Faculty Opinions recommendation of Novel algorithms and the benefits of comparative validation.

Abstract In network and systems medicine, active module identification methods (AMIMs) are widely used for discovering candidate molecular disease mechanisms. To this end, AMIMs combine network analysis algorithms with molecular profiling data, most commonly, by projecting gene expression data onto generic protein–protein interaction (PPI) networks. Although active module identification has led to various novel insights into complex diseases, there is increasing awareness in the field that the combination of gene expression data and PPI network is problematic because up-to-date PPI networks have a very small diameter and are subject to both technical and literature bias. In this paper, we report the results of an extensive study where we analyzed for the first time whether widely used AMIMs really benefit from using PPI networks. Our results clearly show that, except for the recently proposed AMIM DOMINO, the tested AMIMs do not produce biologically more meaningful candidate disease modules on widely used PPI networks than on random networks with the same node degrees. AMIMs hence mainly learn from the node degrees and mostly fail to exploit the biological knowledge encoded in the edges of the PPI networks. This has far-reaching consequences for the field of active module identification. In particular, we suggest that novel algorithms are needed which overcome the degree bias of most existing AMIMs and/or work with customized, context-specific networks instead of generic PPI networks.

Download Full-text

All-gather Algorithms Resilient to Imbalanced Process Arrival Patterns

ACM Transactions on Architecture and Code Optimization ◽

10.1145/3460122 ◽

2021 ◽

Vol 18 (4) ◽

pp. 1-22

Author(s):

Jerzy Proficz

Keyword(s):

Experimental Evaluation ◽

Data Exchange ◽

State Of The Art ◽

Monitoring And Evaluation ◽

The Other ◽

Early Data ◽

Cluster Architecture ◽

Novel Algorithms

Two novel algorithms for the all-gather operation resilient to imbalanced process arrival patterns (PATs) are presented. The first one, Background Disseminated Ring (BDR), is based on the regular parallel ring algorithm often supplied in MPI implementations and exploits an auxiliary background thread for early data exchange from faster processes to accelerate the performed all-gather operation. The other algorithm, Background Sorted Linear synchronized tree with Broadcast (BSLB), is built upon the already existing PAP-aware gather algorithm, that is, Background Sorted Linear Synchronized tree (BSLS), followed by a regular broadcast distributing gathered data to all participating processes. The background of the imbalanced PAP subject is described, along with the PAP monitoring and evaluation topics. An experimental evaluation of the algorithms based on a proposed mini-benchmark is presented. The mini-benchmark was performed over 2,000 times in a typical HPC cluster architecture with homogeneous compute nodes. The obtained results are analyzed according to different PATs, data sizes, and process numbers, showing that the proposed optimization works well for various configurations, is scalable, and can significantly reduce the all-gather elapsed times, in our case, up to factor 1.9 or 47% in comparison with the best state-of-the-art solution.

Download Full-text

A Survey for Recent Techniques and Algorithms of Geolocation and Target Tracking in Wireless and Satellite Systems

Applied Sciences ◽

10.3390/app11136079 ◽

2021 ◽

Vol 11 (13) ◽

pp. 6079

Author(s):

Abulasad Elgamoudi ◽

Hamza Benzerrouk ◽

G. Arul Elango ◽

René Landry

Keyword(s):

Target Tracking ◽

Satellite Communication ◽

Interference Mitigation ◽

Global Navigation Satellite Systems ◽

Military Operations ◽

Satellite Systems ◽

Disturbance Source ◽

Single Radio ◽

Novel Algorithms ◽

Global Navigation Satellite

A single Radio-Frequency Interference (RFI) is a disturbance source of modern wireless systems depending on Global Navigation Satellite Systems (GNSS) and Satellite Communication (SatCom). In particular, significant applications such as aeronautics and satellite communication can be severely affected by intentional and unintentional interference, which are unmitigated. The matter requires finding a radical and effective solution to overcome this problem. The methods used for overcoming the RFI include interference detection, interference classification, interference geolocation, tracking and interference mitigation. RFI source geolocation and tracking methodology gained universal attention from numerous researchers, specialists, and scientists. In the last decade, various conventional techniques and algorithms have been adopted in geolocation and target tracking in civil and military operations. Previous conventional techniques did not address the challenges and demand for novel algorithms. Hence there is a necessity for focussing on the issues associated with this. This survey introduces a review of various conventional geolocation techniques, current orientations, and state-of-the-art techniques and highlights some approaches and algorithms employed in wireless and satellite systems for geolocation and target tracking that may be extremely beneficial. In addition, a comparison between different conventional geolocation techniques has been revealed, and the comparisons between various approaches and algorithms of geolocation and target tracking have been addressed, including H∞ and Kalman Filtering versions that have been implemented and investigated by authors.

Download Full-text

Integrated Heterogeneous Micro-Nano Systems via Modular Designing and Flexible Assembly

Volume 11: Nano and Micro Materials, Devices and Systems; Microsystems Integration ◽

10.1115/imece2011-64095 ◽

2011 ◽

Author(s):

Aditya Das ◽

Rakesh Murthy

Keyword(s):

Uncertainty Propagation ◽

Systems Development ◽

Surface Machining ◽

Flexible Assembly ◽

Nano Scale ◽

Wide Range ◽

Standard Design ◽

Novel Algorithms ◽

And Control ◽

Dedicated Hardware

One of the major challenges in commercializable micro-nano systems development is the high cost and turnaround that are incurred through multiple product-optimization iterations and expensive fabrication processes for specific systems. Development of complex and heterogeneous micro-nano systems, that are only possible through assembly and not by conventional surface machining approaches, are further impeded by lack of standard design rules and off-the-shelf robotic manipulation systems. Dedicated hardware and system specific component designs, although possible, are not commercially viable for addressing the wide range of opportunities that exists in the prevailing micro-nano domain. In this paper, we present an alternative and holistic top-down approach for micro-nano manufacturing using modular part designs and flexible assembly systems. We incorporate, seamlessly, multiple novel algorithms related to microrobotics and scaling of physics, obtained both analytically as well as experimentally; in order to predict, track and control the uncertainty propagation in a typical manufacturing process, in micro-nano scale, throughout production steps including design, machining, setup, assembly, testing etc. We demonstrate, through multiple examples, the implementation of the proposed framework in micro-nano scale manufacturing.

Download Full-text