Reviewerly/exHarmony huggingface dataset:
REFLECTIVE PORTFOLIO IN PROFESIONAL TRAINIGH OF FUTURE SPECIALITS

The authors make actual the possibilities of a reflexive portfolio use in future specialists’ professional training. A reflexive portfolio provides an assessment and self-assessment of achieving goals, features of the course and quality of work with various sources of information, feelings, reflections, impressions and it also reflects both a problem of a study topic and a working process on it. An algorithm for creating a reflective portfolio is considered, which consists of three stages. The preparatory stage provides modelling of the structure and content of a reflexive portfolio. The search and analytical stage includes the systematization of materials reflecting the analysis, evaluation of the process and results of activities. At the final stage, there is a reflection of one’s own reflective activity and the presentation of a reflective portfolio. The article suggests the structure of a reflective portfolio: sections «My expectations», «A step to success», «Defect-effect», «I am a creator». In the process of the creation and presentation of a reflective portfolio, training exercises «The goal of studying», «The chart of my goals», «A suitcase», «The diary of double notes», «Gifts», which develop situational, retrospective and prospective reflection in students. Based on the results of the analysis of the results of the implementation of a reflexive portfolio, it was revealed that this work contributes to the development of reflective skills, the determination of the possibilities of one’s own activity, the choice of optimal options for achieving the intended goals, and the forecasting of the results of one’s activity.
Half-face based recognition using principal component analysis

&lt;span lang="EN-US"&gt;Face recognition is a considerable problem in the field of image processing. It is used daily in various applications from personal cameras to forensic investigations. Most of the provides solutions proposed based on full-face images, are slow to compute and need more storage. In this paper, we propose an effective way to reduce the features and size of the database in the face recognition method and thus we get an increase in the speed of discrimination by using half of the face. Taking advantage of face symmetry, the first step is to divide the face image into two halves, then the left half is processed using the principal component analysis (PCA) algorithm, and the results are compared by using Euclidian distance to distinguish the person. The system was trained and tested on ORL database. It was found that the accuracy of the system reached up to 96%, and the database was minimized by 46% and the running time was decreased from 120 msec to 70 msec with a 41.6% reduction.&lt;/span&gt;
DEFINITION OF APPLICATION FIELD OF THE STAND FOR THE VIDEO MONITORING SYSTEMS INVESTIGATION

The paper presents the results of determining the areas of application of a laboratory stand designed for studying and researching CCTV systems. The necessity of research of video cameras of the security alarm system, their testing at the organization of production and expediency of carrying out laboratory works by students of higher education institutions studying security systems is shown. The state of affairs in this area in post-Soviet countries is shown. Some requirements of the State educational standard on informativeness and expansion of opportunities of laboratory stands are given. The input parameters necessary for the design of video camera research stands are considered. The results of the study of the developed laboratory stand for the study and study of security television systems and the definition of areas for its application are presented. The structure of the stand and its parts is proposed. Developed recommendations for its use are given. The experience of conducting laboratory work on the study of the characteristics of security alarm cameras is analyzed. The possibility of studying robust filtering on the noise immunity of the video system, the influence of the illumination spectrum on the main qualitative characteristics of the video camera using the proposed stand is shown. A list of suggested to run the stand includes laboratory work “Studying the parameters, operation modes and configuration of video surveillance system NOVUS”, “the Study of possibilities of various types of cameras when changing the light and characterization of the sensitivity of various types of cameras, Definition of focal length, angle of view and resolution of different types of cameras and lenses, Definition of the working area of observation, the far and the dead zone for various types of cameras and lenses”, "Determination of conditionally dead zones for different recording speeds of the DVR and at different focal lengths” and" Determination of the volume and quality of recorded information from the value of the recording speed of the DVR”, as well as research works “The signal processing with variable spectrum”, “the Influence of robust filtering for noise immunity video”, “Influence of illumination spectrum on the main qualitative characteristics of the camera” and “Comparative performance of analog and digital cameras.”
IMPLEMENTATION TELEGRAM CHAT BOT ON STUDENT ORIENTATION PERIOD REGISTRATION SYSTEM FOR EFFICIENCY OF DATA MANAGEMENT

Orientation is a routine activity carried out by both public and private tertiary institutions. Universitas Muhammadiyah Surakarta (UMS) which is a private higher education institution also has several types of orientation, one of which is thePeriod of Ta'aruf the Muhammadiyah Student Association (MASTA IMM). IMM. IMM MASTA implementation that has occurred so far in the data processing process is still done manually, so there is often the same data and the time to manage the data is less effective and efficient. This study aims to design a MASTA IMM registration system using Telegram bot to simplify and streamline time in data management and class division. The method used in this research is themethod Waterfall modified, where the repair process is carried out only after the testing and evaluation stages. The development of this system will use the Telegram Bot API and theprogramming Pythonlanguage by utilizing library the provided. This system has several functions, including registration, adding and deleting data, dividing classes, and printing data intodocuments excel. This system has also been tested with good results. The test method used is the blackbox to find out the functionality of the system running properly. As well as testing the System Usability Scale (SUS) to evaluate the usefulness of the system with a final average result of 76.33, which means that the user agrees with the system that has been designed. This system is able to provide convenience during student registration and make it easier for admin in data management.
Designing Website-Based E-Learning Application on SMP Kusuma Bangsa Using Framework Codeigniter

The Covid-19 pandemic currently occurring around the world, including Indonesia has had an impact and changes in various areas of daily life. Especially, in the field of education which during the Covid-19 pandemic must make efforts to adapt. Minimizing direct interactions is an important first step to avoiding the spread of covid-19. This is also applied to teaching and learning activities between teachers and students therefore teaching and learning activities are carried out online. Without any doubt, this change creates problems and difficulties in the delivery of material, interactions between teachers and students, etc. However, SMP Kusuma Bangsa is a private school that still implements face-to-face learning system. To solve this problem, the author propose making an online learning system. In order to achieve this, the author intend to create an e-learning application. This e-learning application is based on website created using the Codeigniter framework. To find out the application requirements desired by the user, the author make user needs which will be used as a form of analysis in making e-learning application. After getting the results of user needs, the author complete the e-learning application with 3 user models, admin, teacher, and students, each of them has their own function. Likert scale is used to measure the level of user satisfaction of the e-learning application. Based on the results of the calculation, it can be seen that users as respondents who strongly agree with the statement that the e-learning application are in the good category, it shows the acquisition of 84.1%. Therefore, the e-learning application has helped minimize direct interaction, the application operates well, and the presence of an online exam feature, a conference system using the zoom application, etc make teaching and learning activities at SMP Kusuma Bangsa easier
Benchmarking a transformer-FREE model for ad-hoc retrieval

Transformer-based "behemoths" have grown in popularity, as well as structurally, shattering multiple NLP benchmarks along the way.However, their real-world usability remains a question.In this work, we empirically assess the feasibility of applying transformer-based models in real-world ad-hoc retrieval applications by comparison to a "greener and more sustainable" alternative, comprising only 620 trainable parameters.We present an analysis of their efficacy and efficiency and show that considering limited computational resources, the lighter model running on the CPU achieves a 3 to 20 times speedup in training and 7 to 47 times in inference while maintaining a comparable retrieval performance.
A Robotics Engineering Specialized Education Trajectory as Part of an Industrial Management System

The training of specialists that meets the individual requirements of a specific production is one of the actual problems of industrial management. This paper proposes a modular structure for training engineering and technical personnel, which allows solving this problem in the main areas of robotics. Based on the analysis of educating students, it was concluded that it is necessary to modernize curricula due to the lack of high academic mobility. The developed specialized trajectory will ensure the training of highly qualified specialists in the field of robotics, which best meets the requirements of the electrical and electronic industry.
An Improve Framework for hate speech detection using Machine Learning Approach

Hate Speech is any correspondence that decries an individual or a gathering based on some trademark, for example, race, identity, sex, sexual direction, ethnicity, religion, or other trademark.Harmful language (e.g., scorn discourse, damaging discourse, or other hostile discourse) principally targets individuals from minority gatherings and can catalyze genuine savagery towards them.The paper proposes an improve framework for hate speech detection using machine learning approach.This system uses a twitter dataset that contains tweeted messages of both hate speech, offensive language, and also messages that is neither hate speech nor offensive language.The dataset was downloaded from kaggle.com, the dataset contains a total of 24,784 twitted messages.The dataset is made up of 8 columns which we later reduced it to two columns by means of feature_extraction.The reduced columns are the tweet columns which contain the twitted messages and the class columns which contains 0,1 and 2, where 0 is classified as hate speech, 1 is classified as offensive language and 2 is classified as neither hate speech or offensive language.we trained our model using support vector machine and random forest classifier and had an accuracy of 95% and 99%.We then deployed our model to web using python flask for easy evaluation and testing.Our experimental results show that our proposed system had better performance in terms of classifying text as hate speech.
THE INTERPLAY BETWEEN LEARNING MEDIA, MOTIVATION AND LEARNING OUTCOMES: INSIGHTS FROM INDONESIAN EFL CONTEXT

&lt;p&gt;The objectives of the study are to explore the impact of English comic learning media towards English’s learning outcomes, the impact of learning motivation towards English’s learning outcomes, and the interaction effect between English comic learning media and learning motivation towards English’s learning outcomes. The method of research is experimental with 2x2 factorial design. Data collection techniques are multiple choice and questionnaires. Population of the study are 175 students. Sample of the study are 60 students. Random sampling are used for gaining sample. The researcher used SPSS 22.0 version to analyze data. The conclusions of this study are: (1) There is a significant impact of English comic learning media towards English’s learning outcomes because significant value is 0.000 &amp;lt; 0.05.(2) There is a significant impact of learning motivation towards English’s learning outcomes because significant value is 0.000 &amp;lt; 0.05. (3) There is a significant interaction impact between English comic learning media and learning motivation towards English’s learning outcomes because significant value is 0.004 &amp;lt; 0.05. &lt;/p&gt;
Hybrid LRU Algorithm for Enterprise Data Hub using Serverless Architecture

In hybrid LRU algorithm was built to execute parameterized priority queue using Least Recently Used model. It helped to determine the object in an optimum mode to remove from cache. Experiment results demonstrated ~30% decrease of the execution time to extract data from cache store during object cache extraction process. In the era of modern utility computing theory, Serverless architecture is the cloud platform concept to hide the server usage from the development community and runs the code on-demand basis. This paper provides Hybrid LRU algorithm by leveraging Serverless Architecture benefits. Eventually, this new technique added few advantages like infrastructure instance scalability, no server management, reduced cost on efficient usage, etc. This paper depicts about the experimental advantage of Hybrid LRU execution time optimization using Serverless architecture.
A Survey on Human Detection using Reinforcement Learning

Human Detection - technology related to computer vision and image processing work by finding people in digital photos and videos and surveillance videos that are part of the observation. Single Shot Detector (SSD) is a deep learning method and is one of the fastest algorithms that use a single convolutional neural network to detect objects involving humans, cats, dogs, etc., and extract feature maps to classify the candidate object in the respective images. The advantage that SSD has is that it is quick to detect and has high accuracy in a given situation compared to regional suggested networks with smaller resolution images and smaller objects. However, it is still somewhat lagging in detecting large objects in larger images as compared to other algorithms that have been used to achieve better accuracy. It is a simple, end-to-end solution for a single network, and detection and extraction are done with one step forward single pass. The proposed system is to use the Optimized-SSD algorithm to detect human accuracy in the proposed database with good accuracy which will be the task of learning to increase SSD capacity as a detection system.
Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models

In this work, we explore joint energy-based model (EBM) training during the finetuning of pretrained text encoders (e.g., Roberta) for natural language understanding (NLU) tasks.Our experiments show that EBM training can help the model reach a better calibration that is competitive to strong baselines, with little or no loss in accuracy.We discuss three variants of energy functions (namely scalar, hidden, and sharp-hidden) that can be defined on top of a text encoder, and compare them in experiments.Due to the discreteness of text data, we adopt noise contrastive estimation (NCE) to train the energy-based model.To make NCE training more effective, we train an autoregressive noise model with the masked language model (MLM) objective.
Contextualisation of the Current Knowledge and Technology Transfer-Related Literature: The Text Analysis

The importance and relevancy of technology and knowledge transfer has been growing together with the interest and attractiveness for the organisations and institutions from both public and private sector.As a result, various literature focus on different aspects of this topic.Therefore, this paper focuses on the analysis of the current knowledge and technology transfer-related literature.It aims to identify the most mentioned keywords and topics to understand and contextualise the research field.The research methodology is based on the text analyses using the open access KH coder software.The correspondence analysis, co-occurrence network analysis, hierarchical cluster analysis and Self-Organising Map are used to reveal the results and the main topics of the discussed area.Crucial keywords strategy, policy and mission are identified.Furthermore, the technology and knowledge transfer are closely related to the learning and networking processes.The outputs also imply the three main word clusters including the academic environment, the organisational processes and projects supported by the software, and the information and knowledge management.Obviously, the discussed issues might provide the topical framework for reaching excellency as well as long-term competitive advantage.
PROCEDURAL COMPONENT OF READYNESS OF FUTURE TEACHERS OF MUSIC ART FOR CULTURAL AND EDUCATIONAL WORK IN EXTRACURRICULAR INSTITUTIONS

The article, based on the analysis of theoretical literature, characterizes the procedural component of the readiness of future music teachers for cultural and educational work in out-of-school education institutions. It was found that the procedural component of the readiness of future music teachers for cultural and educational work in out-of-school education reflects the system of professional performing, artistic and creative skills that students need to carry out effective professional activities, as well as the ability to organize and implement future professional activity of cultural and educational work in the cultural and educational environment of the out-of-school education institution.&#x0D; This system contains the following skills and abilities: didactic-methodical, organizational-managerial, musical-performing, research-design and information-educational.
Lifelong Language Learning With the Most Forgotten Knowledge

Lifelong language learning enables a language model to accumulate knowledge through training on a stream of text data. Recent research on lifelong language learning is based on samples of previous tasks from an episodic memory or generative model. LAMOL, a representative generative model-based lifelong language learning model, preserves the previous information with the generated pseudo-old samples, which are suboptimal. In this paper, we propose an improved version of LAMOL, MFK-LAMOL, which constructs a generative replay using a more effective method. When a new task is received, MFK-LAMOL replays sufficient previous data and retrieves important examples for training alongside the new task. Specifically, it selects the examples with the most forgotten knowledge learned from previous tasks based on the extent to which they include knowledge that has been forgotten after learning new information. We showed that the proposed method outperforms LAMOL on a stream of three different natural language processing tasks.
Malicious Web Page Detection and Content Analysis

The detection of malicious web pages is a complex engineering problem due to the dynamic nature of the information contained on the internet.Since the data stored on web-servers updates on a continuous basis, It is very hard to find and classify which links are malicious and which are not in real-time.Hence, brute-force checks (system-scans) and voting-based approaches (blacklisting) fail to capture the exhaustive list of malicious content on the internet.A machine learning based model is proposed which is able to classify the malicious links and content on the user's device.It can later be applied in the forms: a web application, Android, iOS mobile applications and also browser extension which is able to give you a report of that link which you want to open on a device.The whole system performs a complete scan on that link and generates a report.
A Novel Approach for Detection of Moving Objects in Complex Scenes Using Fuzzy Colour Difference Histogram

Background subtraction schematic is widely used for motion detection. For effective automation of this process, a robust algorithm with high accuracy is needed. One of the major challenges of such algorithms is the identification of objects from an environment with composite elements that may be a dynamic background, frames with a camouflaged background and foreground pixels, and consecutive frames with varying illumination. The existing system uses a multi-color space histogram superposition principle having the biggest challenge of choosing appropriate color components in suitable proportion. Overcoming this challenge, a novel approach, MODITBS, processed in a differential domain, is proposed. A fuzzified color difference histogram-based background modeling is done to significantly deal with complex background scenes followed by principal component analysis-based feature extraction. The foreground objects detected are enhanced using a Kalman filter. The results show that MODITBS attains an accuracy of 95.16% in comparison to the existing system having an accuracy of 91.25%.
TYPES OF SPEAKING ACTIVITIES IN “BUKU BAHASA INGGRIS” FOR TOURISM VOCATIONAL HIGH SCHOOL

The use of textbooks as a media in teaching learning processes especially in English Language Teaching cannot be denied. That’s why this present study is intended to investigate types of speaking activities presented in buku Bahasa Inggris for Tourism Vocational High School. The content of an English text book was described and analyzed by using a descriptive qualitative method. Buku Bahasa Inggris kelas X had been chosen as the source of data. The collected data were analyzed through some steps such as (1) classifying the data into types of speaking activities (Acting from Script, Communication Games, Discussions, Paper Talk, Questionnaires, Simulation and Role Play) and (2) identifying the dominant type of speaking activities. The result indicates buku Bahasa Inggris Kelas X contains six types of speaking activities and it is dominated by speaking activity of prepared talk
Organizational confidence and its role in improving the performance of staff Field research for a sample of Samaraa University and the Samaraat University staff

The research is to learn about organizational confidence and its role in improving the performance of staff and to achieve this goal, the researchers have found through the research hypothesis and its change of organizational confidence in its dimensions (confidence in senior management, confidence in the direct president, trust with co-workers). The second change is to improve the performance of staff, where the research sample consisted of 50 staff members at the university and college levels. The most important results were the lack of delegation of authority, participation in decision-making and insufficient attention to work requirements The experience of the management of the system is that the system is not only a function of the system, but also a function of the system. The 2-way