Menformulasi Pendidikan Pesantren Yang Membebaskan

Islam is a religion of liberation due to the fact that Islam appreciates human to be in equal level, maintains humanity, and higly supports the values democration and justice, teaches telling the truth, and loves the poor and the oppressed. Thus, Islamic education ideally could be conducted on the basis of equality and human dignity. This is to get rid of external hegemony an dit is to give priority to rightness, honesty and fairness, sincerity, and simplicity. The educational foundation might be used by the peasantren (Islamic boarding school) for the instrcutional practice. It is derived from the values that are developed through the educational process---independency, simplicity, and sincerity. The values become the armor for pesantren to get free from any kinds of life anomaly as the impact of the hegemony of modern life style and paradigm. This view concerns with materialism, hednism, opportunism, individualism, and consumerism.Kata-kata kunciPendidikan, pesantren, pembebasa

Time-delayed collective flow diffusion models for inferring latent people flow from aggregated data at limited locations

The rapid adoption of wireless sensor devices has made it easier to record location information of people in a variety of spaces (e.g., exhibition halls). Location information is often aggregated due to privacy and/or cost concerns. The aggregated data we use as input consist of the numbers of incoming and outgoing people at each location and at each time step. Since the aggregated data lack tracking information of individuals, determining the flow of people between locations is not straightforward. In this article, we address the problem of inferring latent people flows, that is, transition populations between locations, from just aggregated population data gathered from observed locations. Existing models assume that everyone is always in one of the observed locations at every time step; this, however, is an unrealistic assumption, because we do not always have a large enough number of sensor devices to cover the large-scale spaces targeted. To overcome this drawback, we propose a probabilistic model with flow conservation constraints that incorporate travel duration distributions between observed locations. To handle noisy settings, we adopt noisy observation models for the numbers of incoming and outgoing people, where the noise is regarded as a factor that may disturb flow conservation, e.g., people may appear in or disappear from the predefined space of interest. We develop an approximate expectation-maximization (EM) algorithm that simultaneously estimates transition populations and model parameters. Our experiments demonstrate the effectiveness of the proposed model on real-world datasets of pedestrian data in exhibition halls, bike trip data and taxi trip data in New York City

Visualization of Documents and Concepts in Neuroinformatics with the 3D-SE Viewer

A new interactive visualization tool is proposed for mining text data from various fields of neuroscience. Applications to several text datasets are presented to demonstrate the capability of the proposed interactive tool to visualize complex relationships between pairs of lexical entities (with some semantic contents) such as terms, keywords, posters, or papers' abstracts. Implemented as a Java applet, this tool is based on the spherical embedding (SE) algorithm, which was designed for the visualization of bipartite graphs. Items such as words and documents are linked on the basis of occurrence relationships, which can be represented in a bipartite graph. These items are visualized by embedding the vertices of the bipartite graph on spheres in a three-dimensional (3-D) space. The main advantage of the proposed visualization tool is that 3-D layouts can convey more information than planar or linear displays of items or graphs. Different kinds of information extracted from texts, such as keywords, indexing terms, or topics are visualized, allowing interactive browsing of various fields of research featured by keywords, topics, or research teams. A typical use of the 3D-SE viewer is quick browsing of topics displayed on a sphere, then selecting one or several item(s) displays links to related terms on another sphere representing, e.g., documents or abstracts, and provides direct online access to the document source in a database, such as the Visiome Platform or the SfN Annual Meeting. Developed as a Java applet, it operates as a tool on top of existing resources

Online multiscale dynamic topic models

We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, some words may be used consistently over one hundred years, while other words emerge and disappear over periods of a few days. Thus, in the proposed model, current topicspecific distributions over words are assumed to be generated based on the multiscale word distributions of the previous epoch. Considering both the long-timescale dependency as well as the short-timescale dependency yields a more robust model. We derive efficient online inference procedures based on a stochastic EM algorithm, in which the model is sequentially updated using newly obtained data; this means that past data are not required to make the inference. We demonstrate the effectiveness of the proposed method in terms of predictive performance and computational efficiency by examining collections of real documents with timestamps