Linux Platform Research Articles

Improved Edge Detection Algorithm and Its Application in Robotic Fish

To get self-adaptive thresholds, the edge detection algorithm of Canny operator is improved in OpenCV library under Linux platform in this paper. Firstly, the gradient graph of the gray image and the maximum value of the gradient are obtained. Then the histogram is calculated and the pixel points corresponding to the gradient values are obtained via the traversion of histogram. Finally, the high and low thresholds are calculated to determine edge. Consequently, there comes the new self-adaptive thresholds algorithm of Canny operator. In the meantime, by simulating on the robotic fish in the water, the new algorithm is compared with the traditional Canny operator in the effect of the output image and the Peak Signal to Noise Ratio. What’s more, the same picture is tested to compare time in the Matlab platform and OpenCV platform. Such comparisons show that the new algorithm has more flexibility and efficiency

Linux Platforms as a Secure Desktop Solution

Linux Platforms as a Secure Desktop Solution

MPMTP-AR: Multipath Message Transport Protocol Based on Application-Level Relay

Recent advancements in network infrastructures provide increased opportunities to support data delivery over multiple paths. Compared with multi-homing scenario, overlay network is regarded as an effective way to construct multiple paths between end devices without any change on the underlying network. Exploiting multipath characteristics has been explored for TCP with multi-homing device, but the corresponding exploration with overlay network has not been studied in detail yet. Motivated by improving quality of experience (QoE) for reliable data delivery, we propose a multipath message transport protocol based on application level relay (MPMTP-AR). MPMTP-AR proposes mechanisms and algorithms to support basic operations of multipath transmission. Dynamic feedback provides a foundation to distribute reasonable load to each path. Common source decrease (CSD) takes the load weight of the path with congestion into consideration to adjust congestion window. MPMTP-AR uses two-level sending buffer to ensure independence between paths and utilizes two-level receiving buffer to improve queuing performance. Finally, the MPMTP-AR is implemented on the Linux platform and evaluated by comprehensive experiments.

Reproducible Large-Scale Neuroimaging Studies with the OpenMOLE Workflow Management System.

OpenMOLE is a scientific workflow engine with a strong emphasis on workload distribution. Workflows are designed using a high level Domain Specific Language (DSL) built on top of Scala. It exposes natural parallelism constructs to easily delegate the workload resulting from a workflow to a wide range of distributed computing environments. OpenMOLE hides the complexity of designing complex experiments thanks to its DSL. Users can embed their own applications and scale their pipelines from a small prototype running on their desktop computer to a large-scale study harnessing distributed computing infrastructures, simply by changing a single line in the pipeline definition. The construction of the pipeline itself is decoupled from the execution context. The high-level DSL abstracts the underlying execution environment, contrary to classic shell-script based pipelines. These two aspects allow pipelines to be shared and studies to be replicated across different computing environments. Workflows can be run as traditional batch pipelines or coupled with OpenMOLE's advanced exploration methods in order to study the behavior of an application, or perform automatic parameter tuning. In this work, we briefly present the strong assets of OpenMOLE and detail recent improvements targeting re-executability of workflows across various Linux platforms. We have tightly coupled OpenMOLE with CARE, a standalone containerization solution that allows re-executing on a Linux host any application that has been packaged on another Linux host previously. The solution is evaluated against a Python-based pipeline involving packages such as scikit-learn as well as binary dependencies. All were packaged and re-executed successfully on various HPC environments, with identical numerical results (here prediction scores) obtained on each environment. Our results show that the pair formed by OpenMOLE and CARE is a reliable solution to generate reproducible results and re-executable pipelines. A demonstration of the flexibility of our solution showcases three neuroimaging pipelines harnessing distributed computing environments as heterogeneous as local clusters or the European Grid Infrastructure (EGI).

Arduino Based Physics and Engineering Remote Laboratory

The concept of remote laboratories exists for some time with increasing importance for contemporary education in various fields and at various levels. Advance of remote labs is based on technology development and conceptual improvements with possible mutual influences such as when new technologies can make new concepts possible. Arduino is a family of small inexpensive single board computers (SBC) based primarily on microcontrollers with added Linux platforms on some boards for improved processing and Internet accessibility. Various shields extend interaction functionality of Arduino boards with environment. A number of other brands with quite similar concepts exist, with Arduino as one of very well-known and widespread. Arduino based remote lab concept relies on “Arduino only” implementation which is possible for many not too demanding applications without usual desktop or similar PC platforms. Such concept has many implications like project cheap price, interconnecting of boards for more demanding tasks, small consumption, autonomy, small dimensions, low installation requirements, which is suitable for applications at remote locations and applications requiring mobility. Hybrid solutions including Arduino or similar boards and other more powerful computer platforms may be optimal for more demanding applications. Programming and application development for Arduino and similar boards are supported by large community of developers and users that provide various libraries, solution examples, forums covering various thematic and application aspects. This paper discusses and presents some hardware and software configurations with Arduino and compatible boards that are used for implementation of experiments in physics and technics. Although the considered remotely operated experiments are different in nature, quite similar hardware and software architectures are used.

Enc-DNS-HTTP: Utilising DNS Infrastructure to Secure Web Browsing

Online information security is a major concern for both users and companies, since data transferred via the Internet is becoming increasingly sensitive. The World Wide Web uses Hypertext Transfer Protocol (HTTP) to transfer information and Secure Sockets Layer (SSL) to secure the connection between clients and servers. However, Hypertext Transfer Protocol Secure (HTTPS) is vulnerable to attacks that threaten the privacy of information sent between clients and servers. In this paper, we propose Enc-DNS-HTTP for securing client requests, protecting server responses, and withstanding HTTPS attacks. Enc-DNS-HTTP is based on the distribution of a web server public key, which is transferred via a secure communication between client and a Domain Name System (DNS) server. This key is used to encrypt client-server communication. The scheme is implemented in the C programming language and tested on a Linux platform. In comparison with Apache HTTPS, this scheme is shown to have more effective resistance to attacks and improved performance since it does not involve a high number of time-consuming operations.

A Migration Method of MPI Program Combining Local Library Replacement and Instruction Translation

Binary translation acts as a main method used to solve software compatibility among different instruction set architectures (ISAs), yet the main objects that the binary translator deals with are serial programs but not parallel programs. We propose a hybrid method combining local library replacement and instruction translation based on a formal model built to describe the equivalent when migrating MPI programs between different clusters. The shared codes in a MPI program (MPI library function call) are treated by executing local libraries, and the other parts are done by dynamic binary translation. Also, during the course of dealing with local library functions, we propose a method of program flow redirection by designing two algorithms along with hierarchically encapsulating local libraries. A framework called MPI-QEMU is designed to implement migrating MPI program of 64 bits from X86-64/Linux platform to the domestic SW platform which is verified by experiment.

Automatic Wheat Leaf Rust Detection and Grading Diagnosis via Embedded Image Processing System

Wheat leaf rust is one of the major fungal diseases that makes severe drop in the wheat production. With the desire for rapid and accurate identification of disease, real-time access to the degree of that and timely measures, a wheat leaf diseases detection system based on embedded image recognition technology is designed. The system adopted the ARM9 processor with the embedded Linux platform as the main body, and the program is developed in the Qt integrated environment. At first, the captured clear disease picture of wheat leaf rust was transformed into G single channel gray image of RGB model. Second, based on exploration Sobel operator method, vertical edges detection were implemented on the gray image, eliminate the background of image and extracts binary feature point set of disease spot. Third, the noisy points in the point set is further filtered out by flood filling algorithm. Finally, the area ratio of disease spots and leaf is calculated to get the precise diagnosis of disease level. It has been verified that the recognition rate reaches 96.2% and accuracy rated reaches 92.3% with the method of image processing, which is approximately equal to the result of human vision. This system can be used as agricultural robot to inspect in the field, realizing the intelligentization in detection, identification, diagnosis and classification of crop disease.

Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data.

Since most analysis software for genome-wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even datasets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper, we reexamine the computational bottlenecks and implement ultra-fast pedigree-based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (six CPU cores at 2.67 GHz), analyzing a univariate HDL (high-density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1,388 individuals in 124 pedigrees) takes less than 2 min and 1.5 GB of memory. Complete multivariate QTL analysis of the three time-points of the longitudinal HDL multivariate trait takes less than 5 min and 1.5 GB of memory. The algorithm is implemented as the Ped-GWAS Analysis (Option 29) in the Mendel statistical genetics package, which is freely available for Macintosh, Linux, and Windows platforms from http://genetics.ucla.edu/software/mendel.

<em>In silico</em> investigations revealed four potential colon cancer drugs from phytochemicals in <em>Zingiber officinale</em>

<p align="left">Cancer is a difficult disease to treat, and few effective drugs are available. Hence, it is of great importance to develop effective anti-cancer therapeutic agents with well-defined pharmacokinetic properties.<strong> </strong>Although, ginger (<em>Zingiber officinale</em>) has a number of proven pharmacological activities, its effect on colon cancer has not received much attention. This study therefore investigated the potential colon cancer drug of compounds found in ginger. Dihydropyrimidine dehydrogenase was modeled using comparative homology modeling and virtual screening was performed locally on a Linux platform using AutoDock Vina<sup>®</sup>. The results showed that human dihydropyrimidine dehydrogenase is a homolog of pig dihydropyrimidine dehydrogenase. The leads of potential colon cancer drugs were beta-sitosterol, 6-Shogoal, Alloaromadedrene, and Zingiberol. They had similar binding site with levamisole for tumor necrosis factor ligand superfamily member 6 with His 148 and Tyr 192 common at their binding site whereas they had different binding sites from 5-fluorouracil for dihydropyrimidine dehydrogenase. The leads had better bioactivities compared with reference drugs (5-flourouracil and Levamisole) approved clinically for the treatment of colon cancer. <em>In vitro</em>, <em>ex vivo</em> and/or <em>in vivo</em> validations of the leads against colon cancer are recommended. <strong></strong></p>

An Experiential Learning in Web Technology Course

Web Technology is the development of the mechanism that allows two or more computer devices to communicate over a network. To understand such a complex system there is a need of experiential learning. Authors adopted an Experiential for teaching the web technology course. Teaching with a hands-on session where the teacher explains the concepts with demonstration and students simultaneously practice and also modify the fields to observe the change. After the end of chapter the students learning is verified by giving the structured enquiry category assignments and are evaluated. At the end of delivery of course that is one month before the term end the collective learning is verified through the course project. Two course projects are carried out by the students as a team of two. One is the intranet project, where student understands how to connect and work in a local area network and the other is internet project, where student learns how to host a website globally. In both the projects students used LINUX platform with LAMP as a framework and developed web apps using HTML5, CSS 3, JQuery, PHP and SQL. The experiential learning enhanced the student's domain knowledge of Linux architecture, computer networks, and web and database servers applying in real time scenarios. Finally, we conclude such practical/programming oriented courses should be designed as hands-on lab course to attain the best outcomes.

Patient Condition Monitoring Modular Hospital Robot

In this paper an intelligent system for remote patient physical condition monitoring service module for an Intelligent Robot Swarm for Attendance, Recognition, Cleaning and Delivery (iWARD) [1] is reported. The system algorithm and module software is implemented in C/C++, and the Orca robotics [2] components use the OpenCV [3] image analysis and processing library. The system is successfully tested on Linux (Ubuntu) platform as well as on a web server. The patient condition monitoring system can remotely measure the following body conditions: body temperature (BTemp), heart rate (HR), electrocardiogram (ECG), respiration rate (RR), body acceleration (BA) using sensors attached to the patient’s body. The system also includes an RGB video camera and a 3D laser sensor, which monitor the environment in order to find any patient lying on the floor. The system deals with various image-processing and sensor fusion techniques. The iWARD patient condition monitoring module evaluation tests were carried out in front of thirty healthcare professionals (doctors, nurses, nursing lecturers and healthcare assistances etc) during the final review meeting of the consortium and in two teaching hospitals (in Newcastle and San Sebastian, 2009) in Europe. The post iWARD system improved upon the prototype by adding a 3D laser sensor and replacing the original camera with a high quality Pan-Tilt-Zoom (PTZ) camera and implementing the identity detection methods. This allowed for the use of more robust patient condition monitoring algorithms. The outcomes of this research have significant contribution to the robotics application area in the hospital environment.

CLOUD COMPUTING FOR SPACECRAFT CHECKOUT OPERATIONS

The Spacecraft Checkout deals with testing and validation of all Spacecraft elements and its functionalities before launch. The checkout deals with extensive testing operations on the Spacecraft and the data related to the tests are also voluminous. About 60 percent of the Spacecraft Checkout operations have been automated using a suite of software tools which runs on Checkout servers which are on LINUX platform. The automated operations using this software suite requires a lot of backend effort for setting up configuration files, databases with information on Telemetry, Telecommand and other subsystems, test files which details the operations to be carried out are logged for future reference. A lot of manual effort goes in the checkout preparatory phase where in the databases, test procedures and configuration files are prepared. During the checkout operations, the satellite data acquired has to be distributed online to different agencies for analysis in real time as well as at a later stage. This project aims at exploring cloud platform based solutions for the unified platform where all satellite preparatory data can be kept, support for tools which aids in generating databases and test files based on previous spacecraft data, spacecraft Data Access Portal for External Agencies and support for tools which aids in Remote Checkout operations. A feasible architecture which suits the checkout environment will be the outcome.

Low-barrier-to-entry data tools: creating and sharing humanities data

Purpose – The purpose of this paper is to determine whether TAMS Analyzer and Viewshare are viable free and open source software data sharing and creation tools for those with limited funding and technological skills. Design/methodology/approach – The participant observer method was used to collect experiential evidence while applying the tools to a collection of text-, image-, and video-based digital cultural records. Findings – TAMS Analyzer was found to be a low barrier to entry tool for those with coding and qualitative data analysis experience. Those with general experience will be able to create datasets with the support of manuals and tutorials, while those with limited experience may find it difficult to use. Viewshare was found to be a low barrier to entry tool for sharing data online, and accessible for all skill levels. Research limitations/implications – TAMS Analyzer supports Mac and Linux platforms only, so a low-cost software recommendation was made for those in Windows environments. Practical implications – Librarians can use these tools to address data access gaps while promoting library digital collections. Social implications – With a greater understanding of data tools, librarians can be advisors, collaborators, agents for data culture, and relevant participants in digital humanities scholarship. Originality/value – The research evaluates both the capabilities of the tools and the barriers to using or accessing them, which are often neglected. The paper addresses a need in the literature for greater scrutiny of tools that are a critical component of the data ecology, and will further assist librarians when connecting scholars to tools of inquiry in an environment with limited funding and technical support.

RADIS: analysis of RAD-seq data for interspecific phylogeny.

In an attempt to make the processing of RAD-seq data easier and allow rapid and automated exploration of parameters/data for phylogenetic inference, we introduce the perl pipeline RADIS. Users of RADIS can let their raw Illumina data be processed up to phylogenetic tree inference, or stop (and restart) the process at some point. Different values for key parameters can be explored in a single analysis (e.g. loci building, sample/loci selection), making possible a thorough exploration of data. RADIS relies on Stacks for demultiplexing of data, removing PCR duplicates and building individual and catalog loci. Scripts have been specifically written for trimming of reads and loci/sample selection. Finally, RAxML is used for phylogenetic inferences, though other software may be utilized.Availability and implementation: RADIS is written in perl, designed to run on Linux and Unix platforms. RADIS and its manual are freely available from http://www1.montpellier.inra.fr/CBGP/software/RADIS/.Contact: astrid.cruaud@supagro.inra.frSupplementary information: Supplementary data are available at Bioinformatics online.

A kernel-space POF virtual switch

Protocol Oblivious Forwarding (POF) aims at providing a standard southbound interface for sustainable Software Defined Networking (SDN) evolvement. It overcomes the limitations of popular OpenFlow protocols (an existing widely-adopted southbound interface), through the enhancement of SDN forwarding plane. This paper pioneers the design and implementation of a Kernel-space POF Virtual Switch (K_POFVS) on Linux platform. K_POFVS can improve the packet processing speed, through fast packet forwarding and the capability of adding/deleting/modifying protocol fields in kernel space. In addition, it is able to enhance flow table matching speed, by separating the mask table (consisting of flow entry masks used to figure out the matching field) and the flow table under a caching mechanism. Furthermore, K_POFVS can achieve efficient communication between the kernel space and the user space, via extending the netlink communication between them. Experimental results show that K_POFVS can provide much better performance than existing user-space POF virtual switches, in terms of packet forwarding delay, packet processing delay and packet transmission rate.

Implementation of Intrusion Detection System and Traffic Analysis – A Case of a Linux Platform

The security of a Computer network cannot be compromised in any form as it would actually defeat the exact purpose for which the network exists; to provide connectivity between nodes that would allow exchange of information or resources. It also goes a long way to ensure absolute security for nodes in communication, information at source, in transit or flight and finally at the destination. Security implementations may vary according to network designs but it is essentially suppose to provide Authentication, Data integrity, Confidentiality, Access control and Availability. This paper looks at the implementation of an Intrusion Detection System on a Linux operating systems and analyzing the traffic, threats and vulnerabilities with a configured Firewall General terms Access privileges, Packets, Operating System

GkmSVM: an R package for gapped-kmer SVM.

We present a new R package for training gapped-kmer SVM classifiers for DNA and protein sequences. We describe an improved algorithm for kernel matrix calculation that speeds run time by about 2 to 5-fold over our original gkmSVM algorithm. This package supports several sequence kernels, including: gkmSVM, kmer-SVM, mismatch kernel and wildcard kernel. gkmSVM package is freely available through the Comprehensive R Archive Network (CRAN), for Linux, Mac OS and Windows platforms. The C ++ implementation is available at www.beerlab.org/gkmsvm mghandi@gmail.com or mbeer@jhu.edu Supplementary data are available at Bioinformatics online.

Embedded multi-channel data acquisition system on FPGA for Aditya Tokamak

The 64 channel data acquisition board is designed to meet the future demand of acquisition channels for plasma diagnostics. The inherent features of the board are 16 bit resolution, programmable sampling rate upto 200kS/s/ch and simultaneous acquisition. To make system embedded and compact, 8 Analog Inputs ADC chip, 4M×16 bit RAM memory, Field Programmable Gate Arrays, PC/104 platform and single board computer are used. High speed timing control signals for all ADCs and RAMs are generated by FPGA. The system is standalone, portable and interface through Ethernet. The acquisition application is developed in Qt. on Linux platform, in SBC. Due to ethernet connectivity and onboard processing, system can be integrated into Aditya and SST-1 data acquisition system. The performance of hardware is tested on Linux and Windows Embedded OS. The paper describes design, hardware and software architecture, implementation and results of 64 channel DAQ system.

GUIdock: Using Docker Containers with a Common Graphics User Interface to Address the Reproducibility of Research.

Reproducibility is vital in science. For complex computational methods, it is often necessary, not just to recreate the code, but also the software and hardware environment to reproduce results. Virtual machines, and container software such as Docker, make it possible to reproduce the exact environment regardless of the underlying hardware and operating system. However, workflows that use Graphical User Interfaces (GUIs) remain difficult to replicate on different host systems as there is no high level graphical software layer common to all platforms. GUIdock allows for the facile distribution of a systems biology application along with its graphics environment. Complex graphics based workflows, ubiquitous in systems biology, can now be easily exported and reproduced on many different platforms. GUIdock uses Docker, an open source project that provides a container with only the absolutely necessary software dependencies and configures a common X Windows (X11) graphic interface on Linux, Macintosh and Windows platforms. As proof of concept, we present a Docker package that contains a Bioconductor application written in R and C++ called networkBMA for gene network inference. Our package also includes Cytoscape, a java-based platform with a graphical user interface for visualizing and analyzing gene networks, and the CyNetworkBMA app, a Cytoscape app that allows the use of networkBMA via the user-friendly Cytoscape interface.