Use Of Files Research Articles

VDefender: An explainable and introspection-based approach for identifying emerging malware behaviour at hypervisor-layer in virtualization environment

Virtualization can be defined as the backbone of cloud computing services, which has gathered significant attention from organizations and users. Due to the increasing number of cyberattacks, virtualization security has become a crucial area of study. In this paper, we propose an explainable and introspection-based malware detection approach called vDefender for fine-grain monitoring of virtual machine (VM) processes at the hypervisor to identify the malicious behaviour of 17 different malware families of Windows exhibiting new evolving behaviour. Initially, it performs a basic security check to detect hidden processes and ensures the presence of security-critical processes. Then, deep memory introspection is performed using a software breakpoints injection approach to intercept the execution of processes. Various process activity logs are captured that include process-related, file manipulation, kernel heap object creation, exception-related activities, etc. Hybrid feature vectors are derived from these logs, which are reconstructed using the proposed mechanism to eliminate the redundant behaviour. The features are then learnt using Random Forest (RF) algorithm to classify distinct malware families. The interpretation and analysis of RF results involve the use of explainability techniques. The proposed approach achieves an accuracy of 95.49%, F1-score of 95.82% with 0.05% false alarms when evaluated using an emerging malware dataset. The contribution includes a comprehensive discussion of results, accompanied by a comparative analysis of current approaches that gives readers insight towards future research directions.

Customized Virtual File System

Customized Virtual File System

The Site/Group Extended Data Format and Tools.

Comparative sequence analysis permits unraveling the molecular processes underlying gene evolution. Many statistical methods generate candidate positions within genes, such as fast or slowly evolving sites, coevolving groups of residues, sites undergoing positive selection, or changes in evolutionary rates. Understanding the functional causes of these evolutionary patterns requires combining the results of these analyses and mapping them onto molecular structures, a complex task involving distinct coordinate referential systems. To ease this task, we introduce the site/group extended data format, a simple text format to store (groups of) site annotations. We developed a toolset, the SgedTools, which permits site/group extended data file manipulation, creating them from various software outputs and translating coordinates between individual sequences, alignments, and three-dimensional structures. The package also includes a Monte-Carlo procedure to generate random site samples, possibly conditioning on site-specific features. This eases the statistical testing of evolutionary hypotheses, accounting for the structural properties of the encoded molecules.

Machine Learning Approaches to Malicious PowerShell Scripts Detection and Feature Combination Analysis

<p>With advances in communication technology, modern society relies more than ever on the Internet and various user-friendly digital tools. It provides access to and enables the manipulation of files, trips, and the Windows API. Attackers frequently use various obfuscation techniques PowerShell scripts to avoid detection by anti-virus software. Their doing so can significantly reduce the readability of the script. This work statically analyzes PowerShell scripts. Thirty-three features that were based on the script’s keywords, format, and string combinations were used herein to determine the behavioral intent of the script. Ones are characteristic-based features that are obtained by calculation; the others are behavior-based features that determine the execution function of behavior using keywords and instructions. Behavior-based features can be divided into positive behavior-based features, neutral behavior-based features, and negative behavior-based features. These three types of features are enhanced by observing samples and adding keywords. The other type of characteristic-based feature is introduced into the formula from other studies in this work. The XGBoost model was used to evaluate the importance of the features that are proposed in this study and to identify the combination of features that contributed most to the detection of PowerShell scripts. The final model with the combined features is found to exhibit the best performance. The model has 99.27% accuracy when applied to the validation dataset. The results clearly indicate that the proposed malicious PowerShell script detection model outperforms previously developed models.</p> <p> </p>

Automation of Seating Plan for Examinations using Round-Robin Policy

Abstract: This paper introduces a Python-based Graphical User Interface (GUI) application designed to automate the seating arrangement process for examinations, specifically catering to the needs of examination departments. Leveraging the openpyxl and pandas libraries for Excel file manipulation and creating Dataframes the application aims to replace the laborious manual process traditionally employed by colleges. The main objective is to reduce the time and effort invested by examination departments in seating arrangement tasks. The user-friendly GUI simplifies data input, while the application's algorithm automates seating assignments, ensuring that no two students writing same exam can’t sit in same bench in optimal manner using excel and python . Results demonstrate a significant reduction in time spent on seating arrangement, with outputs including detailed room-wise seating sheets and comprehensive summaries listing roll numbers by regulation and branch. This innovative approach not only streamlines examination management but also enhances accuracy and efficiency.From this GUI we can add, edit and delete the halls in which the exams are being conducted.Further we input the excel sheet in which the roll numbers of students were there as per their branch and regulation as input and genrates formatted excel sheets that generate seating arrangement .Formatting the font and size of rows and columns and wrapping the columns when required are done automatically

Computational Tools for Handling Molecular Clusters: Configurational Sampling, Storage, Analysis, and Machine Learning.

Computational modeling of atmospheric molecular clusters requires a comprehensive understanding of their complex configurational spaces, interaction patterns, stabilities against fragmentation, and even dynamic behaviors. To address these needs, we introduce the Jammy Key framework, a collection of automated scripts that facilitate and streamline molecular cluster modeling workflows. Jammy Key handles file manipulations between varieties of integrated third-party programs. The framework is divided into three main functionalities: (1) Jammy Key for configurational sampling (JKCS) to perform systematic configurational sampling of molecular clusters, (2) Jammy Key for quantum chemistry (JKQC) to analyze commonly used quantum chemistry output files and facilitate database construction, handling, and analysis, and (3) Jammy Key for machine learning (JKML) to manage machine learning methods in optimizing molecular cluster modeling. This automation and machine learning utilization significantly reduces manual labor, greatly speeds up the search for molecular cluster configurations, and thus increases the number of systems that can be studied. Following the example of the Atmospheric Cluster Database (ACDB) of Elm (ACS Omega, 4, 10965-10984, 2019), the molecular clusters modeled in our group using the Jammy Key framework have been stored in an improved online GitHub repository named ACDB 2.0. In this work, we present the Jammy Key package alongside its assorted applications, which underline its versatility. Using several illustrative examples, we discuss how to choose appropriate combinations of methodologies for treating particular cluster types, including reactive, multicomponent, charged, or radical clusters, as well as clusters containing flexible or multiconformer monomers or heavy atoms. Finally, we present a detailed example of using the tools for atmospheric acid-base clusters.

Rovibronic molecular line list for the N[formula omitted] second positive system

A line list for the N2 second positive system, B3Πg - C3Πu, has been compiled using the PGOPHER spectral simulation software. The line list extends the number of vibrational states of the B3Πg up to v= 29 and a maximum rotational state of J= 150 for simulation temperatures up to 7000 K. New electronic–vibrational transition moments were calculated using refined potential energy curves and a transition dipole moment with the DUO software. Comparisons to experimental data and the SPECAIR software have been used to validate the new line list. The results are available in ASCII ExoMol .state and .trans files and as a PGOPHER input file for use in spectral analysis.

Characterization and control of primary natural frequency of FDM ABS prints through printer parameters and STL file manipulation

Characterization and control of primary natural frequency of FDM ABS prints through printer parameters and STL file manipulation

Superpdf: One-Stop Solution to All Your PDF Problems

Abstract: Superpdf is a web-based application that facilitates the modification and manipulation of PDF files. SuperPDF lets users combine multiple PDFs into one, split a PDF into multiple pages, convert PDFs to other formats, and change PDF content by adding text, photos, and notes. One of the primary advantages of SuperPDF is its user-friendly interface, which makes it simple for users of all ability levels to explore and utilize the software's different capabilities. In addition to a variety of advanced features, such as the ability to password-protect PDFs and redact sensitive information, the tool provides a variety of other capabilities. In addition to its core PDF editing capabilities, SuperPDF offers a variety of additional tools and functions, including the ability to build and fill out PDF forms, extract images and text from PDFs, and add electronic signatures to documents.

ENPS 101—Back to school for process safety

AbstractThis paper will provide an overview of the recently issued CCPS Process Safety for Engineers: An Introduction, Second Edition and how to use it. The objective of the text is to support teaching and learning of risk‐based process safety fundamentals as defined by the Center for Chemical Process Safety (CCPS). It also addresses the Accreditation Board for Engineering and Technology (ABET) Program Criteria for Chemical Engineering, which requires that chemical engineering curricula include consideration of the hazards relevant to chemical processes. This book can be used in meeting that requirement either as a curriculum for an undergraduate‐level process safety course or to provide process safety content into common chemical engineering courses. The team creating the book included professors who teach process safety. The book is founded on the CCPS risk‐based process safety elements and points to numerous tools to support the instructor in teaching and the engineer in conducting process safety fundamentals. Each chapter begins with a detailed process safety incident case study and includes what a new engineer might do, problem sets, numerous references, and a generic presentation file for use by professors.

RING-PyMOL: residue interaction networks of structural ensembles and molecular dynamics.

https://github.com/BioComputingUP/ring-pymol.

MOOSE Reactor Module: An Open-Source Capability for Meshing Nuclear Reactor Geometries

The U.S. Department of Energy (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has developed numerous physics solvers utilizing the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) framework for multiphysics reactor analysis. These solvers require input finite element meshes representing the discretized spatial domain. Typically, reactor analysts turn to licensed tools for the creation of reactor geometry meshes. Recently, open-source functionality has been added to the MOOSE framework to mesh common reactor geometries and improve MOOSE-based nuclear reactor application user workflows. The new functionality is primarily contained in the new Reactor module of MOOSE and includes support for hexagonal pins, assemblies, and cores, extended Cartesian geometry support, options for modeling static and rotating control drums within a hexagonal assembly, core periphery triangulation, and automatic tagging of pin, assembly, plane, and depletion regions for easier post processing of physics results. A set of reactor geometry mesh builder objects further streamlines the construction of hexagonal and Cartesian cores and allows mapping of materials to regions during mesh generation. The meshes produced with the MOOSE Reactor module may be used directly within MOOSE-based applications or exported as Exodus II files for use in other finite element solvers. The tools have been demonstrated and verified using a variety of NEAMS physics solvers on a range of reactor applications, including a sodium-cooled fast reactor core analysis using Griffin, a fast reactor assembly thermal deformation analysis using MOOSE Tensor Mechanics, and a heat pipe–cooled microreactor coupled analysis using Griffin, Bison, and Sockeye. MOOSE’s Reactor module provides significant advantages compared to the use of external meshing tools when analyzing Cartesian and hexagonal reactor lattices using MOOSE-based applications: immediate accessibility (open-source) to the end user, low barrier to entry for new users, speed of mesh generation, volume preservation of meshed fuel pins, and simplification of analysis workflow when used in conjunction with MOOSE-based applications.

Topiary: Pruning the manual labor from ancestral sequence reconstruction.

Ancestral sequence reconstruction (ASR) is a powerful tool to study the evolution of proteins and thus gain deep insight into the relationships among protein sequence, structure, and function. A major barrier to its broad use is the complexity of the task: it requires multiple software packages, complex file manipulations, and expert phylogenetic knowledge. Here we introduce topiary, a software pipeline that aims to overcome this barrier. To use topiary, users prepare a spreadsheet with a handful of sequences. Topiary then: (1) Infers the taxonomic scope for the ASR study and finds relevant sequences by BLAST; (2) Does taxonomically informed sequence quality control and redundancy reduction; (3) Constructs a multiple sequence alignment; (4) Generates a maximum-likelihood gene tree; (5) Reconciles the gene tree to the species tree; (6) Reconstructs ancestral amino acid sequences; and (7) Determines branch supports. The pipeline returns annotated evolutionary trees, spreadsheets with sequences, and graphical summaries of ancestor quality. This is achieved by integrating modern phylogenetics software (Muscle5, RAxML-NG, GeneRax, and PastML) with online databases (NCBI and the Open Tree of Life). In this paper, we introduce non-expert readers to the steps required for ASR, describe the specific design choices made in topiary, provide a detailed protocol for users, and then validate the pipeline using datasets from a broad collection of protein families. Topiary is freely available for download: https://github.com/harmslab/topiary.

METHODS FOR FINDING THE LOCATION OF HISTORICAL PHOTOGRAPHS FOR REPEAT PHOTOGRAPHY

Historical photographs are windows into the past. By comparing historical and modern photographs we can measure change; but how do we find the original camera location to repeat a photograph? Historical, geographic, topographic, and other clues may be used, but we lack a numerical method suitable for any user to find the general location of a historical photograph. We derive a geometric method that can be applied in the field or prior. The method uses measurements of at least three points of reference (POR) in the historical photograph and corresponding geographic locations measured via a compass or on a map. rePhoto, an open-source R package that applies the method and outputs spatial KML files for use with Google Earth, is provided. The geometric method was tested on 20 photographs with known locations and validated by independent users. The effectiveness of the method varied among users, but overall predicted a search area containing the original camera location 70% of the time (the prediction accuracy) and typically predicted search areas 99.5% smaller than the total region evaluated by the method. The method was robust regardless of whether three or four POR were used, and worked well even when POR were more than 30 km away. The proposed method only works for photographs with at least three identifiable geographic POR, thus other methods are illustrated for use more generally. California and the western USA have numerous iconic historical photographs, for which many locations could be found and re-photographed using methods described here.

Investigating the Input Validation Vulnerabilities in C Programs

Input validation is a fairly universal programming practice that helps reduce the chances of producing protection-related vulnerabilities in software. In this paper, an experiment is conducted to specifically determine the input validation issues found in programs and the problematic functions that lead to such issues. The experiment evaluated 12 arbitrarily selected open source C projects written by different programmers. The top two most common input validation problems are buffer overflow/XSS and potential memory mismanagement. In addition, the functions that caused the first problem are (a) strings/text functions (e.g., strcpy and strcmp), and (b) functions that read from standard input, STDIN (e.g., scanf and gets). In contrast, the functions that caused the second problem are (a) memory allocation/deallocation functions (e.g., memmove and malloc), and (b) file manipulation functions (e.g., fopen and fseek). Furthermore, the goto construct—to a small extent—plays a role. The recommendations are that (a) developers are encouraged to use memory-safe programming languages, otherwise, they should perform different types of checks for the validity of inputs as soon as they are entered, and (b) they should have the required knowledge of secure source code and use tools/suites to manage malformed strings.

Music Generation Using Recurrent Neural Networks

Abstract: Over the past years music has been continually evolving through the its tempos and beats as well as it’s melody. Traditionally, music is produced by a group of musicians with different instruments combining together to create a final synchronised product. In recent years, harmonies and beats were always considered to be generated manually. However, with the advent of digital technologies and software, it has become possible for machines to generate music automatically at an alarming pace. The purpose of this research is to propose a method for creating musical notes using Recurrent Neural Networks (RNN), specifically Long Short-Term Memory (LSTM)networks. To implement this algorithm, a model is created and the data is represented in the form of a percussive instrument digital interface (MIDI) file for easy access and interpretation. The process of preparing the data for input into the model isalso discussed, as well as techniques for receiving, processing, and storing MIDI files for use as input.To enhance its learning capabilities, the model should be able to remember previous details of a musical sequence and its structure. This paper discusses the use of a layered architecture in the LSTM model and how its connections interweave to create a neural network.

SCExecute: custom cell barcode-stratified analyses of scRNA-seq data.

In single-cell RNA-sequencing (scRNA-seq) data, stratification of sequencing reads by cellular barcode is necessary to study cell-specific features. However, apart from gene expression, the analyses of cell-specific features are not sufficiently supported by available tools designed for high-throughput sequencing data. We introduce SCExecute, which executes a user-provided command on barcode-stratified, extracted on-the-fly, single-cell binary alignment map (scBAM) files. SCExecute extracts the alignments with each cell barcode from aligned, pooled single-cell sequencing data. Simple commands, monolithic programs, multi-command shell scripts or complex shell-based pipelines are then executed on each scBAM file. scBAM files can be restricted to specific barcodes and/or genomic regions of interest. We demonstrate SCExecute with two popular variant callers-GATK and Strelka2-executed in shell-scripts together with commands for BAM file manipulation and variant filtering, to detect single-cell-specific expressed single nucleotide variants from droplet scRNA-seq data (10X Genomics Chromium System).In conclusion, SCExecute facilitates custom cell-level analyses on barcoded scRNA-seq data using currently available tools and provides an effective solution for studying low (cellular) frequency transcriptome features. SCExecute is implemented in Python3 using the Pysam package and distributed for Linux, MacOS and Python environments from https://horvathlab.github.io/NGS/SCExecute. Supplementary data are available at Bioinformatics online.

Buckling Susceptibility of a K-File during the Initial Negotiations of Narrow and Curved Canals Using Different Manual Techniques.

(1) Background: One possible way to investigate the potential impact or susceptibility of buckling on different manual techniques is to measure compressive loads during canal negotiation. The higher their values, the easier and quicker the critical load level to buckling is reached, leading to possible instrument lateral deformation. The objective of the present study was to investigate the impacts of compressive loads on a small K-file manipulated with different techniques for canal negotiation in simulated narrow and curved canals. (2) Methods: The tooth model selected was a plastic double-curved premolar 23 mm long (DRSK Group AB, Kasernvagen 2, SE-281 35, Hassleholm, Sweden) with an extremely narrow canal lumen to mimic a very difficult anatomical scenario. An experienced endodontist performed the negotiation of 90 of these artificial teeth randomly assigned to 3 different groups of 30 blocks each, respectively, using 3 different techniques: Group A: watch winding/pull (WW) motion; Group B: balanced forces (BF) technique; Group C: envelope of motion (EOM). The measurement system was based on the use of a dynamometer, Instron, Ltd. (model 2525-818 2kN f.s.), linked to a data acquisition unit HBM MGC+ to test all the compression and tensile loads, including all the peaks. (3) Results: All data acquired were processed by the CATMAN AP HBM software. Multiple comparisons for the highest compressive loads estimated the mean difference between WW vs. BF techniques of 3.60 [95% confidence interval (CI): 2.85 to 4.35, p < 0.001], WW vs. EOM of -1.76 (95% CI: -2.11 to 1.40, p < 0.001), and BF vs. EOM -5.36 (95% CI: -6.04 to -4.67, p < 0.001). (4) Conclusions: In conclusion, among the tested manual motions, the BF technique (Group B) was the most susceptible to buckling with the highest compressive load. WW motion (Group A) and EOM (Group C) were less susceptible to buckling than the BF technique. Therefore, a pressure-free manipulation of manual files, such as WW motion or EOM, can help reduce the susceptibility to buckling during the negotiation of narrow-curved canals.

How will United States commercial building energy use be impacted by IPCC climate scenarios?

Climate change and anthropogenically-forced shift of weather in the future will impact energy use and resilience of both the built environment and the electric grid. The aim of this analysis is to understand how future climate scenarios will impact electricity and natural gas use of commercial buildings in the United States. This study analyzes this impact for 2030, 2045, and 2100 using Representative Concentration Pathways (RCP) scenarios defined in Intergovernmental Panel on Climate Change (IPCC) Assessment Report 5. The large, gridded simulation of meteorological variables for RCPs 2.6, 4.5, 6.0, and 8.5 are selected and downscaled to make available hourly Future Meteorological Year (FMY) weather files for use and improvement in subsequent studies. High performance computing resources use these FMYs to simulate commercial prototype buildings in every American Society of Heating, Refrigeration, and Air Conditioning Engineers (ASHRAE) climate zone of the United States (US), and results are scaled to nation-wide energy use using conditioned floor area multipliers. The analysis is conducted without speculating the physical and performance traits of future buildings or the grid characteristics.This analysis quantifies the impact of climate change on source electrical and natural gas usage for commercial buildings in the United States over the next 80 years. If US commercial floorspace remained constant, total energy use by 2100 is predicted between an 1.75% decrease under the greatest emission scenario (8.5) and a 1.76% increase under the lowest emission scenario (2.6). When adjusted for anticipated urban growth by 2100, the predicted range is 65% increase (8.5) and 71% increase (2.6). Under a global temperature rise climate scenario, the warmest US climate zones will see a large increases in electricity use derived from space cooling while the coldest US climate zones will see significant decreases in natural gas use caused by the decrease in heating necessary. While climate change may ultimately require adaptations of the built environment to withstand its effects and because the United States is a country that requires more heating than cooling, from a building energy perspective, climate change (average temperature rise) is a net energy saver for the United States.

Performance Comparison of Open Source and Commercial Computing Tools in Educational andOther Use — Scilab vs. MATLAB

In this paper, the authors compare the features and the overall performance of the two high-level numerical computing and modeling software environments: the freeware Scilab and commercially available industry-standard MATLAB. The motivation for the work emanated from the educational use of these tools at the college and university level, but with a perspective to their professional and scientific use as well. Their performance is tested by measuring the execution times of several combined-task benchmarks implemented as test functions, built upon nine common numerical tasks that are often found in programs for solving standard engineering problems. They include basic algebra and matrix calculations, signal generation, signal analysis, and storing and retrieving data to and from the hard disk drive. Although MATLAB outperforms Scilab in all the benchmarks except the disk file manipulations, in the presumed vectorization versions of the benchmarks, it is not for much. The overall performance of the freeware rival is very satisfactory, making it a good choice not only for educational use but also for scientific and professional purposes, especially when funding is critical.