Reviewerly/exHarmony huggingface dataset:
Digital Humanities Projects in Educational Process

The purpose of the study is to outline the main directions and prospects of digital humanities development; to find out the main principles of the scientific space transformation, caused by the implementation of digital humanities; to define the transdisciplinary ontology as digital humanities important tool. Methodology of the article is based on implementation of principle of information systematicity and its further modeling in educational and scientific aspects. The information is being analysed for distinguishing its structural components and their semantic and functional coherence. According to the structural and semantic analysis of information, the modeling of information representation is performed. As the productive way of modeling is the transdisciplinary ontology, so principle of transdisciplinarity is one of the basical principle in the study. Transdisciplinary ontology seems to be an important tool of digital humanities. Using ontology it is possible to perform educational information in structured form with all its components, organized in hierarchical construction, and their correlation depiction. Transdisciplinary ontology provides various forms of information graphical display, perception of which helps to understand essential causal factors, principles of information arrangement, its regularities Recommendation for further transdisciplinary ontology application is based on the possible ontology extention by new elements adding according to the enrichment of educational material being learned.
Tourism Local Lore in the Modern System of Education

This article covers the main approaches to implementing tourism local lore in the course of education. The problem is relevant due to the demand for competent specialists who are capable to form contemporary children`s competence in the course of education. Therefore, the theoretical-methodological analysis of the researchers of the problem identified, who became the rationale for the main results of the research to be determined, is provided in this paper. It is also ascertained that it is necessary to form a structured part of the professional competence of a rising geography teacher – local lore competence. There is some dependence of the level of qualification of rising teachers on an accurately planned process of formation of not only knowledge, skills and capabilities, but also personal traits of students formed at a higher educational institution. The concepts of native land, local lore and tourism, their correlation, conduction forms, functions are studied in the researches of scholars and according to the results of this theoretical research. In addition, the local lore principle is set as competency-based learning. The method of analysis, scientific, descriptive and research methods are used for studying tourism local lore in the contemporary system of education. Analysing the role of tourism local lore proves the demand for searching and gaining knowledge about a native land, optimising the study of major subjects, forming an individual cognitive experience of students-geographers. Such conclusions are the results of this research.
Interpretability and Explainability: A Machine Learning Zoo Mini-tour

In this review, we examine the problem of designing interpretable and explainable machine learning models. Interpretability and explainability lie at the core of many machine learning and statistical applications in medicine, economics, law, and natural sciences. Although interpretability and explainability have escaped a clear universal definition, many techniques motivated by these properties have been developed over the recent 30 years with the focus currently shifting towards deep learning methods. In this review, we emphasise the divide between interpretability and explainability and illustrate these two different research directions with concrete examples of the state-of-the-art. The review is intended for a general machine learning audience with interest in exploring the problems of interpretation and explanation beyond logistic regression or random forest variable importance. This work is not an exhaustive literature survey, but rather a primer focusing selectively on certain lines of research which the authors found interesting or informative.
Improving Organizations Security Using Visual Cryptography Based on XOR and Chaotic-Based Key

Since data security is an important branch of the wide concept of security, using simple and interpretable data security methods is deemed necessary. A considerable volume of data that is transferred through the internet is in the form of image. Therefore, several methods have focused on encrypting and decrypting images but some of the conventional algorithms are complex and time consuming. On the other hand, denial method or steganography has attracted the researchers' attention leading to more security for transferring images. This is because attackers are not aware of encryption on images and therefore they do not try to decrypt them. Here, one of the most effective and simplest operators (XOR) is employed. The received shares in destination only with XOR operation can recover original images. Users are not necessary to be familiar with computer programing, data coding and the execution time is lesser compared to chaos-based methods or coding table. Nevertheless, for designing the key when we have messy images, we use chaotic functions. Here, in addition to use the XOR operation, eliminating the pixel expansion and meaningfulness of the shared images is of interest. This method is simple and efficient and use both encryption and steganography; therefore, it can guarantee the security of transferred images.
A plan for students' independent study of blended learning in the English Department of STKIP Al Maksum

The purpose of this essay is to evaluate how well students are performing on their own in blended learning in language courses at institutions, STKIP Al Maksum with the ultimate objective of finding obstacles and opportunities for self-directed study. 100 students from the Department of English, STKIP Al Maksum will be surveyed online in October 2022 as part of this study. Several significant conclusions can be derived from the findings. The socioeconomic and demographic backgrounds of English Department faculty members influence students' abilities to self-organize and effectively use technology to study a second language. Students completing independent work in blended learning of foreign languages at the English Department face the following challenges: technical and the need for support from a technical specialist; the inconvenient nature of a blended learning system; the requirement for additional technical skills; the complexity of blended learning. It has also been determined, on average, how effective the blended learning system and technology make the learning process.
A hybrid approach of missing data imputation for upper gastrointestinal diagnosis

Gastrointestinal and liver diseases (GILDs) are the major causes of death and disability in Middle East. The investigation of upper gastrointestinal (GI) symptoms of a medically limited area resource is a challenge. The analysis of real-world clinical data of upper gastrointestinal (GI) using data mining techniques often is facing observations that the data contains missing values. In this paper, the proposed approach to missing data imputation is accomplished for categorical data onto upper GI diseases to apply the feature selection and classification algorithms with accurate and effective results for diagnosing upper GI diseases. This approach is evaluated by implementing experimental framework to apply five phases. These phases aim at partitioning the dataset to eight different datasets; with various ratio of missing data, performing the feature selection, imputing the missing data, classifying the imputed data, and finally, evaluating the outcome using k-fold cross validation for nine evaluation measures.
Comprehensive retrieval method of MOOC teaching resources based on eigenvalue extraction

In order to solve the problems of traditional MOOC teaching resources retrieval methods, such as low retrieval accuracy, poor retrieval recall and low retrieval efficiency, this paper proposes a comprehensive retrieval method of MOOC teaching resources based on eigenvalue extraction. The feature value of MOOC teaching resources is extracted by grey level co-occurrence matrix, and the similarity calculation of resource content features is realised by feature attribute annotation. The MOOC teaching resources search process is designed, and the comprehensive retrieval of MOOC teaching resources is realised by feature value extraction. The experimental results show that the retrieval accuracy of this method is low, the retrieval recall rate is as high as 95%, and the retrieval efficiency of teaching resources is effectively improved.
Metaheuristic Algorithms Based Server Consolidation for Tasks Scheduling in Cloud Computing Environment

Due to the large migration of applications from traditional computing environments to cloud systems, task scheduling has become a well-known research topic. Further, assigning tasks is an essential step in the server consolidation that enables clients’ needs to be mapped to suitable resources, such as Physical Machines (PMs) or Virtual Machines (VMs). The difficulty lies in using the available shared computing resources for various tasks without degrading the quality of service (QoS) or increasing the carbon footprint. In addition, the cloud provider needs to use a good task strategy based on the requirements of the client and the IT resources capacity. The best resource utilization and quickest task execution completion times are essential metrics for a cloud provider to maintain the optimum performance of the cloud system. The appropriate solution distributes tasks to the available virtual machine while applying optimization techniques such as the artificial bee colony (ABC), the cuckoo search (CS) algorithm, and particle swarm optimization (PSO). This paper will analyze the algorithms mentioned above based on energy consumption and resource utilization.
Can representation learning for multimodal image registration be improved by supervision of intermediate layers?

Multimodal imaging and correlative analysis typically require image alignment. Contrastive learning can generate representations of multimodal images, reducing the challenging task of multimodal image registration to a monomodal one. Previously, additional supervision on intermediate layers in contrastive learning has improved biomedical image classification. We evaluate if a similar approach improves representations learned for registration to boost registration performance. We explore three approaches to add contrastive supervision to the latent features of the bottleneck layer in the U-Nets encoding the multimodal images and evaluate three different critic functions. Our results show that representations learned without additional supervision on latent features perform best in the downstream task of registration on two public biomedical datasets. We investigate the performance drop by exploiting recent insights in contrastive learning in classification and self-supervised learning. We visualize the spatial relations of the learned representations by means of multidimensional scaling, and show that additional supervision on the bottleneck layer can lead to partial dimensional collapse of the intermediate embedding space.
Solution to Last Month’s Quiz [Enigmas, etc.]

The RF voltage source <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">v</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</i> ) has a sinusoidal waveform, which can be expressed
Pengaruh Game Pembelajaran Bahasa Arab sebagai Sarana Pembelajaran Jarak Jauh

This research departs from the basic problem of declining student achievement at MI Nurussalam Dadung in Arabic lessons. During the pandemic, the learning process was carried out only by distributing lessons via WhatsApp without face-to-face meetings. Learning Arabic must be done directly so that students fully understand the sound, writing, and meaning of words. Because of this, there was a decrease in students' abilities, especially in Arabic lessons after the implementation of the distance learning system. Then, the researcher is interested in studying the use of learning games to assist the learning process when the distance learning system is implemented. This study aims to determine the effect of Arabic learning games on distance education. This research is based on the premise that the use of learning media can improve students' abilities in learning Arabic during the distance learning process. The results of this study are that the use of Arabic learning games is effective in developing students' abilities in Arabic lessons during distance learning but at a low level of effectiveness. In addition, learning media in the form of learning games also have a positive influence on students and teachers in the learning process, especially in distance learning.&#x0D; Keywords: Instructional Media; Arabic Learning Game; Distance Learning
Key-frame extraction based video watermarking using speeded up robust features and discrete cosine transform

Due to advancements in the internet and multimedia technologies, unauthorised users can easily modify video content. As a result, video authentication has been established as a viable solution for ensuring multimedia security. We propose a key-frame based video watermarking scheme based on discrete cosine transform (DCT). First, the pearson correlation coefficient (PCC) is used to detect the shot boundaries of the input video. To reduce the difficulties created by traditional video watermarking systems; an entropy measure is employed to detect key-frames from input video. Traditional schemes entail embedding the entire watermark into all frames of the video, which is inefficient and time-consuming. To improve the security, robustness, and imperceptibility of the proposed video watermarking scheme, speeded up robust feature points are extracted from each key-frame of the shot and used as reference points for embedding and detection of watermark. The embedded watermark is extracted blindly without using the original data during the extraction process. The results of the experiments reveal that the proposed technique effectively detects shot boundaries under a variety of camera operations and outperforms in terms of imperceptibility and resilience.
Cryptoeconomics as governance: an intellectual history from “Crypto Anarchy” to “Cryptoeconomics”

Existing scholarship on cryptoeconomics describes this field as a new and emergent phenomenon. In this paper, I claim that crypto anarchists and cryptoeconomists design and build decentralised networks as governance systems according to the common principles of cryptography, economics, and engineering, and thus, cryptoeconomics is not new but has historical intellectual roots in the political ideology of Crypto Anarchy. Cryptoeconomics is a multidisciplinary field of study concerned with the design of decentralised systems that facilitate the coordination of multiple actors. Practitioners of crypteoconomics, known as “cryptoeconomists,” employ engineering and economic methods to create institutional infrastructure for social coordination. Crypto Anarchy is a political ideology that emphasises autonomy and anonymity and the practice of self-organising through technical means largely attributed to a counter-cultural subgroup known as the “cypherpunks”. I demonstrate the link between Crypto Anarchy and cryptoeconomics through the analysis of empirical evidence from primary archival sources, secondary sources, and academic literature. The implication of these findings is a deeper understanding of what the creation of cryptoeconomic systems does in enabling a political economy of distributed, autonomous coordination. What cryptoeconomists did not adopt and perpetuate is a value for anonymity, which is where the social outcomes of Crypto Anarchy and cryptoeconomics diverge.
Water Quality Assessment of Wenyu River with Variable Weight Cloud Model

The water resource is an important guarantee of social and economic sustainable development. The improvement of water’s ecological carbon sequestration ability is a direct response to the goal of “double carbon”. Water quality directly affects its carbon sequestration capacity. So it is necessary to understand the water quality of rivers. In view of the fuzziness and uncertainty in water quality evaluation, this paper uses the cloud model to realize the qualitative to quantitative transformation of water quality in Wenyu River. By combining moment estimation theory with critic weight, AHM weight, and variable weight theory. A water quality evaluation method integrating a variable weight cloud model is constructed. And the temporal and spatial changes in water quality in Wenyu River are studied. The results show that the combined weights balance the influence of each index while retaining the advantages of subjective and objective weights. The results of the water quality evaluation are consistent with the practice, which verifies the feasibility and applicability of the method.
The IT Services Management Architecture Design for Large and Medium-sized Companies based on ITIL 4 and TOGAF Framework

The development of information technology occurs rapidly in almost all areas of life. All companies must immediately carry out a business transformation following the development of information technology to survive amid increasingly fierce competition. One of the keys to this business transformation's success is an enterprise architecture that is used as a reference in planning, developing, operating, and monitoring company information technology. Implementation of service management practices in state-owned enterprises needs to be translated into IT Services Management Architecture Design, that match the IT Governance Principles as mandated in PER-03/MBU/02/2018. This research focuses on preparing an enterprise architecture design in IT service management by referring to ITIL 4 best practices. The resulting solution is a target architecture design in the business domain, data, and applications arranged according to the TOGAF framework. It was carried out in four stages: scope identification, which defines practices; preliminary phase, which resulted in 11 architecture principles; architecture vision that produces a value chain for IT service provider organizations; a business architecture which resulted in a business service/function catalog consisting of 13 business functions and 43 business services; and an information system architecture that produces a conceptual data model on the three main priority processes of IT service management and an application use-case diagram that describes the relationship between the four actors (users, service managers, service desks, and support groups) with their roles in applications. The enterprise architecture has been designed following the scope of IT service management practices commonly used as a reference for all large and medium-sized companies.
Optimizing Hand Gesture Recognition Using CNN Model Supported by Raspberry pi for Self-Service Technology

This study describes the optimization of hand gesture recognition on Raspberry Pi 4 technology has advanced over the past years, some computers are now able to compute much more complex problems like real-time object detection. But for small devices, optimization is required to run in real-time with acceptable performance in terms of latency and low-cost effect on accuracy. Low latency is a requirement for most technology, especially when integrating real-time object detection as input into Self-Service Technology on Raspberry Pi for the store. This research was conducted on 288 pictures with six types of chosen hand gestures for command inputs that have been configured in the Self-Service Technology as a training dataset. In the experiment carried out with 5 CNN object detection models were used, namely YOLOv3-Tiny-PRN, YOLOv4-Tiny, MobileNetV2-Yolov3-NANO, YOLO-Fastest-1.1, and YOLO-Fastest-1.1-XL. Based on the experiment after optimization, the FPS and inference time metrics have improved performance. The performance improves due to a gained average value of FPS by 3 FPS and a reduced average value of inference time by 119,260 ms. But such an improvement also comes with a reduction in overall accuracy. The rest of the parameters have a reduced score on Precision, Recall, F1-Score, and some for IoU. Only YOLO-Fastest-1.1-XL have an improved value of IoU by about 0.58%. Some improvements in the CNN and dataset might improve the performance even more without sacrificing too much on the accuracy, but it's most likely suitable for another research as a continuation of this topic.
Assessing Rural Community Empowerment through Community Internet Centre: Using Asset Mapping and Surveys Method

This paper assesses community empowerment through Community Internet Centre. Community empowerment is a process of the outcome made by the community to take action and change or improve the community's quality of life. Hence, adopting Information and Communication Technology would bridge the digital divide in rural areas. The digital divide affected rural community development through numerous barriers that widened the gap between urban and rural communities, consequently generating an imbalance in community development. The community internet center can bridge the digital divide among urban and rural communities. Asset mapping and surveys have been measured to assess rural community empowerment dimensions through distributed questionnaires to eight Community Internet Centres in rural areas of Kelantan. The findings indicate that the Internet Centre is a medium to encourage community empowerment. The Internet Centre bridges the digital divide among communities by providing Information and Communications Technology community building in rural areas. Hence, the center drives community empowerment and improves the quality of life in rural communities. Thus, Community Internet Centre prepared an appropriate platform for empowering the rural community. This is evidence based on the outcome of findings which resulted in three domains of community empowerment: (1) community participation, (2) ownership, and (3) information services. Nevertheless, community participation determined the outcomes of the roles played by the center to empower a community. Further study needs to be conducted in other groups of samples and gaining other perspectives from managerial of the internet center to get different views of the internet center program.
Evaluation of the Visual Learning Application for Mathematics using Holography Display for the topic on Shape and Space

Mathematics is an important foundation in the life of an individual. The problems associated with learning Mathematics that are commonly encountered, are due to factors such as: abstract phenomena and concepts, low imagination, and lack of understanding of the concepts being studied. Thus, the purpose of this study is to help primary school children improve their ability to recognise 3D shapes that are abstract phenomena. This paper presents the Effectiveness Usability Evaluation of the Visual Learning Application for Mathematics using Holography Display for the topic on Shape and Space called MEL-VIS. This study was conducted on eighty (80) primary school students. The results of the study showed that learning about 3D shapes with the E-Visual MEL-VIS application prototype is more effective than traditional methods.