Command Line Interface Research Articles

A Brain Controlled Command-Line Interface to Enhance the Accessibility of Severe Motor Disabled People to Personnel Computer.

There are many applications controlled by the brain signals to bridge the gap in the digital divide between the disabled and the non-disabled people. The deployment of novel assistive technologies using brain-computer interface (BCI) will go a long way toward achieving this lofty goal, especially after the successes demonstrated by these technologies in the daily life of people with severe disabilities. This paper contributes in this direction by proposing an integrated framework to control the operating system functionalities using Electroencephalography signals. Different signal processing algorithms were applied to remove artifacts, extract features, and classify trials. The proposed approach includes different classification algorithms dedicated to detecting the P300 responses efficiently. The predicted commands passed through a socket to the API system, permitting the control of the operating system functionalities. The proposed system outperformed those obtained by the winners of the BCI competition and reached an accuracy average of 94.5% according to the offline approach. The framework was evaluated according to the online process and achieved an excellent accuracy attaining 97% for some users but not less than 90% for others. The suggested framework enhances the information accessibility for people with severe disabilities and helps them perform their daily tasks efficiently. It permits the interaction between the user and personal computers through the brain signals without any muscular efforts.

Liquid nitrogen cooling, control and monitoring system for the ELIADE HPGe clover detectors at ELI-NP

We present a liquid nitrogen (LN2) cooling station for the high-purity germanium (HPGe) segmented clover detectors of the ELI-NP Array of DEtectors (ELIADE) spectrometer, including its associated filling control and monitoring systems, all designed and built in-house at Extreme Light Infrastructure - Nuclear Physics (ELI-NP), Măgurele, Romania. The automated LN2 filling process is controlled by a CompactRIO (cRIO) system from National Instruments through a custom LabVIEW software used for monitoring both the internal germanium crystal temperatures as well as the temperatures of external Pt100 sensors (used for detection of overflow of LN2 from detectors during a filling process). The detectors are filled with LN2 by opening their individual filling valves (which are mounted on the cooling station) and the process is automatically stopped once an overflow condition is fulfilled by the corresponding external Pt100 sensor located downstream. A twelve-hour cycle is used to periodically fill all of the detector dewars and keep their germanium crystals cool at all times. The associated Graphic User Interface (GUI), Command Line Interface (CLI) and Text User Interface (TUI) are used for both controlling and monitoring the above mentioned process. Alert and warning email messages were also enabled via the cRIO system so that users can be alerted in real-time in the event of any cooling malfunction. In this way, any issues related to the cyclic filling procedure, as well as any abnormal observations regarding the germanium crystal temperatures can be quickly and efficiently addressed before the detectors have a chance to warm back up to room temperature. Temperature data of all the Pt100 sensors corresponding to detectors as well as to the solenoid valves are made available in an influx database by the cRIO control system. The web application Grafana access the database and plots them in real-time for online monitoring.

A STUDY ON MATLAB GUI BY USING BINARY BASEBAND COMMUNICATION SYSTEM

This paper presents the MATLAB Graphical User Interface (GUI) mainly used in digital communication and electromagnetics. GUI is powerful tool which is available on MATLAB. It is basically used to design app, which can share live script with others via MATLAB Offline or Online. The MATLAB GUI used to design modules which results in simulation of baseband digital communication system and determines transmission of the Binary Phase Shift Keying signal (BPSK) amid Additive white Gaussian noise (AWGN) channel along with tone jamming background. To reduce the effect of jamming, digital notch filter at the receiver are used. The results of the simulated design modules shows the dissimilarities of the signal corresponding on every section of the communication system. A comparative analysis is done based on illustrated figure. This research also shows the observation and tests by using GUI requires less time as compared to command line interface (CLI) version.

Open Loop Automated Baby Cradle Using Dobot Magician and C#

Purpose: We are all busy, especially those responsible for family expenditure. We have lots of pressure in our workspace. Some employees are still doing work from home. Family being converted into an office as well. The problem arises when our small kids cry during a scheduled meeting. Sometimes need someone who can swing the baby’s cradle. Here we demonstrated an automated baby cradle which is useful when our baby cries. We can put our kids into the robotic cradle and engage in other work. When the baby cries, we trigger the run button from our working PC/Laptop, and the cradle starts to swing automatically. Here we used Dobot Magician for this purpose, a famous robot in the education and research sector due to its cost-effectiveness. To drive the robot, we developed an application in C#. It is a small program that is used to swing the cradle. Here we move the robot by the program. So we can change the program quickly, so our sweetheart feels more comfortable inside the cradle. The entire project source code is available on Github. Anyone downloading the project can integrate, test, and continue further improvement. Design/Methodology/Approach: In our research, we used the Dobot magician robot to swing the cradle. One support-like stick is connected between the robot and the cradle to push the cradle. The robot is driven by the program written inside the programming area. The original API is a little bit programming specific. So we provided intermediate programming space to write code as our understandable language. The complete application is developed using the C# language under Microsoft visual studio 2022. We used the vendor-provided dynamic link library to send the command to the robot to reduce development time. Findings/Result: We can integrate the Dobot magician robot into our custom project after developing the complete system. The movement pattern can be changed by changing the program, which may be used for different task execution utilizing the robot. The IDE can also be used for other robots, like UARM metal, a 3D printer, etc. Under the code, any robot can be operated using this interface. It has a programming interface, as well as a command-line interface. We can test, debug and experiment as well. Originality/Value: We created our application in C#, a modern, easy and flexible language. The IDE has lots of scope for experiments. The program has very easy to understand. We use the robot to swing the cradle for flexibility in nature. We can change the swings pattern by changing the parameter value, which is impossible in fixed monotonous movement. This can give us a unique feature than most other available procedures to swing the cradle. Paper Type: Experimental-based Research.

TIMSCONVERT: a workflow to convert trapped ion mobility data to open data formats.

Advances in mass spectrometry have led to the development of mass spectrometers with ion mobility spectrometry capabilities and dual-source instrumentation; however, the current software ecosystem lacks interoperability with downstream data analysis using open-source software and pipelines. Here, we present TIMSCONVERT, a data conversion high-throughput workflow from timsTOF Pro/fleX mass spectrometer raw data files to mzML and imzML formats that incorporates ion mobility data while maintaining compatibility with data analysis tools. We showcase several examples using data acquired across different experiments and acquisition modalities on the timsTOF fleX MS. TIMSCONVERT and its documentation can be found at https://github.com/gtluu/timsconvert and is available as a standalone command-line interface tool for Windows and Linux, NextFlow workflow and online in the Global Natural Products Social (GNPS) platform. Supplementary data are available at Bioinformatics online.

Design of Three Class Internet Protocol Routing Model Based on Linux Command Line Interface

The world of information technology is currently experiencing very rapid development, especially in internet technology. The Internet itself is a form of utilization of a computer network system, a computer network system consisting of a group of computer systems and other computing hardware linked together through communication channels to facilitate communication and resource sharing among various users. TCP / IP is a standard protocol that is applied to the internet network. The existence of a router in a TCP/IP network is very important, this is due to the large number of hosts and the differences in the devices used on a TCP/IP network. Router is a computer network device that is used to forward data packets from one network to another, both within the scope of LAN and WAN networks (Yani A., 2008). As a result, a routing mechanism is needed that can integrate many users with a high degree of flexibility. Routing is generally divided into two categories, namely static routing and dynamic routing. Static routing is a routing mechanism that depends on the routing table with manual configuration while dynamic routing is a routing mechanism where the routing table exchange between routers on the network is carried out dynamically. Routing in the world of information technology (IT) is part of how to improve network performance. Routing is a process to choose the path (path) traversed by the packet. Routing itself is very instrumental in building a network, be it LAN or WAN. Currently the use of routing in a network is something that needs to be taken into account in a company. Today's companies that have business processes in the IT sector are very dependent on network availability. Network reliability is the main point in the operation of the system. An adequate and reliable network infrastructure is very much needed by the company, especially regarding the company's electability. Companies that have large-scale networks need several techniques so that the network can work optimally and reliably in overcoming various problems that arise, including network connectivity that is still not stable and link redundancy has not been implemented as a backup path to overcome network failures if interference occurs. alternative network paths that are used to increase network availability, so that if there is a broken link in a network, the data path can still be connected without affecting the connectivity of devices on the network

MoloVol: an easy-to-use program for analyzing cavities, volumes and surface areas of chemical structures.

Cavities are a ubiquitous feature of chemical structures encountered in various fields ranging from supramolecular chemistry to molecular biology. They are involved in the encapsulation, transport and transformation of guest molecules, thus necessitating a precise and accessible tool for estimating and visualizing their size and shape. MoloVol, a free user-parametrizable open-source software, developed for calculating a range of geometric features for both unit-cell and isolated structures, is presented here. MoloVol utilizes up to two spherical probes to define cavities, surfaces and volumes. The program was optimized by combining an octree data structure with voxel-partitioned space, allowing for even high-resolution protein structure calculations on reasonable timescales. MoloVol comes with a user-friendly graphic interface along with a command-line interface for high-throughput calculations. It was written in C++ and is available on Windows, macOS and Linux distributions.

CircPrimer 2.0: a software for annotating circRNAs and predicting translation potential of circRNAs

BackgroundSome circular RNAs (circRNAs) can be translated into functional peptides by small open reading frames (ORFs) in a cap-independent manner. Internal ribosomal entry site (IRES) and N6-methyladenosine (m6A) were reported to drive translation of circRNAs. Experimental methods confirming the presence of IRES and m6A site are time consuming and labor intensive. Lacking computational tools to predict ORFs, IRESs and m6A sites for circRNAs makes it harder.ResultsIn this report, we present circPrimer 2.0, a Java based software for annotating circRNAs and predicting ORFs, IRESs, and m6A sites of circRNAs. circPrimer 2.0 has a graphical and a command-line interface that enables the tool to be embed into an analysis pipeline.Conclusionscircprimer 2.0 is an easy-to-use software for annotating circRNAs and predicting translation potential of circRNAs, and freely available at www.bio-inf.cn.

WEBSCAF

Abstract: This is a project that mainly concerns web developers' areas of interest. While creating a project developers face the problem of scaffolding and especially doing it the right way is another major task that needs to be accomplished. It is a NodeJSbased project through which a fresh project structure can be created with the help of the Command Line Interface. Setting up a new project may require setting up various folders which might get hectic hence this project is a perfect solution as it performs scaffolding with the help of a few CLI commands. The idea of creating such a project hit the minds of our team while building other web projects during our bachelor's in technology. This project is an operating system independent product that can be used on any machine with any operating system like Windows, Linux, Mac, etc. The pre-requisite of this project is that Node.JS should be installed in the device on which the product has to be used. NodeJS is an open-source server environment that helps to run JavaScript on the server.

FragGeneScanRs: faster gene prediction for short reads

BackgroundFragGeneScan is currently the most accurate and popular tool for gene prediction in short and error-prone reads, but its execution speed is insufficient for use on larger data sets. The parallelization which should have addressed this is inefficient. Its alternative implementation FragGeneScan+ is faster, but introduced a number of bugs related to memory management, race conditions and even output accuracy.ResultsThis paper introduces FragGeneScanRs, a faster Rust implementation of the FragGeneScan gene prediction model. Its command line interface is backward compatible and adds extra features for more flexible usage. Its output is equivalent to the original FragGeneScan implementation.ConclusionsCompared to the current C implementation, shotgun metagenomic reads are processed up to 22 times faster using a single thread, with better scaling for multithreaded execution. The Rust code of FragGeneScanRs is freely available from GitHub under the GPL-3.0 license with instructions for installation, usage and other documentation (https://github.com/unipept/FragGeneScanRs).

The data analysis and validation engine: an application of artificial intelligence in the improvement of COVID-19 data management

Background: The proper management of healthcare data is fundamental to the health system processes; artificial intelligence has proven its value in these processes. Artificial intelligence can simplify the management of information, improve data security, and automate data flow. It is also useful in the analysis and interpretation of big data. Hence, it has the possibility of screening and diagnosing diseases, categorizing disease severity, detecting therapeutic agents, and forecasting outbreak spots.Methods: A data analysis and validation engine was developed to perform data quality control checks, classify addresses, and generate epidemiology numbers using the index and parse command on the command-line interface of DAVE.Results: DAVE correctly formatted data and created a local copy of the datastore and the index. It also returned previous EPID numbers to each entry and assigned a new EPID number to missed entries. DAVE imported the entries into the data template of the existing data management tool and generated a sample manifest that is then sent to the Laboratory. The data flow from the point of collection to storage and reporting was assessed as 100% accurate without errors and in real-time; there was also the ability to roll back if any error occurred.Conclusions: DAVE is a semi-autonomous system that operates with minimal human intervention; it is automatically faster as it leverages computing power to parse, store, and retrieve data while practically eliminating the need for manual data quality assessment. The DAVE functionality can be extended to incorporate additional features like forecasting outbreaks of emerging/re-emerging diseases, categorizing the severity of diseases and analysis of data in our setting.

TextFormats: Simplifying the definition and parsing of text formats in bioinformatics.

Text formats are common in bioinformatics, as they allow for editing and filtering using standard tools, as well as, since text formats are often human readable, manual inspection and evaluation of the data. Bioinformatics is a rapidly evolving field, hence, new techniques, new software tools, new kinds of data often require the definition of new formats. Often new formats are not formally described in a standard or specification document. Although software libraries are available for accessing the most common formats, writing parsers for text formats, for which no library is currently available, is a very common though tedious task, utilized by many researchers in the field. This manuscript presents the open source software library and toolset TextFormats (available at https://github.com/ggonnella/textformats), which aims at simplifying the definition and parsing of text formats. Formats specifications are written in a simple data description format using an interactive wizard. Automatic generation of data examples and automatic testing of specifications allow for checking for correctness. Given the specification for a text format, TextFormats allows parsing and writing data in that format, using several programming languages (Nim, Python, C/C++) or the provided command line and graphical user interface tools. Although designed as a general purpose software, the main target application field, for the above mentioned reasons, is expected to be in bioinformatics: Thus, the specifications of several common existing bioinformatics formats are included.

IFeatureOmega: an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets.

The rapid accumulation of molecular data motivates development of innovative approaches to computationally characterize sequences, structures and functions of biological and chemical molecules in an efficient, accessible and accurate manner. Notwithstanding several computational tools that characterize protein or nucleic acids data, there are no one-stop computational toolkits that comprehensively characterize a wide range of biomolecules. We address this vital need by developing a holistic platform that generates features from sequence and structural data for a diverse collection of molecule types. Our freely available and easy-to-use iFeatureOmega platform generates, analyzes and visualizes 189 representations for biological sequences, structures and ligands. To the best of our knowledge, iFeatureOmega provides the largest scope when directly compared to the current solutions, in terms of the number of feature extraction and analysis approaches and coverage of different molecules. We release three versions of iFeatureOmega including a webserver, command line interface and graphical interface to satisfy needs of experienced bioinformaticians and less computer-savvy biologists and biochemists. With the assistance of iFeatureOmega, users can encode their molecular data into representations that facilitate construction of predictive models and analytical studies. We highlight benefits of iFeatureOmega based on three research applications, demonstrating how it can be used to accelerate and streamline research in bioinformatics, computational biology, and cheminformatics areas. The iFeatureOmega webserver is freely available at http://ifeatureomega.erc.monash.edu and the standalone versions can be downloaded from https://github.com/Superzchen/iFeatureOmega-GUI/ and https://github.com/Superzchen/iFeatureOmega-CLI/.

Mamba: a systematic software solution for beamline experiments at HEPS.

To cater for the diverse experiment requirements at the High Energy Photon Source (HEPS) with often limited human resources, Bluesky was chosen as the basis for our software framework, Mamba. In our attempt to address Bluesky's lack of integrated graphical user interfaces (GUIs), command injection with feedback was chosen as the main way for the GUIs to cooperate with the command line interface; a remote-procedure-call service is also provided, which covers functionalities unsuitable for command injection, as well as pushing of status updates. In order to fully support high-frequency applications like fly scans, Bluesky's support for asynchronous control is being improved; furthermore, to support high-throughput experiments, Mamba Data Worker is being developed to cover the complexity in asynchronous online data processing for these experiments. To systematically simplify the specification of metadata, scan parameters and data-processing graphs for each type of experiment, an experiment parameter generator will be developed; experiment-specific modules to automate preparation steps will also be made. The integration of off-the-shelf code in Mamba for domain-specific needs is under investigation, and Mamba GUI Studio is being developed to simplify the implementation and integration of GUIs.

MATLAB toolbox for ROC analysis of multi-reader multi-case diagnostic imaging studies.

A common study design for comparing the performances of diagnostic imaging tests is to obtain ratings from multiple readers of multiple cases whose true statuses are known. Typically, there is overlap between the tests, readers, and/or cases for which special analytical methods are needed to perform statistical comparisons. We present our new MATLAB MRMCaov toolbox, which is designed for multi-reader multi-case comparisons of two or more diagnostic tests. The toolbox allows for statistical comparison of reader performance metrics, such as area under the receiver operating characteristic curve (ROC AUC), with analysis of variance methods originally proposed by Obuchowski and Rockette (1995) and later unified and improved by Hillis and colleagues (2005, 2007, 2008, 2018). MRMCaov is open-source software with an integrated command-line interface for performing multi-reader multi-case statistical analysis, plotting, and presenting results. Its features (1) ROC AUC, likelihood ratios of positive or negative ratings, sensitivity, specificity, and expected utility reader performance metrics; (2) reader-specific ROC curves; (3) user-definable performance metrics; (4) test-specific estimates of mean performance along with confidence intervals and p-values for statistical comparisons; (5) support for factorial, nested, or partially paired study designs; (6) inference for random or fixed readers and cases; (7) DeLong, jackknife, or unbiased covariance estimation; and (8) compatibility with Microsoft Windows, Mac OS, and Linux.

SRS-based Timepix3 readout system

With the combination of the highly granular pixel ASIC Timepix3 by the Medipix3 collaboration and several technologies we are developing a range of detectors. These technologies are bump bonded sensors, microchannel plates (MCP) and photolithographically postprocessed gas amplification stages (InGrid). For example, we are using the combination of the ASIC and an InGrid for the development of X-ray detectors for X-ray polarimetry and for axion search at IAXO. Based on the combination of the ASIC and silicon sensors we are developing a tracker or respectively a beam telescope. The combination of the ASIC and a microchannel plate will be used for neutron detectors. As this range of detectors has several requirements towards the readout and control system and a wide range of designs from low- to high-rate (Hz to MHz) and from single- to multichip, a versatile readout system is needed which adapts these applications without producing too much overhead for the others. To fulfil these requirements, we are developing a modular and scalable readout and control system based on the basil framework — a modular data acquisition system and system testing framework. The fully open-source implementation uses Verilog for the firmware and Python for the software. The system supports several FPGA boards to offer different applications a range of capabilities. One of these FPGA boards is the Scalable Readout System (SRS) by RD51 which offers scalability in low to medium rate applications. For high-rate applications we are working towards the firmware implementation on Xilinx adaptive compute acceleration platform. Besides the scalability, the system offers an optional monitoring interface via a microcontroller for monitoring chip temperatures and power supply voltages. Additionally, further external sensors could be connected to the monitoring system for example via I2C or SPI. For controlling the full system, the software offers a command line interface and a graphical user interface. Both interfaces also include an online event display to monitor the raw data. Additional meta data and data of the monitoring system is stored in a database and can be visualised with a monitoring dashboard.

AutoSolvate: A toolkit for automating quantum chemistry design and discovery of solvated molecules.

The availability of large, high-quality datasets is crucial for artificial intelligence design and discovery in chemistry. Despite the essential roles of solvents in chemistry, the rapid computational dataset generation of solution-phase molecular properties at the quantum mechanical level of theory was previously hampered by the complicated simulation procedure. Software toolkits that can automate the procedure to set up high-throughput explicit-solvent quantum chemistry (QC) calculations for arbitrary solutes and solvents in an open-source framework are still lacking. We developed AutoSolvate, an open-source toolkit, to streamline the workflow for QC calculation of explicitly solvated molecules. It automates the solvated-structure generation, force field fitting, configuration sampling, and the final extraction of microsolvated cluster structures that QC packages can readily use to predict molecular properties of interest. AutoSolvate is available through both a command line interface and a graphical user interface, making it accessible to the broader scientific community. To improve the quality of the initial structures generated by AutoSolvate, we investigated the dependence of solute-solvent closeness on solute/solvent identities and trained a machine learning model to predict the closeness and guide initial structure generation. Finally, we tested the capability of AutoSolvate for rapid dataset curation by calculating the outer-sphere reorganization energy of a large dataset of 166 redox couples, which demonstrated the promise of the AutoSolvate package for chemical discovery efforts.

DeepSpectrumLite: A Power-Efficient Transfer Learning Framework for Embedded Speech and Audio Processing From Decentralized Data.

Deep neural speech and audio processing systems have a large number of trainable parameters, a relatively complex architecture, and require a vast amount of training data and computational power. These constraints make it more challenging to integrate such systems into embedded devices and utilize them for real-time, real-world applications. We tackle these limitations by introducing DeepSpectrumLite, an open-source, lightweight transfer learning framework for on-device speech and audio recognition using pre-trained image Convolutional Neural Networks (CNNs). The framework creates and augments Mel spectrogram plots on the fly from raw audio signals which are then used to finetune specific pre-trained CNNs for the target classification task. Subsequently, the whole pipeline can be run in real-time with a mean inference lag of 242.0 ms when a DenseNet121 model is used on a consumer-grade Motorola moto e7 plus smartphone. DeepSpectrumLite operates decentralized, eliminating the need for data upload for further processing. We demonstrate the suitability of the proposed transfer learning approach for embedded audio signal processing by obtaining state-of-the-art results on a set of paralinguistic and general audio tasks, including speech and music emotion recognition, social signal processing, COVID-19 cough and COVID-19 speech analysis, and snore sound classification. We provide an extensive command-line interface for users and developers which is comprehensively documented and publicly available at https://github.com/DeepSpectrum/DeepSpectrumLite.

Two-loop prediction of the anomalous magnetic moment of the muon in the Two-Higgs Doublet Model with GM2Calc 2

We present an extension of the GM2Calc software to calculate the muon anomalous magnetic moment ({a_mu ^{{text {BSM}}}}) in the Two-Higgs Doublet Model. The Two-Higgs Doublet Model is one of the simplest and most popular extensions of the Standard Model. It is one of the few single field extensions that can give large contributions to {a_mu ^{{text {BSM}}}}. It is essential to include two-loop corrections to explain the long standing discrepancy between the Standard Model prediction and the experimental measurement in the Two-Higgs Doublet Model. The new version GM2Calc 2 implements the state of the art two-loop calculation for the general, flavour violating Two-Higgs Doublet Model as well as for the flavour aligned Two-Higgs Doublet Model and the type I, II, X and Y flavour conserving variants. Input parameters can be provided in either the gauge basis or the mass basis, and we provide an easy to use SLHA-like command-line interface to specify these. Using this interface users may also select between Two-Higgs Doublet Model types and choose which contributions to apply. In addition, GM2Calc 2 also provides interfaces in C++, C, Python and Mathematica, to make it easy to interface with other codes.

The Neuroimaging Data Model Linear Regression Tool (nidm_linreg): PyNIDM Project

The Neuroimaging Data Model (NIDM) is a series of specifications for describing all aspects of the neuroimaging data lifecycle from raw data to analyses and provenance. NIDM uses community-driven terminologies along with unambiguous data dictionaries within a Resource Description Framework (RDF) document to describe data and metadata for integration and query. Data from different studies, using locally defined variable names, can be retrieved by linking them to higher-order concepts from established ontologies and terminologies. Through these capabilities, NIDM documents are expected to improve reproducibility and facilitate data discovery and reuse. PyNIDM is a Python toolbox supporting the creation, manipulation, and querying of NIDM documents. Using the query tools available in PyNIDM, users are able interrogate datasets to find studies that have collected variables measuring similar phenotypic properties. This, in turn, facilitates the transformation and combination of data across multiple studies. The focus of this manuscript is the linear regression tool which is a part of the PyNIDM toolbox and works directly on NIDM documents. It provides a high-level statistical analysis that aids researchers in gaining more insight into the data that they are considering combining across studies. This saves researchers valuable time and effort while showing potential relationships between variables. The linear regression tool operates through a command-line interface integrated with the other tools (pynidm linear-regression) and provides the user with the opportunity to specify variables of interest using the rich query techniques available for NIDM documents and then conduct a linear regression with optional contrast and regularization.