher impact science.

We are investigating the manner in which different scientific fields differ in their communication cultures. Our research methodology combines quantitative (graph-theoretic) and qualitative (ethnographic) techniques, which mutually inform each other. In this paper, we present the results of a case study on the identification and classification of scientific collaborations based on structural patterns in co-authorship networks. We investigate three co-authorship networks in specialised subfields of organic chemistry and physical chemistry using an information-theoretic clustering algorithm by Rosvall et al. to extract the modular structure of the networks and thereby investigate the mesoscopic structures of these networks. The clusters found mostly correspond to hierarchically organised research groups or multi-centre research networks. Based on the co-author links between these clusters we analyse group and network interactions, using interviews with participants from the fields in question to inform our interpretation. Structurally one can distinguish two broad classes of linking patterns between clusters: 'exclusive' connections where a single node (author) connects two clusters, and 'manyto-many' connections where substantial fractions of the nodes of both clusters are involved. Within these broad classes one can find further subclasses that correspond to typical collaboration and mobility events.