158 research outputs found
A Multi-Sample Based Method for Identifying Common CNVs in Normal Human Genomic Structure Using High-Resolution aCGH Data
BACKGROUND: It is difficult to identify copy number variations (CNV) in normal human genomic data due to noise and non-linear relationships between different genomic regions and signal intensity. A high-resolution array comparative genomic hybridization (aCGH) containing 42 million probes, which is very large compared to previous arrays, was recently published. Most existing CNV detection algorithms do not work well because of noise associated with the large amount of input data and because most of the current methods were not designed to analyze normal human samples. Normal human genome analysis often requires a joint approach across multiple samples. However, the majority of existing methods can only identify CNVs from a single sample. METHODOLOGY AND PRINCIPAL FINDINGS: We developed a multi-sample-based genomic variations detector (MGVD) that uses segmentation to identify common breakpoints across multiple samples and a k-means-based clustering strategy. Unlike previous methods, MGVD simultaneously considers multiple samples with different genomic intensities and identifies CNVs and CNV zones (CNVZs); CNVZ is a more precise measure of the location of a genomic variant than the CNV region (CNVR). CONCLUSIONS AND SIGNIFICANCE: We designed a specialized algorithm to detect common CNVs from extremely high-resolution multi-sample aCGH data. MGVD showed high sensitivity and a low false discovery rate for a simulated data set, and outperformed most current methods when real, high-resolution HapMap datasets were analyzed. MGVD also had the fastest runtime compared to the other algorithms evaluated when actual, high-resolution aCGH data were analyzed. The CNVZs identified by MGVD can be used in association studies for revealing relationships between phenotypes and genomic aberrations. Our algorithm was developed with standard C++ and is available in Linux and MS Windows format in the STL library. It is freely available at: http://embio.yonsei.ac.kr/~Park/mgvd.php
On Evaluating Commercial Cloud Services: A Systematic Review
Background: Cloud Computing is increasingly booming in industry with many
competing providers and services. Accordingly, evaluation of commercial Cloud
services is necessary. However, the existing evaluation studies are relatively
chaotic. There exists tremendous confusion and gap between practices and theory
about Cloud services evaluation. Aim: To facilitate relieving the
aforementioned chaos, this work aims to synthesize the existing evaluation
implementations to outline the state-of-the-practice and also identify research
opportunities in Cloud services evaluation. Method: Based on a conceptual
evaluation model comprising six steps, the Systematic Literature Review (SLR)
method was employed to collect relevant evidence to investigate the Cloud
services evaluation step by step. Results: This SLR identified 82 relevant
evaluation studies. The overall data collected from these studies essentially
represent the current practical landscape of implementing Cloud services
evaluation, and in turn can be reused to facilitate future evaluation work.
Conclusions: Evaluation of commercial Cloud services has become a world-wide
research topic. Some of the findings of this SLR identify several research gaps
in the area of Cloud services evaluation (e.g., the Elasticity and Security
evaluation of commercial Cloud services could be a long-term challenge), while
some other findings suggest the trend of applying commercial Cloud services
(e.g., compared with PaaS, IaaS seems more suitable for customers and is
particularly important in industry). This SLR study itself also confirms some
previous experiences and reveals new Evidence-Based Software Engineering (EBSE)
lessons
Non-Invasive Induction Link Model for Implantable Biomedical Microsystems: Pacemaker to Monitor Arrhythmic Patients in Body Area Networks
In this paper, a non-invasive inductive link model for an Implantable
Biomedical Microsystems (IBMs) such as, a pacemaker to monitor Arrhythmic
Patients (APs) in Body Area Networks (BANs) is proposed. The model acts as a
driving source to keep the batteries charged, inside a device called,
pacemaker. The device monitors any drift from natural human heart beats, a
condition of arrythmia and also in turn, produces electrical pulses that create
forced rhythms that, matches with the original normal heart rhythms. It
constantly sends a medical report to the health center to keep the medical
personnel aware of the patient's conditions and let them handle any critical
condition, before it actually happens. Two equivalent models are compared by
carrying the simulations, based on the parameters of voltage gain and link
efficiency. Results depict that the series tuned primary and parallel tuned
secondary circuit achieves the best results for both the parameters, keeping in
view the constraint of coupling co-efficient (k), which should be less than a
value \emph{0.45} as, desirable for the safety of body tissues.Comment: IEEE 8th International Conference on Broadband and Wireless
Computing, Communication and Applications (BWCCA'13), Compiegne, Franc
Performance Evaluation of Sparse Matrix Products in UPC
This is a post-peer-review, pre-copyedit version of an article published in The Journal of Supercomputing. The final authenticated version is available online at: https://doi.org/10.1007/s11227-012-0796-4[Abstract] Unified Parallel C (UPC) is a Partitioned Global Address Space (PGAS) language whose popularity has increased during the last years owing to its high programmability and reasonable performance through an efficient exploitation of data locality, especially on hierarchical architectures like multicore clusters. However, the performance issues that arise in this language due to the irregular structure of sparse matrix operations have not yet been studied. Among them, the selection of an adequate storage format for the sparse matrices can significantly improve the efficiency of the parallel codes. This paper presents an evaluation, using UPC, of the most common sparse storage formats with different implementations of the matrix-vector and matrix-matrix products, which are key kernels in many scientific applications.Ministerio de Ciencia e Innovación; TIN2010-16735Ministerio de Educación; AP2008-01578Ministerio de Ciencia e Innovación; CAPAP-H3; TIN2010-12011-
Kirchhoff's Circuit Law Applications to Graph Simplification in Search Problems
This paper proposes a new analysis of graph using the concept of electric
potential, and also proposes a graph simplification method based on this
analysis. Suppose that each node in the weighted-graph has its respective
potential value. Furthermore, suppose that the start and terminal nodes in
graphs have maximum and zero potentials, respectively. When we let the level of
each node be defined as the minimum number of edges/hops from the start node to
the node, the proper potential of each level can be estimated based on
geometric proportionality relationship. Based on the estimated potential for
each level, we can re-design the graph for path-finding problems to be the
electrical circuits, thus Kirchhoff's Circuit Law can be directed applicable
for simplifying the graph for path-finding problems
Adaptive data rate control in low power wide area networks for long range IoT services
[EN] Internet of Things (loT) technologies can provide various intelligent services by collecting information from objects. To collect information, Wireless Sensor Networks (WSNs) are exploited. The Low Power Wide Area Network (LPWAN), one type of WSN, has been designed for long-range loT services. It consumes low power and uses a low data rate for data transmission. The LPWAN includes several communication standards, and Long Range Wide Area Network (LoRaWAN) is the representative standard of the LPWAN. LoRaWAN provides several data rates for transmission and enables adaptive data rate control in order to maintain network connectivity. In the LoRaWAN, the wireless condition is considered by the reception status of the acknowledgement (ACK) message, and adaptive data rate control is performed according to the wireless condition. Because the judgment of the wireless condition by the reception status of ACK messages does not reflect congestion, adaptive data rate control can lead to inefficiency in data transmission. For efficient data transmission in long-range loT services, this paper proposes a congestion classifier using logistic regression and modified adaptive data rate control. The proposed scheme controls the data rate according to the congestion estimation. Through extensive analysis, we show the proposed scheme's efficiency in data transmission. (C) 2017 Elsevier B.V. All rights reserved.This research was supported by the Soonchunhyang University Research Fund (No. 20160220). This work was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2016R1A2B4011069).Kim, D.; Kim, S.; Hassan Mohamed, H.; Park, JH. (2017). Adaptive data rate control in low power wide area networks for long range IoT services. Journal of Computational Science. 22:171-178. https://doi.org/10.1016/j.jocs.2017.04.014S1711782
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