Manajemen Resiko dalam Dunia Perbankan

This paper is explained about risk management in general and every steps that should be done to implement risk management. The issue about risk management now is become very important in every side of science and practical area. Banking system is one of practical area that risk management which becomes very important and have a great impact to the banking system that now is running. Recently Central Bank of Indonesia make a new rule that every bank in Indonesia have to form a risk management team. This team have obligation to control a multiple aspect of risk management in every bank and to observe the impact of implementing risk management especially to the monetary strength in Indonesia. Therefore this paper will be studied how to implement risk management in general

Analisis Perbedaan Kinerja Keuangan Sebelum dan Sesudah Initial Public Offering Pada Perusahaan Go Public di Bursa Efek Indonesia

Tujuan penelitian ini dilakukan untuk membuktikan perbedaan yang terdapat pada kinerja keuangan sebelum dan sesudah (IPO) Initial Public Offering. Didalam penelitian ini merupakan penelitian kuantitatif dengan menguji hipotesis menggunakan paried-t sampel berpasangangan.Hasil analisis yang telah dilakukan dalam penelitian ini dapat disimpulkan bahwa rasio likuiditas, rasio aktivitas, dan rasio profitabilitas pada pengujian Current Rasio, Total Aset Turnover, dan Return On Investment bahwa kinerja keuangan perusahaan sebelum IPO tidak berbeda secara signifikan setelah IPO pada perusahaan go public di BEI, serta pada rasio solvabilitas dan rasio profitabilitas dengan pengujian Debt to Equity Rasio bahwa kinerja keuangan perusahaan sebelum IPO berbeda secara signifikan setelah IPO pada perusahaan go public di BEI

Analytical Solution of Heat Conduction for Hollow Cylinders with Time-Dependent Boundary Condition and Time-Dependent Heat Transfer Coefficient

An analytical solution for the heat transfer in hollow cylinders with time-dependent boundary condition and time-dependent heat transfer coefficient at different surfaces is developed for the first time. The methodology is an extension of the shifting function method. By dividing the Biot function into a constant plus a function and introducing two specially chosen shifting functions, the system is transformed into a partial differential equation with homogenous boundary conditions only. The transformed system is thus solved by series expansion theorem. Limiting cases of the solution are studied and numerical results are compared with those in the literature. The convergence rate of the present solution is fast and the analytical solution is simple and accurate. Also, the influence of physical parameters on the temperature distribution of a hollow cylinder along the radial direction is investigated

Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach

BACKGROUND: The main limitation in performing genome-wide gene-expression profiling is the assay of low-expression genes. Approaches with high throughput and high sensitivity for assaying low-expression transcripts are urgently needed for functional genomic studies. Combination of the suppressive subtractive hybridization (SSH) and cDNA microarray techniques using the subtracted cDNA clones as probes printed on chips has greatly improved the efficiency for fishing out the differentially expressed clones and has been used before. However, it remains tedious and inefficient sequencing works for identifying genes including the great number of redundancy in the subtracted amplicons, and sacrifices the original advantages of high sensitivity of SSH in profiling low-expression transcriptomes. RESULTS: We modified the previous combination of SSH and microarray methods by directly using the subtracted amplicons as targets to hybridize the pre-made cDNA microarrays (named as "SSH/microarray"). mRNA prepared from three pairs of hepatoma and non-hepatoma liver tissues was subjected to the SSH/microarray assays, as well as directly to regular cDNA microarray assays for comparison. As compared to the original SSH and microarray combination assays, the modified SSH/microarray assays allowed for much easier inspection of the subtraction efficiency and identification of genes in the subtracted amplicons without tedious and inefficient sequencing work. On the other hand, 5015 of the 9376 genes originally filtered out by the regular cDNA microarray assays because of low expression became analyzable by the SSH/microarray assays. Moreover, the SSH/microarray assays detected about ten times more (701 vs. 69) HCC differentially expressed genes (at least a two-fold difference and P < 0.01), particularly for those with rare transcripts, than did the regular cDNA microarray assays. The differential expression was validated in 9 randomly selected genes in 18 pairs of hepatoma/non-hepatoma liver tissues using quantitative RT-PCR. The SSH/microarray approaches resulted in identifying many differentially expressed genes implicated in the regulation of cell cycle, cell death, signal transduction and cell morphogenesis, suggesting the involvement of multi-biological processes in hepato-carcinogenesis. CONCLUSION: The modified SSH/microarray approach is a simple but high-sensitive and high-efficient tool for differentially profiling the low-expression transcriptomes. It is most adequate for applying to functional genomic studies

Instantons at Strong Coupling, Averaging over Vacua, and the Gluino Condensate

We consider instanton contributions to chiral correlators, such as <0| Tr \lambda^2 (x) Tr \lambda^2(x') |0>, in N=1 supersymmetric Yang-Mills theory with either light adjoint or fundamental matter. Within the former model, extraction of the gluino condensate from a connected 1-instanton diagram, evaluated at strong coupling, can be contrasted with expectations from the Seiberg-Witten solution perturbed to an N=1 vacuum. We observe a numerical discrepancy, coinciding with that observed previously in N=1 SQCD. Moreover, since knowledge of the vacuum structure is complete for softly broken N=2 Yang-Mills, this model serves as a counterexample to the hypothesis of Amati et al. that 1-instanton calculations at strong coupling can be interpreted as averaging over vacua. Within N=1 SQCD, we point out that the connected contribution to the relevant correlators actually vanishes in the weakly coupled Higgs phase, despite having a nonzero value through infra-red effects when calculated in the unbroken phase.Comment: 20 pages, LaTeX; minor additions, to appear in Nucl. Phys.

An augmented reality interface for multi-robot tele-operation and control

This thesis presents a seamlessly controlled human multi-robot system comprised of ground and aerial robots of semi-autonomous nature for source localization tasks. The system combines augmented reality interfaces capabilities with human supervisor\u27s ability to control multiple robots. It used advanced path planning algorithms to ensure obstacles are avoided and that the operators are free for higher-level tasks. A sensor data fused AR view is displayed which helped the users pin point source information or help the operator with the goals of the mission. The paper studies a preliminary Human Factors evaluation of this system in which several interface conditions are tested for source detection tasks

Machine-Learned Wireless Propagation Model

Generally, the present disclosure is directed to predicting wireless propagation in an area and/or at a wavelength. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict propagation data (e.g. radio signal attenuation and/or Bit Error Rate (BER)) based on connection data and terrain data

Determining Optimal Wireless Propagation Model for a Region and Wavelength

Generally, the present disclosure is directed to determining an optimal wireless propagation model for a given region and wavelength. In particular, in some implementations, the systems and methods of the present disclosure can include or otherwise leverage one or more machine-learned models to predict an optimal wireless propagation model for a region based on terrain data for the region