Linux Machine Research Articles

ProcaryaSV: structural variation detection pipeline for bacterial genomes using short-read sequencing

BackgroundStructural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results.ResultsWe developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool.ConclusionsThe ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly available on GitHub at https://github.com/robinjugas/ProcaryaSV.

ANCHOR: A New Proposed Stream Cipher for Smart Cards with Crypto Co-Processor

A smart card is a small pocket-sized computer with limited resources used for secure data processing and storage. The card consists of different software and hardware components, including a microprocessor, crypto co-processor, RAM, secure ROM, and operating system. Even though smart cards have a lot of limitations in terms of processing power and small-sized memory, smart cards are widely used in many applications that require a high degree of security such as e-passports, citizen cards, e- banking, etc... Basically, the security of a smart card depends mainly on the security strength of the cipher algorithm implemented inside. This paper presents a new lightweight, high-speed, and cryptographically strong stream cipher algorithm (ANCHOR) suitable for implementation on smart cards. The building blocks of the proposed cipher were carefully built/chosen with high-valued cryptographic properties. The randomness and linear complexity properties of the proposed cipher algorithm have been successfully tested with statistical tests of the NIST suite and the Berlekamp- Massey algorithm respectively. In order to test the performance of the proposed cipher algorithm, the algorithm was developed in C language and executed on a Linux machine.

ROS OS Based Environment Mapping of Cyber Physical System Lab by Depth Sensor

The 21st century is a century of Robotics and thus the appearance of robots in the industries made the “Industrial Revolution 4.0” in which we can control and analyse the system using HMI’s or wirelessly over network and it’s a great example of industry 4.0 component. Nowadays robots are very important part of industry’s processing unit as they have the tendency to work 24*7 thus increases the efficiency of processing and production unit.
 In our project a depth sensor (Microsoft’s Xbox Kinect) is mounted on a mobile robot whose main task is to map our Cyber Physical System Lab in 3-Dimensional which uses a ROS OS software installed on linux machine.
 The robot will use a Simultaneous localization and mapping (SLAM) process to map an environment while currently generating an estimate for the location of the Robot.

Smart railways: the design and construction of an autonomous inspection and maintenance vehicle

The Railway Inspection and Maintenance Vehicle (RIMV) is a state-of-the-art autonomous ground robot for the railway environment. The robot has specialised hardware tailored for specific functionalities, ensuring optimal performance in its designated tasks. It incorporates a GPS, IMU, and encoder for robust localisation, and it integrates a LiDAR system and a depth camera for collision avoidance. Prioritising safety, the RIMV features an IP camera for real-time environmental monitoring and is equipped with emergency stop mechanisms. An Ubuntu Linux machine manages the robot’s data processing, complemented by a 5G Wi-Fi router for remote monitoring and operation when necessary. ROS2 is the primary platform for robot operations, standing out for its open-source solution and enhanced cybersecurity features. We validated the RIMV in a heritage railway setting with an ultrasonic inspection kit to detect rail-track defects. Beyond this specific application, the RIMV is versatile and designed to serve as a platform for other autonomous inspection and maintenance tasks within the railway sector. Its adaptability highlights its potential to enhance efficiency and safety in railway maintenance, offering invaluable assistance to human operators across varied scenarios.

Vincent: Green hot methods in the JVM

In this paper, we show the energy efficiency of Java applications can be improved by applying Dynamic Voltage and Frequency Scaling (DVFS) inside the Java Virtual Machine (JVM). We augment the JVM to record the energy consumption of hot methods as the underlying CPU is run at different clock frequencies; after all the frequency possibilities for a method have been explored, the execution of the method in an optimized run is set to the CPU frequency that leads to the most energy-efficient execution for that method. We introduce a new sampling methodology to overcome the dual challenges in our design: both the underlying measurement mechanism for energy profiling and the DVFS for energy optimization are overhead-prone. We extend JikesRVM with our approach and benchmark it over the DaCapo suite on a server-class Linux machine. Experiments show we are able to use 14.9% less energy than built-in power management in Linux, and improve energy efficiency by 21.1% w.r.t. the metric of Energy-Delay Product (EDP).

Towards a Critical Review of Cybersecurity Risks in Anti-Poaching Systems

Anti-poaching operations increasingly make use of a wide variety of technology for intelligence and communications. These technologies introduce cybersecurity risk, and they need to be secured to provide greater protection to the information and people involved in anti-poaching operations, ultimately protecting vulnerable animals better. A hypothetical network of anti-poaching technologies was simulated in Graphical Network Simulator 3 (GNS3), consisting of various field devices identified in the literature, and a main control room with relevant hardware devices. A virtual Kali Linux machine was connected to the network and played the role of a digital attacker or intruder. Several cyber-attacks were carried out, to show the risks inherent to such an interoperable and socio-technical network. These attacks included Man in the Middle (MitM) and Denial of Service (DoS) attacks. These attacks were then mitigated via system configurations. Further risks and threat considerations were identified in the literature. Using the STRIDE, DREAD and Attack Tree threat models, the risks to an anti-poaching network were classified and calculated. The most prevalent threats and the attacks performed in the simulation were all calculated to have a high risk level, posing a great threat to an unsecured network. The STRIDE classes of Denial of Service and Elevation of Privilege posed the most risk to the system, both having a calculated average risk score of 9 out of 10. Mitigations to general network threats and those identified in the simulation are mentioned. Additionally, authentication for such a system was investigated, as improper authentication practices were deemed a risk and provides a foothold for further risks in the network. Recommendations made, include the proper configuration of network devices, especially the router and switch, and the use of anti-virus, firewalls, and intrusion detection systems, as well as having an external audit performed annually. Multi-factor authentication, with a password/fingerprint combination, is recommended.

DNS Poisoning of Operating System Caches: Attacks and Mitigations

The Domain Name System (DNS) is a protocol supporting name resolution from Fully Qualified Domain Names (FQDNs) to the IP address of the machines corresponding to them. This resolution process is critical to the operation of the Internet, but is susceptible to a range of attacks. One of the most dangerous attack vectors is DNS poisoning where an attacker injects malicious entries into the DNS resolution forcing clients to be redirected from legitimate to malicious servers. Typically, poisoning attacks target a DNS resolver allowing attackers to poison a DNS entry for all machines that use the compromised resolver. However, recent defenses protect resolvers substantially limiting these attacks. In this paper, we present a new class of DNS poisoning attacks targeting the client-side DNS cache, which is used in mainstream operating systems, circumventing defenses protecting resolvers. We implemented the attack on Windows, Mac OS, and Ubuntu Linux machines. We also generalize the attack to work even when the client is behind a Network Address Translation (NAT) router. Our results show that we can reliably inject malicious DNS mappings, with on average, an order of tens of seconds. We also propose client-side mitigations and demonstrate that they can effectively mitigate the vulnerability.

High-Throughput Fluorescent Pollen Tetrad Analysis Using DeepTetrad.

Meiotic recombination initiates from ~100-200s of programmed DNA double stranded breaks (DSBs) in plants. Meiotic DSBs can be repaired using homologous chromosomes to generate a crossover . Meiotic crossover is critical for chromosomal segregation and increasing genetic variation. The number of crossovers is limited to one and three per chromosome pair in most plant species. Genetic, epigenetic, and environmental factors control crossover frequency and distribution. Due to the limited number of crossovers it is challenging to measure crossover frequency along chromosomes. We adapted fluorescence-tagged lines (FTLs ) that contain quartet1 mutations and linked transgenes expressing dsRed, eYFP, and eCFP in pollen tetrads into the deep learning-based image analysis tool, DeepTetrad. DeepTetrad enables the measurement of crossover frequency and interference by classifying 12 types of tetrads from three-color FTLs in a high-throughput manner, using conventional microscope instruments and a Linux machine. Here, we provide detailed procedures for preparing tetrad samples, tetrad imaging, running DeepTetrad, and analysis of DeepTetrad outputs. DeepTetrad-based measurements of crossover frequency and interference ratio will accelerate the genetic dissection of meiotic crossover control.

Re-Evaluating the Necessity of Third-Party Antivirus Software on Windows Operating System

There is a general assumption that one must purchase costly antivirus software products to defend one’s computer system. However, if one is using the Windows Operating System, the question that arises is whether one needs to purchase antivirus software or not. The Windows operating system has a market share of 31.15% behind Android with a market share of 41.56% worldwide amongst all the operating systems. This makes Windows a prime target for hacking due to its large user base. Windows 11 a recent upgrade to the Windows operating system has claimed to have taken its security to the next level. There is a need to evaluate the capability of the Windows 11 default security against antivirus evasion tools. This research investigated the capability of Windows 11 default security by evaluating it against 6 free and open-source antivirus evasion tools: TheFatRat, Venom, Paygen, Defeat Defender, Inflate and Defender Disabler. The criteria for the selection of the antivirus evasion tools were free and open source and recently updated. A research lab was set up using Oracle VirtualBox where two guest machines were installed: a Windows 11 victim machine and the Kali Linux attacking machine. The antivirus evasion tools were installed on the Kali Linux machine one at a time to generate a malware and pass it to the victim machine. Apache web server was used in holding the malicious sample for the Windows 11 victim machine to download. A score of 2 was awarded to an antivirus evasion tool that successfully evaded the Windows 11 security and created a reverse connection with the attacking machine. From the research results: TheFatRat had a 25% evasion score, Venom had 20% while the rest had a 0% evasion score. None of the payloads generated with the antivirus evasion tools was able to create a connection with the Kali Linux attacking machine. The research results imply that the default Windows 11 security is good enough to stand on its own. A third-party antivirus solution will only supplement the already good protection capability of Windows 11.

Simulator Coupled with Distributed Co-Simulation Protocol for Automated Driving Tests

To meet the challenges in software testing for automated vehicles, such as increasing system complexity and an infinite number of operating scenarios, new simulation methods must be developed. Closed-loop simulations for automated driving (AD) require highly complex simulation models for multiple controlled vehicles with their perception systems as well as their surrounding context. For the realization of such models, different simulation domains must be coupled with co-simulation. However, widely supported model integration standards such as functional mock-up interface (FMI) lack native support for distributed platforms, which is a key feature for AD due to the computational intensity and platform exclusivity of certain models. The newer FMI companion standard distributed co-simulation protocol (DCP) introduces platform coupling but must still be used in conjunction with AD co-simulations. As part of an assessment framework for AD, this paper presents a DCP compliant implementation of an interoperable interface between a 3D environment and vehicle simulator and a co-simulation platform. A universal Python wrapper is implemented and connected to the simulator to allow its control as a DCP slave. A C-code-based interface enables the co-simulation platform to act as a DCP master and to realize cross-platform data exchange and time synchronization of the environment simulation with other integrated models. A model-in-the-loop use case is performed with the traffic simulator CARLA running on a Linux machine connected to the co-simulation master xMOD on a Windows computer via DCP. Several virtual vehicles are successfully controlled by cooperative adaptive cruise controllers executed outside of CARLA. The standard compliance of the implementation is verified by exemplary connection to prototypic DCP solutions from 3rd party vendors. This exemplary application demonstrates the benefits of DCP compliant tool coupling for AD simulation with increased tool interoperability, reuse potential, and performance.

Scalable object detection pipeline for traffic cameras: Application to Tfl JamCams

With CCTV systems being installed in the transport infrastructures of many cities, there is an abundance of data to be extracted from the footage. This paper explores the application of the YOLOv3 object detection algorithm, trained on the COCO dataset, to the Transport for London’s (TfL) JamCam feed. The result, open-sourced and publicly available, is a series of easy to deploy Docker pipelines to create, store and serve (through a REST API) data on identified objects on that feed. The pipelines can be deployed to any Linux machine with an NVIDIA GPU to support accelerated computation. We studied how different confidence thresholds affect detections of relevant objects (cars, trucks and pedestrians) in London JamCam scenes. By running the system continuously for three weeks, we built a dataset of more than 2200 detection datapoints for each camera (~6 datapoints an hour). We further visualized the detections on an animated geospatial map, showcasing their effectiveness in identifying traffic patterns typical of an urban city like London, portraying the variation on different object population levels throughout the day.

A Study of Dark Photon at the Electron-Positron Collider Experiments Using KISTI-5 Supercomputer

The universe is well known to be consists of dark energy, dark matter and the standard model (SM) particles. The dark matter dominates the density of matter in the universe. The dark matter is thought to be linked with dark photon which are hypothetical hidden sector particles similar to photons in electromagnetism but potentially proposed as force carriers. Due to the extremely small cross-section of dark matter, a large amount of data is needed to be processed. Therefore, we need to optimize the central processing unit (CPU) time. In this work, using MadGraph5 as a simulation tool kit, we examined the CPU time, and cross-section of dark matter at the electron-positron collider considering three parameters including the center of mass energy, dark photon mass, and coupling constant. The signal process pertained to a dark photon, which couples only to heavy leptons. We only dealt with the case of dark photon decaying into two muons. We used the simplified model which covers dark matter particles and dark photon particles as well as the SM particles. To compare the CPU time of simulation, one or more cores of the KISTI-5 supercomputer of Nurion Knights Landing and Skylake and a local Linux machine were used. Our results can help optimize high-energy physics software through high-performance computing and enable the users to incorporate parallel processing.

ROS OS based environment mapping of Cyber Physical System Lab by Depth sensor

The 21st century is a century of Robotics and thus the appearance of robots in the industries made the “Industrial Revolution 4.0” in which we can control and analyse the system using HMI’s or wirelessly over network and it’s a great example of industry 4.0 component. Nowadays robots are very important part of industry’s processing unit as they have the tendency to work 24*7 thus increases the efficiency of processing and production unit.
 In our project a depth sensor (Microsoft’s Xbox Kinect) is mounted on a mobile robot whose main task is to map our Cyber Physical System Lab in 3-Dimensional which uses a ROS OS software installed on linux machine.
 The robot will use a Simultaneous localization and mapping (SLAM) process to map an environment while currently generating an estimate for the location of the Robot.

WEB GIS SOLUTION FOR URBAN PLANNING DOCUMENTATION WORKFLOW

The goal of this work is to study the use of WEB GIS open source solution for workflow organizing of urban planning documentation: zoning permit, building permit, occupancy permit, utilities connection. A web GIS solution Giscuit.Com developed by a moldavian company VEC.MD was used as a framework for implementation of test version of a specialized website Primaria.Giscuit.Com. Giscuit is a cost-effective web mapping platform built on powerful, cutting-edge, open source geospatial components. The goal is to make it as easy as possible to build more secure, reliable and modern web GIS applications. With Giscuit users stay in control of their content through centralized management of vector and raster spatial data. Giscuit allows users to visualize, share, edit and analyze geospatial data. It has powerful web-based administrator panel with features like data import, layer styling, user management, permissions management, publishing data and more. It is compliant with the Open Geospatial Consortium standards, this is achieved through OpenLayers or PHP MapScript supporting several OGC standards like WMS, WFS, WMC etc. Giscuit provides a scalable GIS server platform that can be deployed on a single Linux or Microsoft Windows machine, it can be distributed across multiple servers or deployed on cloud infrastructure.

A Multi Platform for Utility using openFMBTM Reference Architecture: Chalenges and Lessons Learned

The exponential growth of smart micro grids is making centralized control unmanageable. Data generated by grid-edge devices are also inaccessible due to the installation of private micro grids with proprietary communication protocols. The OpenFMBTM reference architecture solves this interoperability issue and eases the manageability of huge data by creating a virtual node that would allow exchange information between field devices with the use of publish/subscribe paradigm. However, the OpenFMBTM framework is yet to be adopted by industries but researches related to the implementation of this framework is being conducted with the aim to find out the cost and reliability on performance issues such as accuracy, scalability and security. Smart Grid Interoperability Panel (SGIP) provided a live demonstration of OpenFMBTM framework at DistribuTECH conference. DistribuTECH demo provides a guideline to setup simulators deployed in a single Linux machine. This paper discusses about the simulation demo and lessons learned to further developing the project. The implemented demo focuses on the use of MQTT communication protocol for transport layer data transfer. The experiment uses the guidelines of the DistribuTECH demo and addresses the challenge of deploying the framework in real devices at industry level.

Open Universe for Blazars: a new generation of astronomical products based on 14 years ofSwift-XRT data

Aims.Open Universe for Blazars is a set of high-transparency multi-frequency data products for blazar science, and the tools designed to generate them. Blazars are drawing growing interest following the consolidation of their position as the most abundant type of source in the extragalactic very high-energyγ-ray sky, and because of their status as prime candidate sources in the nascent field of multi-messenger astrophysics. As such, blazar astrophysics is becoming increasingly data driven, depending on the integration and combined analysis of large quantities of data from the entire span of observational astrophysics techniques. The project was therefore chosen as one of the pilot activities within the United Nations Open Universe Initiative, whose objective is to stimulate a large increase in the accessibility and ease of utilisation of space science data for the worldwide benefit of scientific research, education, capacity building, and citizen science.Methods.Our aim is to deliver innovative data science tools for multi-messenger astrophysics. In this work we report on a data analysis pipeline calledSwift-DeepSky based on theSwiftXRTDAS software and the XIMAGE package, encapsulated into a Docker container.Swift-DeepSky downloads and reads low-level data, generates higher level products, detects X-ray sources, and estimates several intensity and spectral parameters for each detection, thus facilitating the generation of complete and up-to-date science-ready catalogues from an entire space-mission data set.Results.As a first application of our innovative approach, we present the results of a detailed X-ray image analysis based onSwift-DeepSky that was run on allSwift-XRT observations including a known blazar, carried out during the first 14 years of operations of theNeil Gehrels SwiftObservatory. Short exposures executed within one week of each other have been added to increase sensitivity, which ranges between ∼1 × 10−12and ∼1 × 10−14erg cm−2s−1(0.3–10.0 keV). After cleaning for problematic fields, the resulting database includes over 27 000 images integrated in different X-ray bands, and a catalogue, called 1OUSXB, that provides intensity and spectral information for 33 396 X-ray sources, 8896 of which are single or multiple detections of 2308 distinct blazars. All the results can be accessed online in a variety of ways, from the Open Universe portal through Virtual Observatory services, via the VOU-Blazar tool and the SSDC SED builder. One of the most innovative aspects of this work is that the results can be easily reproduced and extended by anyone using the Docker version of theSwift-DeepSky pipeline, which runs on Linux, Mac, and Windows machines, and does not require any specific experience in X-ray data analysis.

IoT Based Occupancy Detection using Wireless Controller in a Building/Workspace

Occupancy of seats/chairs in places like cafeteria, occupancy in meeting room is a key factor in offices having thousands of employees, it is often convenient to know the number of seats occupied in cafeteria and availability of meeting room in IT companies before he/she visits. There is an IoT wave sweeping the technology arena. Internet of Things (IoT) is the amalgamation of all physical nodes using internet as medium. The nodes communicate with each other over internet and allows to control or get controlled by the click of a button. Various sensor in the market can detect occupancy of the seat and the meeting room with low cost systems. The objective of the present paper is to study number of people occupied the seats in cafeteria and displayed occupied and unoccupied seats on web browser for user information, collecting those data for some period and use the data to display seat occupancy at different points of time. The above objective is achieved using shell scripts running on linux machine used to simulate the occupancy of chairs/seats in cafeteria and occupancy of meeting rooms which is communicated to webserver via IoT.

GeoEasy an open source project for surveying calculations

The development of the GeoEasy program started in 1997. Twenty years later in 2017 it became free software under GPL license, version 3.0.0 is freely available for everybody. The core development of GeoEasy is made on Linux operating system, using Tcl/Tk script language, thanks to the Tcl/Tk ports to other operating systems, the program can be run on Linux, Windows, Android and OSX machines. Objectives of the development are to create user friendly graphical user interface (GUI) for surveying calculations in a modular structure with flexible, open connections to other programs. Both educational and professional usages are supported.

RSEQREP: RNA-Seq Reports, an open-source cloud-enabled framework for reproducible RNA-Seq data processing, analysis, and result reporting.

RNA-Seq is increasingly being used to measure human RNA expression on a genome-wide scale. Expression profiles can be interrogated to identify and functionally characterize treatment-responsive genes. Ultimately, such controlled studies promise to reveal insights into molecular mechanisms of treatment effects, identify biomarkers, and realize personalized medicine. RNA-Seq Reports (RSEQREP) is a new open-source cloud-enabled framework that allows users to execute start-to-end gene-level RNA-Seq analysis on a preconfigured RSEQREP Amazon Virtual Machine Image (AMI) hosted by AWS or on their own Ubuntu Linux machine via a Docker container or installation script. The framework works with unstranded, stranded, and paired-end sequence FASTQ files stored locally, on Amazon Simple Storage Service (S3), or at the Sequence Read Archive (SRA). RSEQREP automatically executes a series of customizable steps including reference alignment, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially expressed genes, heatmaps, co-expressed gene clusters, enriched pathways, and a series of custom visualizations. The framework outputs a file collection that includes a dynamically generated PDF report using R, knitr, and LaTeX, as well as publication-ready table and figure files. A user-friendly configuration file handles sample metadata entry, processing, analysis, and reporting options. The configuration supports time series RNA-Seq experimental designs with at least one pre- and one post-treatment sample for each subject, as well as multiple treatment groups and specimen types. All RSEQREP analyses components are built using open-source R code and R/Bioconductor packages allowing for further customization. As a use case, we provide RSEQREP results for a trivalent influenza vaccine (TIV) RNA-Seq study that collected 1 pre-TIV and 10 post-TIV vaccination samples (days 1-10) for 5 subjects and two specimen types (peripheral blood mononuclear cells and B-cells).

RSEQREP: RNA-Seq Reports, an open-source cloud-enabled framework for reproducible RNA-Seq data processing, analysis, and result reporting

RNA-Seq is increasingly being used to measure human RNA expression on a genome-wide scale. Expression profiles can be interrogated to identify and functionally characterize treatment-responsive genes. Ultimately, such controlled studies promise to reveal insights into molecular mechanisms of treatment effects, identify biomarkers, and realize personalized medicine. RNA-Seq Reports (RSEQREP) is a new open-source cloud-enabled framework that allows users to execute start-to-end gene-level RNA-Seq analysis on a preconfigured RSEQREP Amazon Virtual Machine Image (AMI) hosted by AWS or on their own Ubuntu Linux machine via a Docker container or installation script. The framework works with unstranded, stranded, and paired-end sequence FASTQ files stored locally, on Amazon Simple Storage Service (S3), or at the Sequence Read Archive (SRA). RSEQREP automatically executes a series of customizable steps including reference alignment, CRAM compression, reference alignment QC, data normalization, multivariate data visualization, identification of differentially expressed genes, heatmaps, co-expressed gene clusters, enriched pathways, and a series of custom visualizations. The framework outputs a file collection that includes a dynamically generated PDF report using R, knitr, and LaTeX, as well as publication-ready table and figure files. A user-friendly configuration file handles sample metadata entry, processing, analysis, and reporting options. The configuration supports time series RNA-Seq experimental designs with at least one pre- and one post-treatment sample for each subject, as well as multiple treatment groups and specimen types. All RSEQREP analyses components are built using open-source R code and R/Bioconductor packages allowing for further customization. As a use case, we provide RSEQREP results for a trivalent influenza vaccine (TIV) RNA-Seq study that collected 1 pre-TIV and 10 post-TIV vaccination samples (days 1-10) for 5 subjects and two specimen types (peripheral blood mononuclear cells and B-cells).