Windows Operating Research Articles

TreeViewer: Flexible, modular software to visualise and manipulate phylogenetic trees.

Phylogenetic trees illustrate evolutionary relationships between taxa or genes. Tree figures are crucial when presenting results and data, and by creating clear and effective plots, researchers can describe many kinds of evolutionary patterns. However, producing tree plots can be a time-consuming task, especially as multiple different programs are often needed to adjust and illustrate all data associated with a tree. We present TreeViewer, a new software to draw phylogenetic trees. TreeViewer is flexible, modular, and user-friendly. Plots are produced as the result of a user-defined pipeline, which can be finely customised and easily applied to different trees. Every feature of the program is documented and easily accessible, either in the online manual or within the program's interface. We show how TreeViewer can be used to produce publication-ready figures, saving time by not requiring additional graphical post-processing tools. TreeViewer is freely available for Windows, macOS, and Linux operating systems and distributed under an AGPLv3 licence from https://treeviewer.org. It has a graphical user interface (GUI), as well as a command-line interface, which is useful to work with very large trees and for automated pipelines. A detailed user manual with examples and tutorials is also available. TreeViewer is mainly aimed at users wishing to produce highly customised, publication-quality tree figures using a single GUI software tool. Compared to other GUI tools, TreeViewer offers a richer feature set and a finer degree of customisation. Compared to command-line-based tools and software libraries, TreeViewer's graphical interface is more accessible. The flexibility of TreeViewer's approach to phylogenetic tree plotting enables the program to produce a wide variety of publication-ready figures. Users are encouraged to create their own custom modules to expand the functionalities of the program. This sets the scene for an ever-expanding and ever-adapting software framework that can easily adjust to respond to new challenges.

Smart Garden on Chili Plants Based on IoT

Abstract:Cultivating chili plants requires special attention such as temperature and soil humidity. Internet of Things (IoT) technology is a technology that allows objects around us to be connected to the internet network. The widespread adoption of various internet of things technologies has a very pronounced influence in the domestic sector such as home and smart car applications, and the agricultural sector is no exception.Temperature monitoring system, humidityIoT-based soil pan on chili plants (smart garden) is an IoT-based monitoring system design to control temperature and soil moisture on chili plants which can make it easier for farmers to measure soil and plant conditions and to make it easier for farmers to monitor the quality of their agricultural land. The process of creating a monitoring system design begins with interviews to collect primary data and literature studies to collect secondary data. Then carry out system design, tool assembly and implementation. The system for monitoring and controlling temperature and soil moisture using IoT can be run using Windows operating system software. The hardware used is the DHT11 temperature sensor, Moisture Sensor, Arduino, and Nodemcu ESP8266. This system utilizes a pump and fan for its hardware, using an automatic system implementation from a microcontroller so that it can make the hardware run without user intervention.If the humidity value displayed on the LCD is <70% then the pump will be on and the plants will be watered, and if the humidity is >80% then the pump will be off and stop watering.

RI−Calc: A user friendly software and web server for refractive index calculation

The refractive index of an optical medium is essential for studying a variety of physical phenomena. One useful method for determining the refractive index of scalar materials (i.e., materials which are characterized by a scalar dielectric function) is to employ the Kramers−Kronig (K−K) relations. The K−K method is particularly useful in cases where ellipsometric measurements are unavailable, a situation that frequently occurs in many laboratories. Although some packages can perform this calculation, they usually lack a graphical interface and are complex to implement and use. Those deficiencies inhibit their utilization by a plethora of researchers unfamiliar with programming languages. To address the aforementioned gap, we have developed the Refractive Index Calculator (RI−Calc) program that provides an intuitive and user−friendly interface. The RI−Calc program allows users to input the absorption coefficient spectrum and then easily calculate the complex refractive index and the complex relative permittivity of a broad range of thin films, including of molecules, polymers, blends, and perovskites. The program has been thoroughly tested, taking into account the Lorentz oscillator model and experimental data from a materials' refractive index database, demonstrating consistent outcomes. It is compatible with Windows, Unix, and macOS operating systems. You can download the RI−Calc binaries from our GitHub repository or conveniently access the program through our dedicated web server at nanocalc.org.

Pericardial Window Operation in Oncology Patients: Analysis of Long-Term Survival and Prognostic Factors.

Pericardial effusion (PE) is a serious condition in cancer patients, primarily arising from malignant dissemination. Pericardial window formation is a surgical intervention for refractory PE. However, the long-term outcomes and factors associated with postoperative survival remain unclear. We retrospectively analyzed data from 166 oncology patients who underwent pericardial window formation at Samsung Medical Center between 2011 and 2023. We analyzed survival and PE recurrence regarding surgical approach, cancer type, and cytopathological findings. To identify factors associated with survival, we utilized Cox proportional-hazards regression. All patients had tumors documented in accordance with the American Joint Committee on Cancer staging manual, including lung (61.4%), breast (9.6%), gastrointestinal (9.0%), hematologic (3.6%), and other cancers (16.4%). Surgical approaches included mini-thoracotomy (67.5%) and thoracoscopy (32.5%). Postsurgical cytopathology confirmed malignancy in 94 cases (56.6%). Over a median follow-up duration of 50.0 months, 142 deaths and 16 PE recurrences occurred. The 1-year overall and PE recurrence-free survival rates were 31.4% and 28.6%, respectively. One-year survival rates were significantly higher for thoracoscopy recipients (43.7% vs. 25.6%, p=0.031) and patients with negative cytopathology results (45.1% vs. 20.6%, p<0.001). No significant survival difference was observed between lung cancer and other types (p=0.129). Multivariate analysis identified New York Heart Association class, cancer stage, and cytopathology as independent prognostic factors. This series is the largest to date concerning window formation among cancer patients with PE. Patients' long-term survival after surgery was generally unfavorable. However, cases with negative cytopathology or earlier tumor stage demonstrated comparatively high survival rates.

Changes in Concentration of Carbon Dioxide and Temperature in University Classrooms

This study aims to observe variations in temperature, relative humidity, and carbon dioxide concentrations in university classrooms without mechanical ventilation throughout the day. Over three days, two classrooms in Riga Stradiņš University, equipped solely with natural ventilation, were evaluated for variations in indoor air quality. Observations were recorded using the Aranet4 sensor during actual study sessions with varying numbers of occupants, and ventilation periods marked by window operations. The recorded parameters were compared with established indoor air quality guidelines. The results showed that the relative humidity remained within the ideal range (40%-60%) throughout the observation period. Indoor temperature varied between 18 °C to 26 °C, with noticeable increases during practical study sessions and decreases during ventilation periods. The carbon dioxide levels consistently exceeded the safe limit of 1000 ppm during all study sessions, with the time taken to exceed this threshold being directly proportional to the number of occupants. The findings underline the need for strategic ventilation interventions and classroom arrangements, considering occupancy and room size to promote healthier learning environments. Further research incorporating occupant surveys and including diverse educational settings is recommended. Keywords: indoor air quality; natural ventilation; classroom environment; carbon dioxide; relative humidity; temperature.

Dual-port ferroelectric NAND flash memory for large memory window, QLC programmable and disturbance-free operations

Dual-port ferroelectric NAND flash memory for large memory window, QLC programmable and disturbance-free operations

Glass Packaged Mineral Water Recognition System Based On Logo Using The Histogram Of Oriented Gradients Method

Application of Glass Packaged Mineral Water Recognition System Based on Logo Using Method Histogram of Oriented Gradients is an application program used to introduce brands or logos of glass bottled mineral water. This application was designed on the Windows operating system and uses Python and Open CV software. The methods used in this design are Histogram of Oriented Gradients as a method for feature extraction, Method Euclidean Distance as a method for measuring similarity distance, and k-Nearest Neighbor as a method of recognizing a logo or brand. The average accuracy of the test is 13.575%.

A Comprehensive MATLAB based Optical Mark Reader and Database Generation System for the Windows Operating System

The importance of software systems in business cannot be overstated. Often, there are numerous processes involved in developing software solutions, including problem definition, solution design, building, testing, and maintenance. The objective of this study is to propose an optical mark reader (OMR) that is practical, affordable, and compatible with Windows. The OMR can be used to process data in polling places, schools, elections, and other comparable places. It was created especially for grading multiple-choice tests. It may be easily integrated with a multipurpose printer and comes with an updated tool for image scanning and reading. The article also provides a database that generates thorough reports and was built in a soft environment. The paper uses an aptitude test grading system for a university to show how well the system works, and the database successfully creates a detailed report of the student’s data and final results. The system was created utilizing state-of-the-art software, including MATLAB and SQL server.

DATA PREPARATION MODEL FOR TRAINING NEURAL NETWORKS

The paper presents the results a research of changes in the state of the operating environment when it is damaged by malware. The Windows operating system of various versions and builds was selected as a test environment. The research was carried out using polymorphic malware abc, cheeba, december_3, stasi, otario, dm, v-sign, tequila, flip. The research was conducted to obtain the value of operating system signatures for subsequent training of neural networks. Context triggered piecewise hashing and performance testing methods were used for research the assessment of changes in the state of the operating environment when it is damaged by malware. Simulation of the developed method was carried out in the Hyper-V virtual environment.

Comparative analysis of machine learning algorithms used in malware analysis

Despite the achievement of the field of cyber security in the modern world of science and the continuous development of its methods, malware is still one of the biggest threats to information security. Malware is evolving every day, and its types and behaviors are increasing day by day. And the importance of using modern, sophisticated technologies in identifying and combating such complex and diverse malicious programs is increasing. In this regard, it is possible to mention the advantages of using intelligent systems in the field of information security. In this article, we will analyze PE (Portable Executable) files on the Windows operating system, that is, the processes running on the computer and analyzing the malicious programs using machine learning algorithms. At the same time, we will focus on the operation of different machine learning algorithms and show which method is most effective to use for our example. In this article, we will have the following tasks: Providing information about malicious software. Definition of PE files, its structure and nature. Preparation of data for practical work (collection of files with clean and malicious code). An overview of methods for separating files into clean and malicious files. Sorting the signs necessary for training according to pre-prepared files, that is, getting only those signs that allow to achieve the most accurate result during training. Implementation of several machine learning algorithms and selection of the most effective among them.

Simple ePDF: A Pair Distribution Function Method Based on Electron Diffraction Patterns to Reveal the Local Structure of Amorphous and Nanocrystalline Materials.

Amorphous, glassy or disordered materials play important roles in developing structural materials from metals or ceramics, devices from semiconductors or medicines from organic compounds. Their local structure is frequently similar to crystalline ones. A computer program is presented here that runs under the Windows operating system on a PC to extract pair distribution function (PDF) from electron diffraction in a transmission electron microscope (TEM). A polynomial correction reduces small systematic deviations from the expected average Q-dependence of scattering. Neighbor distance and coordination number measurements are supplemented by either measurement or enforcement of number density. Quantification of similarity is supported by calculation of Pearson's correlation coefficient and fingerprinting. A rough estimate of fractions in a mixture is computed by multiple least-square fitting using the PDFs from components of the mixture. PDF is also simulated from crystalline structural models (in addition to measured ones) to be used in libraries for fingerprinting or fraction estimation. Crystalline structure models for simulations are obtained from CIF files or str files of ProcessDiffraction. Data from inorganic samples exemplify usage. In contrast to previous free ePDF programs, our stand-alone program does not need a special software environment, which is a novelty. The program is available from the author upon request.

MENDELEY APPLICATION TRAINING TO IMPROVE STUDENT FINAL ASSIGNMENT WRITING

Every student who has entered the final study period must complete the final project/thesis as a graduation requirement. In order to produce quality and responsible writing, students must have the provision of knowledge and how to find, find and determine the correct references and write good citations to avoid plagiarism in thesis writing. The Mendeley application can assist in managing reference sources and writing citations, which can synchronize with the references menu in Microsoft Word. So the PKM team of the Mandarin Language Education Study Program, FKIP UNTAN, provided training on using the Mendeley Application to 20 semester VII students taking thesis writing. Based on the results of the training activities, it can see that 95% of the students who attended the training were able to master the Mendeley application. The obstacle faced in this training was the problem of student laptop devices still using a low version of the Windows operating system, resulting in students needing help installing the Mendeley application. However, this obstacle can be handled thanks to the direction and guidance of the lecturer in the PKM Team. The Mendeley application is relatively easy to learn, understand, and operate, so students will use the Mendeley application as support in completing their final project/thesis.

IntelliGenes: a novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles.

In this article, we present IntelliGenes, a novel machine learning (ML) pipeline for the multi-genomics exploration to discover biomarkers significant in disease prediction with high accuracy. IntelliGenes is based on a novel approach, which consists of nexus of conventional statistical techniques and cutting-edge ML algorithms using multi-genomic, clinical, and demographic data. IntelliGenes introduces a new metric, i.e. Intelligent Gene (I-Gene) score to measure the importance of individual biomarkers for prediction of complex traits. I-Gene scores can be utilized to generate I-Gene profiles of individuals to comprehend the intricacies of ML used in disease prediction. IntelliGenes is user-friendly, portable, and a cross-platform application, compatible with Microsoft Windows, macOS, and UNIX operating systems. IntelliGenes not only holds the potential for personalized early detection of common and rare diseases in individuals, but also opens avenues for broader research using novel ML methodologies, ultimately leading to personalized interventions and novel treatment targets. The source code of IntelliGenes is available on GitHub (https://github.com/drzeeshanahmed/intelligenes) and Code Ocean (https://codeocean.com/capsule/8638596/tree/v1).

Design and Implementation of Smart Home System Based on STM32 Microcomputer

Abstract With the rapid development of the Internet of Things science and technology, people′s living standards are gradually improving, and the requirements for the living environment are also getting higher and higher, which makes smart homes gradually enter thousands of households. The purpose of this project is to design a system that integrates hardware and software and can measure and transmit various data. Among them, the hardware part includes data measurement and data display. The data measurement module consists of DHT11 temperature and humidity sensor, DSM501 particle number sensor and MQ3 alcohol concentration sensor. The experimental data will be displayed on the TFTLCD screen. The system software is partly run on the Windows operating system, using the Python language development. This system takes ESP8266 module as the transfer station, realizes the communication between STM32 development board and computer. The experiment shows that the system has the advantages of high measurement data accuracy, fast data refresh speed, complete data transmission, simple design, high reliability, easy installation, economical and practical, and has certain practical value in life, production, industry and other fields.

Occupants' interaction with building services: Development of a camera-based method for detailed monitoring of windows, shadings, and lights

Several energy gains or losses in buildings are influenced by occupant interactions with building services, such as lighting or HVAC systems, thermostat settings, and window and shading operations. Occupant behavior is usually triggered by discomfort, nevertheless actions taken to restore comfort can have an impact on final energy demand. Thus, an accurate energy assessment for both new and retrofit building design must properly account for occupant behavior, based on reliable models developed from real case studies and detailed monitoring. This work presents a new approach for continuous and non-intrusive monitoring of window opening angle, shading position, and lighting operation to determine the net air exchange area for ventilation. A camera-based device and a post-processing algorithm are developed, and a monitoring campaign over 6 month is carried out to showcase the monitoring system. The device consists of a camera setup connected to a microprocessor, and a dedicated script which enables the device to track window opening, shading movement and lighting operation through target and object identification. Results of the prototyping case study show that the proposed system can effectively detect window opening angles and shutter positions, dealing with multiple windows and shutters simultaneously and allowing the deployment of the benefits of continuous monitoring. The explored application is the direct use of the collected data for the calculation of natural ventilation rates from the net exchange area (EN 16798-7) over long term datasets. As future development, the monitoring system will be used to develop accurate behavioral models based on the experimental data to analyze and suggest the occupant’s response to discomfortable conditions in order to improve indoor air quality and save energy.

Development of window scheduler algorithm exploiting natural ventilation and thermal mass for building energy simulation and smart home controls

Building energy simulations often rely on abstract assumptions when it comes to natural ventilation, such as ‘windows always open [or closed]’ or ‘windows open when outdoor temperature is below a certain threshold.’ However, simulations based on these assumptions fail to fully exploit the cooling potential of natural ventilation, as its effectiveness can be enhanced or diminished by various factors, including the presence of thermal mass. This issue also extends to smart home controls, where determining the window schedule becomes challenging without information about the building's response to outdoor conditions. To address these issues, this study has developed an analytical model for window operation schedules that leverages the passive cooling from natural ventilation. The analytical model was validated against a Modelica simulation. A case study utilizing the BESTEST model of ANSI/ASHRAE Standard 140 underwent validation with EnergyPlus simulations, showing strong concordance. The algorithm provides window schedule recommendations adapted to various airflow rates, thermal masses, and climate variations. The case study demonstrated that proper window scheduling could reduce indoor temperature by up to 8 °C under the given simulation settings, thereby improving resilience and indicating potential energy savings. Furthermore, the paper explores the potential opportunities and challenges this approach presents, especially for building simulation and smart home applications.

Development of software for the management of the maintenance of equipment of thermal power plants

The relevance of the use of thermal power plants for the generation of thermal and electric energy on the territory of the Russian Federation is revealed, taking into account its geographical and climatic features. The substantiation of the importance of the process of maintenance and repair in relation to boiler units, which are operated at thermal power plants, is given. Difficulties accompanying the practical implementation of this process are identified. The influence of the identified difficulties on the existing shortcomings in the process of maintenance and repair of boiler equipment and the technological pipelines connecting them and pipelines of steam and hot water is shown. The goal of the study is set, which is aimed at eliminating the identified objective difficulties and the tasks are formulated, the solution of which will contribute to the achievement of the goal. The necessity of developing specialized software for managing the process of maintenance and repair of equipment and pipelines of boiler units of combined heat and power plants is substantiated. The methodology of the work is based on the development of digital models of pipelines and boiler equipment, as well as algorithms aimed at processing the parameters of digital models. The software implementation of the developed models and algorithms is made by means of object-oriented programming in the form of a client-server application for the Windows operating system. The description of the results of software development aimed at solving the set tasks is given. Examples of some dialog boxes accompanying the functioning of the developed software are given, as well as examples of created digital models of boiler equipment and their individual elements. The practical application of the research results contributes to an increase in the degree of digitalization of industrial production in general and energy production in particular. The results obtained in the framework of this work, in the form of software, can be used to accompany the process of maintenance and repair of boiler equipment of combined heat and power plants. With appropriate adaptation, the results obtained can also be applied to boiler equipment, pipelines and apparatus that are used in the chemical, petrochemical and oil refining industries.

Ransomware Behavior on Windows Endpoint: An Analysis

This paper provides a comprehensive examination of ransomware behavior on Windows endpoints, exploring the intrusion mechanisms, proliferation methods, and the mitigating strategies that can be employed. It provides a comparative analysis of several ransomware families and their effects on Windows systems, culminating with suggestions for future research directions in enhancing endpoint security against ransomware attacks. In the wake of a rising number of ransomware attacks worldwide, epitomized by the damaging disruptions to the Colonial Pipeline and the Irish Health Service Executive, the persistent threat of ransomware to critical infrastructure has never been more apparent. While Windows endpoints remain primary targets, these attacks have also highlighted a less explored but crucial aspect of ransomware behavior: the exploitation of Application Programming Interface (API) calls integral to the Windows operating system. This comprehensive study provides an exhaustive investigation into the interplay between ransomware and Windows APIs, emphasizing the patterns of invocation and manipulative misuse by various ransomware families. By investigating specific API calls, such as the CryptEncrypt function in the Cryptography API for encryption, and the CreateFile and WriteFile functions in the File API for file system interaction, we illuminate the mechanisms by which ransomware carry out their damaging actions. Further, using the real-world examples drawn from the Colonial Pipeline and Irish Health Service Executive incidents, among others, the study shows how these API calls were manipulated during actual ransomware attacks. In these cases, ransomware like DarkSide and Conti used Windows APIs not just for the primary tasks of encryption and file system manipulation, but also for achieving network communication, maintaining persistence, and even thwarting detection. By presenting a comparative analysis of API call sequences in both benign and ransomware-infected Windows environments, this study serves as a critical exploration into the behavior of these malicious entities. The different patterns observed provide us with valuable insights into their operational strategies and offer opportunities for the development of detection heuristics. The insights derived from this research contribute significantly to our understanding of the behavior patterns of recent, high-profile ransomware attacks. In turn, this work aims to guide the evolution of more sophisticated, behavior-based detection mechanisms, thus strengthening the security posture of Windows endpoints. Ultimately, this study underscores the need for continuous research into API call patterns, as the cybersecurity landscape continues to face dynamic and increasingly sophisticated threats.

Space-Level air conditioner electricity consumption and occupant behavior analysis on a university campus

In China, despite only 2 % of the population residing on university campuses, these campuses account for 8 % of the total energy consumption. Understanding the space-level energy consumption characteristics and energy-related occupant behaviors on a university campus can help improve campus buildings' energy efficiency. This study investigates 21 office spaces on a university campus to better understand the space-level electricity consumption of air-conditioners (AC) and the occupant behaviors (OB), thermal comfort needs, and window operation. First, Internet of Things (IoT) sensors were installed in the 21 office spaces to collect the indoor temperature and humidity, the electricity consumption of the AC, and the status of doors. The data were collected for the entire cooling season. The space-level occupancy patterns were then analyzed based on the quality of the doors, including the first occupant’s arrival time and the last occupant’s departure time. Moreover, the indoor temperature, humidity, and illuminance were combined to evaluate occupants’ thermal and visual comfort need. In addition, statistical and clustering analyses were conducted on air conditioner operations' duration, frequency, and electricity consumption. The results showed that the spaces were typically occupied from 9:21 to 22:25, with 10 h and 53 min daily. The average indoor temperature was 26.1 °C, ranging from 22.1 °C (5th percentile) to 34.9 °C (95th percentile) when the room was occupied and ranging from 21.7 °C (5th percentile) to 32.5 °C (95th percentile) when the AC was on. The air conditioner's electricity consumption ranges from 11.7 to 152.2 kWh/m2 with a median of 68.9 kWh/m2 and from 46.84 to 1883.7 kWh/person with a median of 464.7 kWh/person. The different occupancy densities often lead to a significant difference in the electricity consumption of air conditioners. The findings of this study can be used to support the development of prototype energy models and occupant-centric control (OCC) models for campus office buildings.

Implementation of Finite State Machine Models on the Artificial Intelligence System of Characters in The Game "MMORPG" using RPG Maker

Technological developments are the main drivers of global social, economic, and cultural change, including in the rapidly growing gaming industry. The Role-Playing Game (RPG) genre, in which players portray characters in the game's story, is gaining popularity. The application of FSM Models and AI technology in character development and RPG game interaction not only resulted in exciting entertainment, but also inspired similar uses in various fields. With AI, characters interact dynamically with players and environments, and FSM Models govern complex character behavior, the game experience is even more immersive. RPG Maker, one of the popular engines, simplifies the process of creating RPG games with an easy user interface. The implementation of the FSM Model is done through events and switches, directing storylines and character situations with structured logic. This study analyzes the application of FSM Model in MMORPG RPG games. Through the design, testing, and analysis stages, FSM proved effective in creating games that combine entertainment with learning. This game invites players to look for requirements and challenges to proceed to the next level. The result is an MMORPG game played on a PC with a Windows operating system, providing an educational and entertaining gaming experience.