Reviewerly/exHarmony huggingface dataset:
COMPARATIVE STUDY OF FONT RECOGNITION USING CONVOLUTIONAL NEURAL NETWORKS AND TWO FEATURE EXTRACTION METHODS WITH SUPPORT VECTOR MACHINE

Font recognition is one of the essential issues in document recognition and analysis, and is frequently a complex and time-consuming process. Many techniques of optical character recognition (OCR) have been suggested and some of them have been marketed, however, a few of these techniques considered font recognition. The issue of OCR is that it saves copies of documents to make them searchable, but the documents stop having the original appearance. To solve this problem, this paper presents a system for recognizing three and six English fonts from character images using Convolution Neural Network (CNN), and then compare the results of proposed system with the two studies. The first study used NCM features and SVM as a classification method, and the second study used DP features and SVM as classification method. The data of this study were taken from Al-Khaffaf dataset [21]. The two types of datasets have been used: the first type is about 27,620 sample for the three fonts classification and the second type is about 72,983 sample for the six fonts classification and both datasets are English character images in gray scale format with 8 bits. The results showed that CNN achieved the highest recognition rate in the proposed system compared with the two studies reached 99.75% and 98.329 % for the three and six fonts recognition, respectively. In addition, CNN got the least time required for creating model about 6 minutes and 23- 24 minutes for three and six fonts recognition, respectively. Based on the results, we can conclude that CNN technique is the best and most accurate model for recognizing fonts.
The Library as a Driver of Open Science: Essential Competences of the Librarian

There is a need to define the role of the library in the development and implementation of open science, based not only on the widespread concept of open access to scientific publications, but also on other principles. UNESCO’s concept of open science is presented in relationship with the concept of open knowledge analyzed in the context of three approaches: 1) “openness” from the point of view of copyright (unrestricted reading, distribution, processing of the original work and publication of derivative works); 2) scientific communication (interpretation of knowledge and its transfer between different scientific disciplines, governmental structures, social actors, non-scientists and non-scientific institutions, as well as publicly accessible communication); 3) open, comprehensible, verifiable knowledge, accessible to all members of society by means of well-known criteria. The directions of libraries' activities within the framework of open science are proposed. Some of the competences necessary for such activities are fixed in the professional standard “Specialist in Library and Information Activities”: the ability to organise a multifunctional library space, analytical and synthetic processing of documents, etc. The competences of the library specialist are also required. In addition, the library specialist needs additional knowledge about the essence of open knowledge (open scientific knowledge) and its key components, the basics of intellectual property legislation, the basics of research ethics, the organisation of open reviewing, the use of altmetrics, the organisation of open learning platforms. Taking into account the amount of knowledge and skills required, as well as the specificity of their application areas, it seems reasonable to train first of all employees of scientific, scientific-technical, and university libraries. With the new competences, library professionals will be able to contribute to the effective integration of their institutions into the research process. The library can become a real driving force for open science.
Risk and uncertainty assessment in software project management: integrating decision trees and Monte Carlo modeling

The evaluation of risk and uncertainty in the context of software project management is the subject of this paper. This paper discusses the difficulties faced by project managers in handling uncertainty brought on by the complex nature of software projects and the ever evolving requirements of technology. A review of the literature, data production, visualization, statistical analysis, and mathematical modeling are included in this study. The goal of this study is to create a methodical approach to assist project managers in making decisions by considering the inherent uncertainty in software development and to find approaches and procedures that may successfully reduce risks, improve decision-making, and eventually result in the implementation of successful projects. The following tasks were carried out: to evaluate risk and uncertainty by examining the state-of-the-art in decision theory and its applications in software project management; to develop an integrated strategy that blends Monte Carlo Simulation with Decision Trees to assess risk and uncertainty in software project management; to generate data, visualize it, and perform statistical analysis to comprehend how project outcomes, costs, and time are affected; to identify important variables affecting project results and decision-making using decision trees; to use Monte Carlo simulation to create project scenarios and weigh the likelihood of each; and to supply project managers with knowledge and suggestions to help them make informed decisions and successfully manage risks. Methods. To evaluate risk and uncertainty in software project management, this paper analyzes the decision theory approaches currently used as well as Decision Trees and Monte Carlo Simulation techniques. Results. This study offers thorough insights into how project results, costs, and duration vary among various techniques. The critical factors that have a substantial influence on project success are shown through decision trees. According to the study’s findings, combining decision theory and statistical analysis equips project managers to make wise decisions despite uncertainty. Conclusions. Project managers may improve decision making, risk reduction, and overall project success by applying these cutting-edge approaches. To adapt these techniques to unique software project management contexts and real-world situations, further study and implementation in practice are necessary. With the use of such techniques, the software development sector would be better able to manage the complexity of projects and provide good results within set financial and time parameters.
Augmented reality application areas for the architecture, engineering, and construction industry

Augmented reality (AR) is among the technologies that have the potential to advance the Architecture, Engineering, and Construction (AEC) industry. Yet, studies show that there remain challenges in applying AR in AEC. According to the literature, the use of AR is focused on the construction phase to address performance, supervisory, and safety-related concerns. However, other phases of AEC projects could also benefit from this technology. Accordingly, this chapter provides an application-centric study to assess the state-of-the-art applications areas of AR in the AEC industry. Various applications have been identified as visualization and simulation; in-situ experience; real-time information retrieval; maintenance, inspection, and repair; project documentation; heavy equipment operation; educational training; health and safety; site navigation; and automated measurements. To further explore these application areas, a case study was conducted using the AR solution of Trimble XR10 with HoloLens 2 in a precast construction context. The results show that existing AR technologies and systems for simulation/visualization and construction quality control are still immature. The study highlighted the current use cases, the potential for technology improvements, and the obstacles that hinder the widespread AR implementation in the AEC industry. Considering these factors, further directions and future research paths for innovators are proposed.
USING SPECIAL LETTERS AND DIACRITICS IN STEGANOGRAPHY IN HOLY QURAN

Because of the great development that took place in information transfer and communication technologies, the issue of information transfer security has become a very sensitive and resonant issue, great importance must be given to protecting this confidential information. Steganography is one of the important and effective ways to protect the security of this information while it is being transmitted through the Internet, steganography is a technology to hide information inside an unnoticeable envelope object that can be an image, video, text or sound. The Arabic language has some special features that make it excellent covers to hide information from Through the diversity of the Arabic letters from dotted letters in several forms or vowels or special letters, the Holy Qur’an is considered a cover rich in movements and Arabic grammar, which makes it a wide cover for the purpose of concealing information. The Holy Qur’an is a sacred book where it is not permissible to modify, add or move any of the letters or any diacritical mark to it. The algorithm hides the two bits by uses six special letters of Arabic language. Moreover, it checks for the presence of specific Arabic linguistic features referred Arabic diacritics. The proposed system achieved a high ability to hide as in Surat Al-Baqarah (4524 bits) and also (2576 bits) in Surat Al-Imran and in Surat Al-An’am (2318 bits).
Designing A Web-Based Credit Application Information System

In today's technological developments, the role of Internet media must be addressed. The ease of doing online activities certainly must be connected to the critical role of websites in it. One of the benefits of applying the Internet in the banking sector is simplifying work processes such as processing data for credit applications. The system being used to process data at one of the Sharia financial institutions in Bandung still needs to be better organized, so it is less effective and efficient, less accurate, or errors often occur, and also takes up much space for customer documents. Therefore, the author is interested in building a system expected to overcome the problems faced by one of the Sharia financial institutions in Bandung. This system was formulated as "Designing a Web-Based Credit Application Information System (Study at one of the Sharia financial institutions in Bandung)." The method the author uses is a qualitative descriptive method. The system development method that the author uses is the object-oriented method, namely OOSE. The author used PHP, MySQL, and XAMPP as tools to create this website. The results of this accounting information system application research can help simplify data processing at one of the Sharia financial institutions in Bandung that has been running so far.
IMPLEMENTASI MANAJEMEN PEMBIAYAAN (Di MTs Miftahul Jannah Nagreg Kabupaten Bandung)

ABSTRACT&#x0D; This study aims to determine the implementation of financial management in Madrasah Tsanawiyah, as well as related to supporting and inhibiting factors in Madrasah Tsanawiyah, especially in Madrasah Tsanawiyah Miftahul Jannah Nagreg Kab. Bandung. The existence of this research originated from the importance of financing and finance in Islamic education institutions because financing is one of the supporting components and is important for activities in the education process at Madrasah. The type of research in this research uses field research and includes descriptive qualitative research, this research is through data sources from information and documents, data collection techniques are through interviews, documentation, and observation, and using data analysis techniques, namely data reduction, data presentation, and then withdrawal. conclusion. The results of this study indicate that the financing management carried out at MTs Miftahul Jannah Nagrek Kab. Bandung, namely: (1) the financing system at Madrasah Tsanawiyah Miftahul Jannah refers to the Indonesian Government Regulation on Education Funding and national education standards (SNP) PP RI No. 19 of 2005 in article 62. (2) In addition, the funding for education that runs at MTs Miftahul Jannah uses the full cost of the School Operational Assistance (BOS) funds, and there is no collection of any funds to students/parents of students so that all students are 100% free. (3) The supporting factors include supporting infrastructure and human resources according to standards. (4) The obstacle is the small amount of budget input obtained by MTs Miftahul Jannah Nagreg Kab. Bandung.&#x0D; Keywords: Management, Financing, Madrasah.
FACIAL RECOGNITION-BASED IDENTITY VERIFICATION AND DETECTION SYSTEM

This scientific investigation is dedicated to an in-depth exploration and comprehensive evaluation of the Haar cascade classifier method as an essential component of facial recognition technology. In addition to its rigorous analysis, this paper substantiates the rationale behind selecting this particular algorithm and offers a detailed account of the system's implementation process, shedding light on the intricacies of the experimental setup employed for our study. The crafted facial recognition system underwent rigorous testing using a diverse dataset of facial photographs. This dataset included a broad spectrum of images captured at varying distances from the camera, under diverse lighting conditions, and encompassing various facial orientations within the camera's field of view. Subsequent to the extensive testing phase, a meticulous analysis of the test results was meticulously conducted. These results provided valuable insights into the system's strengths and weaknesses, highlighting the significance of certain factors in achieving optimal accuracy in facial recognition technology. The in-depth evaluation allowed us to draw robust conclusions regarding the critical considerations essential for the effective design and deployment of facial recognition systems aimed at attaining exceptionally high levels of precision and reliability. By identifying these factors, our research contributes significantly to the advancement of facial recognition technology, paving the way for more accurate and dependable systems in various applications. Key words: system, recognition, device, face tracking. algorithm, Haar classifiers.
Application of Advanced State Space Grids to the analysis of physics teaching

In this chapter, the final research question “How can the ASSG method be used for the analysis of physics teaching?” is addressed. The application of the ASSG method will be divided into general applications and specific applications. The two specific applications that are of particular interest for the analysis of physics teaching are dealt with in Section 11.3 and Section 11.4.
ON THE USE OF SUBJECT-ORIENTED ONTOLOGIES TO SUPPORT DECISION-MAKING IN THE PROFESSIONAL ACTIVITY OF A TEACHER

The work considers the issues associated with the organization of professional activity of a teacher in terms of automation of decision support. It carries out the analysis of the use of DSS (decision support system) in various fields of human activity. Results of the analysis showed that IDSS (intelligent decision support systems) are widely and effectively used in the field of Education, however, due to the diversity of areas of pedagogical activity, many issues remain unresolved at the moment. The work proposes to use such a class of systems to support the DM (decision-maker), i.e. the teacher, when choosing the optimal strategy or set of strategies aimed at improving the effectiveness of preparing the student to perform the tasks of the “Written part” of the Unified State Exam in English. The authors proposed using domain-oriented ontological models as the framework for the Knowledge Base (KB) of such a system. Due to the fact that the development of IDSS is a complex task, the purpose of the present work is to develop a subject–oriented ontological model of task evaluation criteria with a detailed answer “Personal email” of the Unified State Exam in the open ontology editor Protégé 5.6.1.
Unsupervised Entity Alignment

Abstract State-of-the-art entity alignment solutions tend to rely on labeled data for model training. Additionally, they work under the closed-domain setting and cannot deal with entities that are unmatchable. To address these deficiencies, we offer an unsupervised framework that performs entity alignment in the open world. Specifically, we first mine useful features from the side information of KGs. Then, we devise an unmatchable entity prediction module to filter out unmatchable entities and produce preliminary alignment results. These preliminary results are regarded as the pseudo-labeled data and forwarded to the progressive learning framework to generate structural representations, which are integrated with the side information to provide a more comprehensive view for alignment. Finally, the progressive learning framework gradually improves the quality of structural embeddings and enhances the alignment performance by enriching the pseudo-labeled data with alignment results from the previous round. Our solution does not require labeled data and can effectively filter out unmatchable entities. Comprehensive experimental evaluations validate its superiority.
Comparative study of methods to identify sensitive parameters for improving performance of predictive models

Machine learning models map inputs to predictions. Supervised machine learning models learn from a dataset containing several samples or experiments by assigning a weightage to each of the input parameters, commonly referred as features, so as to map to the corresponding target outcome. Different algorithms are used in the learning process, each following a set of rules to achieve the stated objective of mapping features to the corresponding value of target. In this development process, algorithms assign weights to each feature and refine them iteratively to reduce the error between the predicted outcomes with the actual value in the dataset. It is observed that each type of algorithm is based on certain themes such as linear, tree-based, kernel, etc. Each adoption of each of these themed algorithms assigns different weights to features to arrive at the target outcome while reducing the error with the actual value. Iterations alter the weights of parameters until fully tuned and hence there is a need to get reliable weights early in the model development process.
Performance analysis of naive bayes in text classification of islamophobia issues

In the aftermath of the 2013 Woolwich attack, a disturbing surge in hate crimes against the Muslim community emerged both offline and on social media platforms, prompting concerns about the widespread issue of Islamophobia. To systematically evaluate and quantify the presence of Islamophobic sentiment in online spaces, this study employed sentiment analysis, a robust method for deriving insights from textual data. Two classification models, Bernoulli Naive Bayes and Multinomial Naive Bayes, were selected to conduct a thorough analysis. Bernoulli Naive Bayes, specialized in handling binary data, was used for binary sentiment analysis, while Multinomial Naive Bayes, well-suited for data with multiple occurrences, was applied for more comprehensive analysis. The research encompassed nine meticulously designed test-train data scenarios, ranging from a 10:90 test-train data ratio to a 20:80 ratio. Surprisingly, both models exhibited a maximum accuracy rate of 68% in their respective optimal scenarios, raising intriguing questions about the potential and limitations of sentiment analysis and Naive Bayes models in the complex task of identifying and quantifying Islamophobic content on social media
Face Recognition Attendance Monitoring System

Abstract: As we know attendance is the crucial part in colleges, schools, corporate offices etc. Attendance plays an important role for keeping track of student’s record. Mostly attendance is taken manually in most of the colleges and schools. The manual attendance process involves taking attendance by calling the name or by signing the attendance sheet. This manual process is very time consuming and it is difficult to maintain the attendance record. Due to this drawback of manual attendance system, there is a need of automated attendance system. Here facial recognition plays an important part for automated attendance system. This suggested study focuses on face detection algorithm to provide automated attendance system. This proposed system uses Histogram of Oriented Gradients (HOG) and Deep Convolutional Neural Network for face detection and face recognition respectively to build automated attendance system.
Sign Language to Speech Conversion

Abstract: A huge population in India alone is of the dumb and deaf people. So the system is working on a glove based device which will be used for conversion of sign language (ASL) to speech .The basic system consists of a two parts; sign language recognition and conversion to text and further to speech. The sign language glove consist of a simple hand gloves fitted with flex sensors which is being used for the monitoring the amount of bend on the fingers. Flex means bend, this is the sensors that change the resistance depending on the amount of bend on the sensor. Data from the sensors is send to the Control unit which is the Arduino Nano the analog signals from the sensors are digitally converted and compared with the stored value for the recognition of sign and then displayed as a text on the 16x2 LCD. Further the text output is wirelessly transmitted to a cellular phone or a PC which consist of a test to speech conversion software.
VIRD: Immersive Match Video Analysis for High-Performance Badminton Coaching

Badminton is a fast-paced sport that requires a strategic combination of spatial, temporal, and technical tactics. To gain a competitive edge at high-level competitions, badminton professionals frequently analyze match videos to gain insights and develop game strategies. However, the current process for analyzing matches is time-consuming and relies heavily on manual note-taking, due to the lack of automatic data collection and appropriate visualization tools. As a result, there is a gap in effectively analyzing matches and communicating insights among badminton coaches and players. This work proposes an end-to-end immersive match analysis pipeline designed in close collaboration with badminton professionals, including Olympic and national coaches and players. We present VIRD, a VR Bird (i.e., shuttle) immersive analysis tool, that supports interactive badminton game analysis in an immersive environment based on 3D reconstructed game views of the match video. We propose a top-down analytic workflow that allows users to seamlessly move from a high-level match overview to a detailed game view of individual rallies and shots, using situated 3D visualizations and video. We collect 3D spatial and dynamic shot data and player poses with computer vision models and visualize them in VR. Through immersive visualizations, coaches can interactively analyze situated spatial data (player positions, poses, and shot trajectories) with flexible viewpoints while navigating between shots and rallies effectively with embodied interaction. We evaluated the usefulness of VIRD with Olympic and national-level coaches and players in real matches. Results show that immersive analytics supports effective badminton match analysis with reduced context-switching costs and enhances spatial understanding with a high sense of presence