Reviewerly/exHarmony huggingface dataset:
FEATURES OF THE USE OF INFORMATION AND COMMUNICATION TECHNOLOGIES TO SUPPORT PROJECT PROCESSES IN DISTRIBUTED TEAMS

The study presents an in-depth analysis of the role of information and communication technologies (ICT) in the context of managing project processes in distributed teams. The main focus is on the classification and evaluation of the effectiveness of communication and information technologies as tools that significantly increase productivity and contribute to the optimization of work processes in such distributed teams. The main interpretations of the concept of distribution in project teams are given.&#x0D; The methodological approach of the article is based on a comprehensive analysis of existing problems of communication and information exchange in distributed teams. A systematic approach was used to structure and define the main channels of communication, based on a hierarchical diagram developed on the basis of expert assessments and analysis of work processes.&#x0D; The results of the study present a detailed comparative analysis of widely used platforms for project management, such as Trello, Asana, Jira, Microsoft Project, etc., with an emphasis on their functionality, areas of application, and project management models and assignments in terms of distribution in project teams.&#x0D; The authors carried out a comprehensive comparison of communication and information systems, as a result, a number of main trends in the use of ICT in project management over the past four years were revealed. Special attention is paid to the most popular tools, the definition of their unique features and the potential of application in various projects. Innovative approaches to the automation of project processes in the context of project management platforms for distributed teams are also considered, with the proposal of a new algorithm for their implementation.&#x0D; The conducted analysis makes an important contribution to the understanding of how information and communication technologies can be applied to improve the efficiency and productivity of distributed teams, in particular in the aspects of supporting project processes. The study contributes to a deep understanding of the key factors affecting the successful integration of the considered technologies into modern project practices.
METHOD AND MEANS OF SECURITY MONITORING IN A COMPUTER NETWORK BY SIEM MEANS

This work focuses on researching, analyzing, and enhancing methods and tools for security monitoring in computer networks. The study develops security monitoring tools and methods based on SIEM agents, improving the data normalization process from security logs. The research explores SIEM's role in the SIEM-EDR-NDR triad perspective to accelerate responses to network security threats. The investigation is grounded in the experiences of foreign companies and domestic banking networks. The interaction of SIEM-EDR-NDR components, forming a SOC triad, is examined. SIEM is utilized for centralized data analysis, including EDR and NDR, providing a comprehensive security overview. EDR detects and responds to threats on endpoints, complemented by NDR, extending SIEM analysis. This combination ensures effective response to cyberattacks, reducing "dwell time" until detection. The formulation of tasks for EDR components in the SIEM-EDR-NDR triad is discussed. Emphasis is placed on the importance of protecting endpoints at all stages of an attack, and effective strategies, such as traffic analysis, application control, and centralized cybersecurity management, are identified. Integration of EDR with existing security tools to create a comprehensive system is highlighted. Within the SIEM context, data processing stages, from log collection and normalization to event classification and correlation, are illuminated. The role of correlation in incident formation and investigation is underscored. An enhanced normalization scheme with an expanded agent deployment and key data processing stages within the SIEM system is proposed. The work addresses the improvement of event log processing in SIEM for effective network security monitoring and timely threat mitigation. The achieved goal accelerates threat response processes through SIEM agent integration, facilitating the organization and classification of information flows for prompt threat mitigation.
METHODS AND MEANS OF PROTECTING RESOURCES IN COMPUTER SDN NETWORK

The work is dedicated to the analysis and improvement of methods and tools for building the architecture of software-defined networks (SDNs). A crucial aspect involves comparing the differences between network management using traditional methods and utilizing an SDN controller. Primary attention is given to the development of security models based on software-defined networks.The research is grounded in the analysis of specific cases involving the use of such networks, including gathering opinions and expert assessments from professionals in the field. It leverages publicly available information on methods and tools for securing the architecture of software-defined networks. SDN technology provides greater flexibility and speed in implementing security measures, allowing real-time responses to threats. In contemporary conditions, where cyber threats are becoming more complex and pronounced, SDN networks enable the detection of attacks, blocking malicious actions, and applying security policies in real-time. However, the increasing complexity of cyber threats and constant technological changes necessitate further development and enhancement of the information security of SDN network resources for companies. There is a need for further analysis and improvement of methods and tools for protecting information and other resources in computer-based SDN networks. The necessity for further analysis and improvement of methods and tools for protecting information and other resources in computer-based SDN networks serves as the foundation for this research. As a result, an enhancement in the level of information security for SDN network resources has been achieved by: 1) reducing the intervention time in the network; 2) applying an improved method of traffic processing based on network security of packet flows, allowing desired network applications to efficiently manage forwarding.
A Minimal White-Box Dedicated Cipher Proposal Using Incompressible Lookup Tables: Space-Hard AES

In a white-box context, an attacker has full access to the execution environment and the implementation of cryptographic algorithms. Dedicated white-box ciphers, such as WEM and SPNbox, provide incompressibility and key extraction protections in this context, at the cost of increased memory usage and performance loss compared to standard ciphers. Even when a pure white-box threat model is not warranted, the use of incompressible lookup tables can be helpful in deterring side-channel attacks. In this paper we present a simple threat model for such scenarios and propose a dedicated cipher, Space-Hard AES, which provides minimal incompressibility guarantees while presenting better performance for ARMv8 implementations than other dedicated ciphers.
Gender Discrimination by Female Journalists Against Companies in the Media

Reseacrh aims to find findings from the forms of discrimination experienced by female journalists by media companies in Surabaya. The research subjects consisted of four media in Surabaya, namely Suara Surabaya, Ngopibareng.id, Jawa Pos, and Jawa Pos Televisi. This study aims to determine the discrimination committed by editors in the media Suara Surabaya, Ngopibareng.id, Jawa Pos, and Jawa Pos Televisi (JTV) against their female journalists. In addition to knowing the perspective of the editor-in-chief on gender in the world of work and the media industry. Through explorative qualitative research methods, researchers seek data from various sources. The results of this study indicate that there are still many media in Surabaya that have not fully fulfilled the rights of female journalists. At the Jawa Pos Office there are lactation room facilities as well as a refrigerator to store breast milk (ASI). Meanwhile in Suara Surabaya, the communication pattern formed by the chief editor towards female journalists is different from that of male journalists. Other findings also concern the workload experienced by female journalists from Ngopibareng.id and Jawa Pos Televisi (JTV). Based on research showing that the media in Surabaya, only one that has a good perspective on gender, namely Jawa Pos. Meanwhile, the editors-in-chief of Suara Surabaya, Ngopibareng.id and Jawa Pos Televisi (JTV) still don't have a good perspective on gender.
Advancing P&amp;ID Digitization with YOLOv5

In the realm of engineering diagram recognition and digitization, significant progress is evident across various domains, including the handling of intricate diagram categories like Piping and Instrumentation Diagrams (P&IDs), scene text in images, and point symbols on scanned topographic maps. These advancements result from diverse methodologies, such as deep learning, neural networks, digital image processing, and the implementation of the YOLOv5 algorithm for symbol detection and recognition. These approaches substantially improve efficiency and automation in applications ranging from plant design to information extraction. They not only surmount challenges in processing complex visual data but also showcase how advanced technology like YOLOv5 is transforming industries, from manufacturing to geographic information systems. In the field of engineering diagram recognition and digitization, YOLOv5 achieves a 93% accuracy rate, demonstrating its significant impact. The model excelled in precision (92%), recall (94%), F1 score (93%), AUC score (0.97), nd ROC score (0.92), advancing document digitization and automation. These innovations pave the way for further enhancements in engineering and document digitization.
Flowchart Generation and Mind Map Creation using Extracted Summarized Text

The technology discussed in this research study aims to transform text into a variety of visual representations, including mind maps, flowcharts, and summaries. The research underlines the usefulness of graphical representations and summaries for greater retention, starting with the challenges of remembering and digesting information from numerous sources. The project uses machine learning and deep learning algorithms to extract text from user-provided images or PDFs and transform it into mind maps or flowcharts based on user preferences. The capability of this research spans both the business and academic areas, allowing for the concise summarization of lengthy, complex documents. An overview of the literature on text extraction, summarization, and conversion techniques is given in the article. These techniques covered include OCR, network text analysis, deep learning-based summarization, keyword extraction, and data flow diagrams. The suggested method involves extracting text using OCR, summarising text using the T5 transformer model, creating flowcharts based on phrase relationships, and creating mind maps using NLTK and NetworkX modules. The conclusion of the study discusses the advantages and implementation specifics of each technique. The project offers a powerful way for converting text into visual representations in both academic and professional contexts, encouraging better comprehension, information retention, and improved learning and problem-solving skills.
DroneMag: A Novel Approach Using Drone Technology for Detection of Magnetic Metal

The study introduces an innovative approach to enhance the precision of metal-sensitive magnetometers used in unmanned aerial vehicles (UAVs). The three-pronged strategy comprises of using lightweight drone bodies produced via 3D printing, elongated rods, and electrical shielding. The system’s primary objective is to enhance reading accuracy, especially in regions with volcanic activity, hence improving safety and efficiency. The study highlights the need of integrating magnetometer data with other geophysical methods in order to comprehend metal depositions. The technology has potential applications in the fields of environmental protection, infrastructure inspection, and archaeology. The suggested approach entails the integration of drones equipped with magnetometers to enhance safety, efficiency, and precision in conducting surveys inside a volcanic region. The quadrotor drone equipped with magnetometers is a significant advancement in unmanned aerial vehicle (UAV) technology. It provides autonomous navigation capabilities, a magnetic interference compensator and a real-time metal detecting sensor.
Limited Resources Multi-Object Tracking by Utilizing Motion Cue from the Meanshift Algorithm

Multi-object tracking has various applications in intelligent surveillance systems. Substantial advancements have been made to enhance the accuracy of multi-object tracking. Nevertheless, many existing approaches struggle with real-time tracking in resource-constrained environments such as surveillance centers. While it's possible to get close to real-time tracking with low resources utilizing motion-based trackers, their framerates are frequently limited by detectors. In this article, we introduce a technique that reduces the frequency of object detectors and association algorithms calls in SORT-like trackers by performing target detection and data association every several frames, predicting the positions of bounding boxes between target detections using motion cues derived from the meanshift algorithm. By this mean, we achieved real-time multi-object tracking with an average end-to-end framerate of 38.09 fps on the MOT17 dataset on a single mobile RTX4060 65W, which is 230% of the original SORT implementation while maintaining most of the precision metrics evaluated in IDF1 and MOTA, significantly increasing the tracking framerate in resource-constrained scenarios.
Literature Review of Automatic Restoration of Arabic Diacritics

Arabic is one of the most commonly utilized languages on the internet. Arabic Natural Language Processing (NLP) has advanced greatly since the 1980s. Automatic diacritization is a major field in Arabic NLP because of two reasons: the lack of diacritics in most Arabic texts, and the importance of diacritics in reading. Numerous researches and studies were carried out to come up with the most effective approach for automatic restoration of Arabic diacritics. In general, three major categories were involved: linguistic approaches, machine learning approaches and hybrid approaches. In this literature review, we present a comparison of 20 articles that tackled this topic using different techniques.
LoRa Enhanced Real-Time Earthquake Monitoring System for Constructions Using IoT and Cloud

Robust earthquake monitoring systems are essential in seismically active areas such as construction sites to ensures the construction site safety, protect people, property and ongoing operations. Traditional techniques for earthquake monitoring are costly and it cannot be able to deliver real-time data sometimes. This proposed system provides a solution to overcome those problems. Here, LoRa is used for wide rage data transmission of earthquake data, IoT used to enhance the sensor integration. This system is designed to provide efficient, cost-effective, and real-time earthquake monitoring of seismic activities on construction sites. Details about the seismic events like ground vibrations and structural movements are obtained with the help of seismic sensors like Accelerometer, Gyroscope, Tilt sensor, Vibration sensor, Piezoelectric sensor, etc. In order to prioritize the people and construction site safety, an effective monitoring and communication systems can be implemented by integrating new technologies like LoRaWAN, IoT, Cloud based data analysis and visualization, real-time, cost-effective monitoring. With this capability, it can able to implement immediate, proactive security measures for both employees and infrastructure. This system interfaces with a cloud-based platform to simplify data management, analysis and visualization. Additionally, the platform offers straightforward dashboards and reporting capabilities. Data-driven decision- making and improved risk management are possible by harnessing the power of data analytics, which construction stakeholders can use to gain useful insights into the behavior of structures and the condition of the ground. It provides a practical and affordable method for the collection, transmission and analysis of real-time data, thereby increasing safety and reducing the impact of seismic events on building projects.
Teaching English by Using YouTube in SMP IT Al-Afkari Deliserdang

This study aimed to explore the use of YouTube videos in learning English, students' conclusions about improving their English skills after using YouTube videos, problems faced by teachers and students, and student acceptance of the use of YouTube videos. Bottom. While studying English. The respondents were 7 English teachers from the eighth exam and 40 second-year students from the 8th. This study used a mixed graft method as the study design. Information was collected through the dissemination of surveys. Our investigation revealed the following: a) The trainer was able to implement this process because he used a YouTube video technique to train some skills in English. Students had positive opinions about changes in English learning. Students also said that following this procedure could reduce boring classes and increase their motivation to learn English. There were issues in designing the evaluation process when implementing the YouTube video strategy, such as internet connectivity and student readiness. Teachers had to create procedures to help students better understand the topic. As a result of these reflections, her use of YouTube recordings in teaching and learning English positively impacted students' English proficiency and assisted teachers in communicating topics to students. The results were consistent with past reflection results. Was consistent. Aside from that, this program made some discoveries, such as teachers' practice methods, students' opinions on improving their English skills, and students' evaluations of the introduction of YouTube videos.
Evaluasi Program Pembelajaran Literasi Multibahasa di Sekolah Dasar

This research aims to evaluate the multilingual literacy learning program at SDN Ciborelang I. The research method used is a qualitative approach with phenomenological research design. Data were collected through interviews, classroom observations, and document analysis. The results of data analysis showed a significant improvement in students' multilingual literacy skills after participating in the program. These findings support previous research findings on the effectiveness of multilingual learning programs in improving students' language skills. Practical implications include the importance of developing inclusive curricula, providing ongoing teacher training, and involving parents and communities in supporting multilingual learning programs. Recommendations for future research include the development of new learning methods and deeper program evaluations. By implementing these steps, it is hoped that multilingual literacy learning programs can become more effective in preparing students to meet the demands of globalization and become competent citizens in various languages. This abstract provides a brief overview of the research and its findings, as well as presenting implications and recommendations for the development of multilingual learning programs in the future.
3D measurement using fringe projection profilometry

This work is devoted to measuring the depth of the 3D object using the structured light method, in particular, phase shift profilometry. Theoretical studies on the methods of three-dimensional measurement systems and fringe projection profilometry are presented. The phase shift profilometry method with an improved calculation of the frequency of sinusoidal patterns is applied. In practical implementation in the environment (20 cm × 30 cm), the algorithm is tested on a stepped object consisting of eight steps with a difference of 150 mm between two successive steps. In this case, the achievable error for measuring such an object is 20 mm. Our method has great potential in industrial applications where the measurement of the smoothing of the surface of the object is needed to find the defect in the surface with high accuracy without contacting the object.
Vis-SAGA: Visual Analytics for Situational Awareness of Grid Anomalies

We describe supporting near real-time situational awareness of the electric distribution system by visualizing novel data from voltage sensors deployed on existing broadband cable television network equipment. Our scalable web-based visual analytics platform supports interactive geospatial exploration, time-series analysis, and summarization of grid behavior during potentially anomalous events. The broadband cable television sensor network provides observability of the electrical distribution system at a higher local spatial resolution than is typically available to most utilities, revealing the operational state of the network and aiding in the detection of ab-normal behaviors or deviations from expected patterns, particularly across electric utility service areas. We outline the design and development of interactive geospatial and time-series visualization components and the scalable data services that supply metadata, historical, and real-time streams of sensor data across the network. We present our platform during periods of extreme weather, demon-strating its ability to assist in detecting patterns of operation that affect power availability, quality, resiliency, and service restoration.
Analysis Over Vision-Based Models for Pedestrian Action Anticipation

Anticipating human actions in front of autonomous vehicles is a challenging task. Several papers have recently proposed model architectures to address this problem by combining multiple input features to predict pedestrian crossing actions. This paper focuses specifically on using images of the pedestrian's context as an input feature. We present several spatio-temporal model architectures that utilize standard CNN and Transformer modules to serve as a backbone for pedestrian anticipation. However, the objective of this paper is not to surpass state-of-the-art benchmarks but rather to analyze the positive and negative predictions of these models. Therefore, we provide insights on the explainability of vision-based Transformer models in the context of pedestrian action prediction. We will highlight cases where the model can achieve correct quantitative results but falls short in providing human-like explanations qualitatively, emphasizing the importance of investing in explainability for pedestrian action anticipation problems.
Infrared Image Stripe Noise Removal by Solving First-And Second-Order Total Variation Inverse Problem

Stripe noise is a prominent type of noise in infrared imaging systems. It has a unique directional property where it usually appears as vertical lines imposed on the image. This paper introduces an algorithm that turns an image denoising problem into solving inverse problems for each row of the noisy image, giving users a powerful tool for destriping infrared images. This was done by integrating first- and second-order total variation (TV) regularizations, which has led to excellent denoising capabilities around edges and smooth areas. The algorithm's performance is carefully examined, along with comparisons to other denoising techniques, using simulated and real-world data, emphasizing the algorithm's superiority in terms of noise reduction and reconstruction accuracy. Comparing the proposed method to state-of-the-art techniques, it shows greater performance in improving the visual quality of the produced image.