Reviewerly/exHarmony huggingface dataset:
Decentralized Storage Rental System

Abstract: In the era of exponential digital data growth, the Decentralized Storage Rental System addresses critical challenges in data management within a context defined by increasing volumes of information, cybersecurity threats, and limitations of traditional centralized storage infrastructures. The widespread utilization of digital assets demands innovative approaches to guarantee data security, integrity, and accessibility. This project systematically analyzes these challenges and proposes an advanced solution that leverages blockchain technology and a network of decentralized storage nodes. By adopting this innovative approach, the system provides users with a seaamless experience in renting storage space, uploading, and accessing data securely. Through the implementation of smart contracts, the system ensures transparent and reliable transactions, while the decentralized storage nodes guarantee data availability and resilience against potential failures. In conclusion, the Decentralized Storage Rental System not only addresses the existing challenges in data management but also offers a glimpse into the future of secure and decentralized data storage solutions.
Script Independent Document Analysis for Forensics

Abstract: The main objective of this research is to utilize ink analysis for the identification of forgeries in handwritten documents, particularly checks. The completion of this study involves the application of motif feature extraction techniques, including Peano scan motif, Directional local motif, and third-order recombination between RGB planes. Following Method 1, the Peano scan motif is employed. To detect ink forgeries, 112 check images were examined, each written with fourteen different pens. A MATLAB function is applied to extract features for each of the mentioned approaches. The Weka application is utilized for both testing and training to validate the accuracy of the techniques. Typically, motif approaches like Peano scan motif, Directional local motif, and third-order recombination are used for identifying comparable items in databases, such as content-based picture retrieval systems. What sets this project apart is its innovative use of ink level forgery detection. The recombination approach, involving modified color planes and the previously mentioned Peano scan motif method, introduces a novel aspect to the study.
FaceBreach Alert: Multi-Modal Intrusion Detection emphasizing Face Recognition

Abstract: The face is one of the easiest ways to distinguish the individual identity of each other. Face recognition is a personal identification system that uses personal characteristics of a person to identify the person's identity. Human face recognition procedure basically consists of two phases, namely face detection, where this process takes place very rapidly in humans, except under conditions where the object is located at a short distance away, the next is the introduction, which recognize a face as individuals. Stage is then replicated and developed as a model for facial image recognition (face recognition) is one of the muchstudied biometrics technology and developed by experts. There are two kinds of methods that are currently popular in developed face recognition pattern namely, Eigenface method and Fisher face method. Facial image recognition Eigenface method is based on the reduction of face dimensional space using Principal Component Analysis (PCA) for facial features. The main purpose of the use of PCA on face recognition using Eigen faces was formed (face space) by finding the eigenvector corresponding to the largest eigenvalue of the face image. The area of this project face detection system with face recognition is Image processing. The software requirements for this project is MATLAB software.
Auto-numbered list continuations

Pandoc’s Markdown allows for “fancy lists”, i.e., lists with different styles used for the marker of ordered list items. E.g., the list (I) primus (#) secundus (#) tertius uses uppercase roman numerals and double parentheses for the markers. It gets rendered as primus secundus tertius Continuations The fancy lists feature also allows to continue lists after an intermediate paragraph: i. one #. another Interruption;
Meningkatkan Motivasi Belajar Siswa Melalui Metode PBL Materi Kisah Pembebasan Bangsa Israel Pak Kelas IV SDN 08 Buluh Merindu

The background of this research is the low learning motivation of students at SDN 08 Buluh Merindu. Research Method Using Quantitative The results of the Cycle 1 research showed that students' success rate in understanding the material was 79%. However, only 40% of students reached the new skill level, 50% of students were at the proficient level, and 10% of students were at the adequate level. In cycle 2, research data shows that student learning motivation has reached the set target of 79%. In terms of achieving skill levels, 60% of students are at the advanced level, 30% of students are at the proficient level, and only 10% of students are at the adequate level. The application of the Problem Based Learning (PBL) method in Catholic Religious Education lessons has been proven to improve student learning outcomes and motivation. The implication of these findings is that the Problem Based Learning (PBL) learning model has been proven to be able to increase student learning motivation in the classroom.
AN ANALYSIS OF BLENDED LEARNING IN ENGLISH EDUCATION DEPARTMENT OF UIN SULTHAN THAHA SAIFUDDIN JAMBI

This research aims to discover third-semester students' perceptions of integrated learning in speaking skills implemented during the previous two semesters at the English Education Study Programme at the State Islamic University of Malaysia. The Sulthan Thaha Saifuddin Jambi University. The researcher carried out a qualitative investigation. Through interviews, information is collected. The researcher employed a technique of purposive sampling by selecting 10 students from each third-semester class based on information gleaned from their classmates and previous grades. This research included 30 participants. 15 open-ended questions were developed based on Schiffman and Kanuk's (2004) theory, the CAC model, which incorporates cognitive, affective, and conative components. Positive and negative perceptions of integrated learning in speaking classes over the past two semesters are revealed by the study's findings. Positive perceptions of the cognitive component include the ability to reduce the spread of Covid-19 at the time, the use of technology that is currently being developed in the education world, and the capacity to locate information from a variety of sources. Positive perceptions in the affective component, such as learning, can be achieved at any time and in any location. Nonetheless, there are negative perceptions, such as in the cognitive component, due to the lecturer's material being indistinct and the students' pronunciation being difficult to understand due to the poor internet connection. While the negative perception of the affective component is that students cannot manage their time between an online and offline discussion of the next topic, this is not the case. In contrast, the conative component focuses on the absence of interaction between new students and the content of online classes. In fact, some of the difficulties they encountered during the previous two semesters included a poor internet connection, the absence of an internet bundle on campus, and the separation of online and offline instruction.
Invariant-based Mapping of Space During General Motion of an Observer

This paper explores visual motion-based invariants, resulting in a new instantaneous domain where: a) the stationary environment is perceived as unchanged, even as the 2D images undergo continuous changes due to camera motion, b) obstacles can be detected and potentially avoided in specific subspaces, and c) moving objects can potentially be detected. To achieve this, we make use of nonlinear functions derived from measurable optical flow, which are linked to geometric 3D invariants. We present simulations involving a camera that translates and rotates relative to a 3D object, capturing snapshots of the camera projected images. We show that the object appears unchanged in the new domain over time. We process real data from the KITTI dataset and demonstrate how to segment space to identify free navigational regions and detect obstacles within a predetermined subspace. Additionally, we present preliminary results, based on the KITTI dataset, on the identification and segmentation of moving objects, as well as the visualization of shape constancy. This representation is straightforward, relying on functions for the simple de-rotation of optical flow. This representation only requires a single camera, it is pixel-based, making it suitable for parallel processing, and it eliminates the necessity for 3D reconstruction techniques.
Orchestration of model computing assets for the development of digital twins

With the development of industries and manufacturing requirements, the use of digital twin technology is promising for increasing efficiency and improving product quality. An important component of digital twin implementation is the provision of tools for modeling and simulation processes. In this study, a solution based on the use of Python-based models and the Controller software platform, which provides communication between models and external elements of digital twins and other IIoT solutions, was proposed as such a toolkit. It defines the main approaches for creating model, scenario, and function libraries, along with the concept of implementing dynamic scenarios based on JSON requests from the orchestrator. In addition, the algorithm, the structure of the Controller, and its main functionality are considered. The resulting solution takes advantage of the Python and Node.js languages in performing the relevant tasks and contains several solutions that reduce traffic and workload on communication systems, increase system reliability, scale the system, etc.
Minimizing the time for UAV to reach a moving target

In this study, we address the control challenges of directing a flying object, specifically a drone, to a designated target, utilizing coordinates relayed from a monitoring device. Monitoring device delivers information about coordinates of suspicious object to drone. Upon receiving signals from a monitoring device about potential threats on the ground, the drone is tasked to promptly respond, identify, and neutralize the suspicious object. This article deals with the issue of controlling the process of flying snow to the target in the shortest possible time.
Distillation of Large Language Models for Text Simplification

This work presents a comprehensive methodology for harnessing the capabilities of Large Language Models to address specific Natural Language Processing tasks, with a focus on Text Simplification. While LLMs have demonstrated their prowess in tackling a wide range of NLP challenges, their demanding computational requirements can render them impractical for real-time online inference. In response to this limitation, we suggest the concept of text distillation, a technique aimed at effectively transferring the knowledge stored within LLMs to more compact and computationally efficient neural networks.
Feasibility of a Voice-only Chatbot with Anthropomorphic Features Compared to a Text-based Chatbot as a Responder to Questions on Mental Health: a Randomized, Controlled Trial among Healthy Participants (Preprint)

<sec> <title>BACKGROUND</title> The use of chatbots in mental health support has increased exponentially in recent years, with studies showing that they may be effective in treating mental health problems. More recently, the use of voice-controlled visual avatars called digital humans has been introduced, which use machine learning and mimicry of facial emotions to build emotional engagement with users. It is important to study the difference in emotional response and usability preferences between text-based chatbots and digital humans for interacting with mental health services. </sec> <sec> <title>OBJECTIVE</title> The aim of this study was to explore to what extent a voice-only and a text-only chatbot interface differed on usability when tested by healthy participants, using BETSY (Behavior, Emotion, Therapy System, and You) which employs two distinct interfaces: a voice-only user interface with anthropomorphic features and a text-only user interface. We also set out to explore how chatbot-generated conversations on mental health (specific to each interface) affected self-reported feelings and biometrics. </sec> <sec> <title>METHODS</title> We explored to what extent a voice-only chatbot with anthropomorphic features differed from a traditional text-only chatbot regarding perception of usability though the System Usability Scale (SUS-10), emotional reactions though electroencephalography, and feeling of closeness. Healthy participants (n=45) were randomized to two groups that used a voice-only chatbot with anthropomorphic features (n=25) or a text-only chatbot with no such features (n=20). The groups were compared by linear regression analysis and t-tests. </sec> <sec> <title>RESULTS</title> No differences were observed between the text-only and voice-only group regarding demographic features. Mean (SD) SUS-10 score was 75.34 (10.01) [range, 57-90] for text-only chatbot versus 64.80 (14.14) (range, 40-90) for the voice-only chatbot. Both groups scored their respective chatbot interfaces as average or above average in usability. Women were more likely to report feeling annoyed by BETSY. </sec> <sec> <title>CONCLUSIONS</title> The text-only chatbot was perceived as significantly more user-friendly than the voice-only chatbot, although there were no significant differences in EEG measurements. Male participants exhibited lower levels of annoyance with both interfaces contrary to previously reported findings. </sec>
Understanding the Patterns of Hate Incidents and Reporting Attitudes at a UK University

Widening participation, through diversity and inclusion, has become a major goal to achieve in UK Higher Education, with the potential of the most able, rather than simply the socially advantaged, attending university. Addressing challenges of racism and religiously motivated hate incidents in universities is important if we are to provide an educational environment in which all can feel safe to learn. The current study is a survey investigation and one of the very largest of its kind in the UK. The focus is on the extent of hate crime incidents and patterns of reporting the incidents by students and staff at a university in the North East of England. All staff and students were invited to take part in the anonymous survey, generating a sample of 2,265 respondents. Of those who responded, 27% indicated that they had experienced a hate incident, and only 20% of those who had experienced an incident also reported it. The survey results, counterintuitively, and for some no doubt controversially, showed relatively small differences in the patterns of experiencing hate incidents motivated by race or religion across different subgroups in the sample. Students and staff with disabilities were the group most likely to report experiencing hate crime, both within and outside the university. The findings have research and policy implications. There is a need for establishing clear institutional policies on reporting pathways and procedures, maintaining an effective system for information, help, support, and advice.
A decision support system for verifying the quality of application software code

The proposed architecture of the decision support system for quality control of software code of applied codebases. The proposed approach is modular and applicable to most software development projects. The proposed system allows deriving empirical rules for long-term software development and maintenance.
An algorithm for soil identification according to the World Reference Base for Soil Resources

This paper addresses soil identification according to the World Reference Base for Soil Resources. A structure of the database of soil parameters of diagnostic horizons is proposed. Three variants of allocating soils to Reference Soil Groups based only on soil parameters, or on the combination of diagnostic horizons and soil parameters, or only on diagnostic horizons are considered
Stefan Odobleja, cybernetics and artificial thinking/Artificial Intelligence

The article demonstrates that the Romanian scientist Stefan Odobleja (1902-1978), in his work "Consonantist Psychology" elaborated the principles and laws that are the basis of artificial thinking. The fascination with artificial intelligence began last century, when humanity was very far from the technologies without which we cannot imagine life today. Artificial intelligence refers to the phenomenon where a machine acts like a human mind. The history of artificial intelligence can include the scientist Stefan Odobleja, as the father of artificial thinking, described in his work, which is actually a generalized cybernetics.
Contradiction Epistemology in the Context of the Law of Unity and Struggle of Opposites

The problem of divergence of dialectical materialism from the materialist worldview, which causes the necessi-ty of epistemological and ontological comprehension of the known laws of dialectics, is considered. Since the law of transition of quantitative changes into qualitative ones and the law of negation of negation have been considered by the author in previous works, the subject of the study becomes the law of unity and struggle of opposites. The unity and contradictions of the object of cognition are placed in the focus of the research. The unity of the object of cognition is qualified within the framework of the system approach as its integrity, in turn defined through stability and localization. Consideration of contradictions of the object of cognition revealed their division into real and imaginary. Real contradictions are associated with the processes of creation and destruction, underlying the existence of all objects in the world. Imaginary contradictions arise in the process of cognition and include contradictions of unreliability of knowledge, methodological contradictions and termino-logical contradictions. Among the imaginary contradictions also includes the contradiction of identity and differ-ence of the object of cognition.
A Comprehensive Review of Advancements in Communication-Efficient Distributed Optimization

Abstract: In the ever-evolving landscape of machine learning and deep neural networks, the demand for training large models on massive datasets has driven research into innovative approaches for efficient distributed optimization. These approaches aim to simultaneously improve model accuracy and generalization while mitigating the communication overhead challenges inherent to distributed training. Reduced communication complexity is highly desirable, as communication overhead often poses a performance bottleneck in distributed systems. This literature review explores the progression of communication-efficient techniques, culminating in the introduction of the Slow Momentum (SLOWMO) framework. It traces the trajectory of distributed optimization, addresses decentralization strategies, and highlights the role of Local Stochastic Gradient Descent (Local SGD) and momentum in communication-efficient algorithms. It delves into Block-Wise Model Update Filtering (BMUF) and introduces SLOWMO, a framework consistently enhancing optimization and generalization performance across various base algorithms. This review unveils the evolving field of communication-efficient distributed optimization, offering theoretical guarantees and practical insights for improving large-scale model training.
Student-centered educational process and protection of children's rights

Student-centered learning is a philosophy or approach to education designed to meet the individual needs of each student. In a truly student-centered learning environment, teachers and students work together to create a curriculum or pathway that best suits the needs of each individual student. In a learner-centered learning environment, the teacher strives to create an environment that is individualized to each student's learning needs. The teacher acts as the architect of each student's learning experience. The article discusses the connection of the student-centered approach with children's rights and what kind of historical context it has.
Introduction to Mixture Models

In Chap. 1, we introduce the fundamental concept of a statistical model and provide a detailed definition of both mixture models and finite mixture models. We uncover the latent structure inherent in mixture models, address the issue of identifiability, and explore various commonly utilized mixture models. Additionally, we highlight the relationship between mixture models and the models applied in the context of over-dispersed populations.
OPTICAL CHARACTER RECOGNITION MENGGUNAKAN UIPATH DAN PENCOCOKAN DATA SERTIFIKAT DENGAN ALGORITMA LEVENSHTEIN DISTANCE

The collection of the certificates was one of the requirements for graduating from Tarumanagara University that the certificate became an important point of attention to improving the competency of Tarumanagara University students. Certificates can be collected from seminars, workshops, courses, and so forth. The Certificate Information Extraction design were created using Uipath Studio application that uses vb.Net programming language and Levenshtein Distance Algorithm. The design aims to assist the study program in validation on student certificates file by obtaining better accuracy using the Levenshtein Distance Algorithm.. The design uses input data as student certificates that’s next to be processed by text preprocessing consisting of text deductions (parsing), case folding, lexical analysis (tokenizing), and text removal (stopword removal). After processing, the Levenshtein Distance Algorithm will be used to calculate the minimum distance between one text and the other with a two-dimensional matrix operation, thus determining the validity of student certificates. The results of this design represent that using the Levenshtein Distance Algorithm, obtaining the best word accuracy result of 83.52% and RPA running time of 94.7 ms.
LECTURERS' PERCEPTION ON THE USE OF WHATSAPP IN TEACHING AND LEARNING ACTIVITIES DURING COVID-19

The covid-19 has an impact on the educational field. The learning process has changed from conventional to online learning. Several applications are offered to help educators in doing online learning. One of them is Whatsapp application. Whatsapp is one of the information media that is widely used by many people, including teachers, lecturers, and students. In subsequent developments, Whatsapp application is not only used to communicate and exchange messages, but Whatsapp is also used for educational purposes. The researcher conducted the study of using Whatsapp in teaching and learning activities during Covid-19 at English Education Study Program Jambi University by implemented a qualitative approach with a case study design in gaining the data. Interviews with four English Lecturers were used to obtain data and evidence about how do they perceive the use of Whatsapp in the teaching and learning process during covid-19. The results of data analysis revealed that all of the lecturers have many positive perceptions rather than the negative one about using Whatsapp to do online learning during covid-19. Using Whatsapp in online learning during covid-19 is easy because lecturers can monitor learning at any time, it does not consume a lot of quotas, and many features available on Whatsapp make it easier for lecturers to take the usefulness of these features to carry out online learning activities such as discussion, sharing learning material in various formats, giving assignments, collecting assignments, giving review or feedback and for academic planning and scheduling.