Reviewerly/exHarmony huggingface dataset:
An Efficient Stacked Deep Incremental Model for Online Streaming Video QoE Prediction

The Quality of Experience (QoE) metric is used as a direct evaluation of customers' experiences in video streaming diffusion, which is very important for network management, especially for the optimization and the improvement of the network.Hence, it is important to continuously quantify the perceived QoE of streaming video clients to minimize the QoE degradation.Nevertheless, the continuous evaluation of the perceived quality is challenging since it is defined by complex dynamic interactions between the QoE influencing factors.Thus, in this work, a new Deep Incremental Support Vector Machine (ISVM) QoE assessment model is developed that integrates deep learning techniques and a multiclass ISVM.The deep learning layer is employed to extract deep features which have discriminative power and lead to performance improvement.ISVM algorithm aims to manage non-stationary and massive amounts of data in real-time scenarios.Experiments are carried out on a real-world public datasets.The results demonstrate that our approach outperforms state-of-the-art approaches for evaluating QoE.
SCREENCAST AND ITS EFFECT ON IMPROVING LEARNERS’ ACADEMIC ACHIEVEMENT AND MOTIVATION IN PHYSICS

Screencasts are multimedia-based learning which involves multimodal sensory, such as eyes and ears. These are increasingly used as schools transition to blended learning mode. This study aims to describe the screencast and its effect on improving learners’ academic achievement and motivation in Physics. This quasi-experimental research determined learners’ academic achievement and level of motivation before and after treatment to screencasts focusing on heat, temperature, and electricity. The study was done in a large public secondary school in a highly urbanized city in the central Philippines. Academic achievement was measured through a constructed test while the level of motivation was evaluated using Keller’s Instructional Materials Motivation Survey. Results showed that screencasts improved the learners’ academic achievement and increased their level of motivation. The use of screencast has a good impact on changing learners' knowledge and skills and is an effective online learning media. Findings also obtained a p-value of 0.00 which showed that there is a significant difference in the learner’s academic achievement before and after treatment to screencast. This study discovered that learning using screencasts is engaging to the learners. The screencast provided the learners with the opportunity to learn at their pace and brought them better learning experiences.
Description of Image encryption Using AES-256 bits

Abstract: Image Encryption using AES Algorithm is a technique to secure the confidentiality of images. One of the most popular and secure encryption algorithms is the AES (Advanced Encryption Standard) algorithm. It is a symmetric encryption algorithm that encrypts data using a 128-bit block cipher. In this process, the image is first converted into a binary format. Then, a random 128-bit key is generated, which is used to create a sequence of subkeys that will be used for each round of encryption. The binary image is then divided into 128-bit blocks, and the encryption algorithm is applied to each block using the subkeys generated earlier. This process ensures that the image is encrypted securely and is only accessible to those who have the key to decrypt it. One of the advantages of using AES is that it provides a high level of security, making it difficult for hackers to decrypt the encrypted data. Additionally, AES is a fast algorithm and can be implemented easily in hardware or software. The use of AES for image encryption ensures that the image is protected against unauthorized access and provides a secure way of transmitting sensitive images over the internet. Thus we can say that Image Encryption using AES Algorithm is a secure and efficient way to protect the confidentiality of images. It uses AES, a widely used encryption algorithm, to encrypt images securely, making it difficult for hackers to decrypt them without the key.
Development of Powtoon Learning Media for Student Learning Activities in Theme 2 Clean Air For Health Class V SDN 064954 Medan Amplas

This study aims to: (1) develop Powtoon learning media for student learning activities on theme 2 clean air for health for grade V SD, (2) determine the feasibility of developing the Powtoon application in SD thematic learning. This research is a type of Research and Development (RD) research with the ADDIE model which includes five steps including: analysis, design, development, implementation, evaluation. The subjects in this study were media expert validators, education practitioners, material experts, namely fifth grade teachers and fifth grade elementary school students. The research instruments used in data collection were questionnaires, observation, and documentation. The results of this study indicate that Powtoon learning media in Thematic Learning Theme 2 Clean Air for Health Class V SD "Very Eligible" with details of the eligibility percentage given by Media Experts in sub-theme 1 of 71.6% in the "Decent" category, media sub-theme 2 86.6% in the "Very Eligible" category, 88.3% in subtheme 3 media in the "Very Eligible" category. Material experts on media sub-theme 1 are 76% in the category "Appropriate", sub-theme 2 are 88% in the "Very Eligible" category, sub-theme 3 is 90% in the "Very Eligible" category. In Education Practitioners, the media subtheme 1 is 90% with the category "Very Eligible", subtheme 2 is 90% with the category "Very Eligible", subtheme 3 is 90% with the category "Very Eligible", Individual Trials are 90.8% with category "Very Feasible" and Student Learning Activities by 80% with the category "Very Feasible". Therefore it can be concluded that the Powtoon learning media for student learning activities on theme 2 clean air for the health of class V SDN 064954 Medan Amplas is "very appropriate" to be used with students during the learning process.
Secure Cybersecurity Information Sharing for Sectoral Organizations Using Ethereum Blockchain and IPFS

The COVID-19 pandemic has resulted in increased cross-sector cyber-attacks. Passive and reactive cybersecurity techniques relying solely on technology are insufficient to combat sophisticated attacks, necessitating proactive and collaborative security measures to minimize attacks. Cybersecurity Information Sharing (CIS) enhances security via proactive and collaborative cybersecurity information exchange, but its implementation via cloud services faces threats from man in the middle (MITM) and distributed denial of service (DDoS) attacks, as well as a vulnerability in cloud storage involving centralized data control. These threats and vulnerabilities result in a lack of user confidence in the confidentiality, integrity, and availability of information. This paper proposes Secure Cybersecurity Information Sharing (SCIS) to secure Cybersecurity Information in sectoral organizations using the private interplanetary file system (IPFS) network and the private Ethereum Blockchain network. Private Ethereum Blockchain enables secure and transparent transaction logging, while Private IPFS network provides decentralized storage, addressing vulnerabilities in centralized storage systems. The outcomes of the tests reveal that the suggested SCIS system offers cybersecurity information availability, confidentiality, and integrity. SCIS provides a high level of security to protect cybersecurity information exchanged between sectoral organizations using the Private Ethereum Blockchain network and the Private IPFS network so that organizations can safely share and utilize information.&#x0D;
Analysis of User Readiness Using the TRI Model for Smart School Implementation in the City of Pekanbaru

Currently, Smart Schools have been widely applied in several schools, within the scope of education and services as they are being encouraged to support Smart City. Smart Schools is a school concept utilizing information technology used in the teaching and learning process in the class and school administration. One of the schools in Pekanbaru City that will implement smart schools is Junior High School 17 Pekanbaru. The aspect of building smart schools themselves is not only adequate infrastructure such as servers, labor, and integrated systems but also the readiness on the part of schools and students in implementing Smart Schools in the future. Therefore, to find out the level of readiness of prospective users of the Smart Schools concept, the technology readiness index (TRI) method with four personality variables; optimism, innovativeness, discomfort, and insecurity was used. The purpose of this research was to find out the readiness index of prospective users in the implementation of Smart Schools and see what factors need to be improved from the readiness of prospective users. The results show that teachers and students are ready to apply new technologies in an effort to implement smart schools at Junior High School 17 Pekanbaru. This can be seen from the results obtained, namely the optimism and innovation variables received medium to high ratings. for the discomfort and insecurity to be completely low. However, the student guardians are still unsure because all variables get medium scores. From these results it was stated that Junior High School 17 Pekanbaru was ready to apply new technology for implementing smart schools. In addition, this research can also serve as a guideline for other junior high schools in analyzing new technology users, so that the applied technology can run well.&#x0D;
PENERAPAN MODEL KOOPERATIF LEARNING TIPE NHT (NUMBER HEAD TOGETHER) BERBANTUAN MEDIA VIDEO PEMBELAJARAN UNTUK MENINGKATKAN HASIL BELAJAR PESERTA DIDIK KELAS II SEKOLAH DASAR

This research is motivated by the results of observations which show that the learning outcomes of students are still low. To respond to this, the researchers conducted Classroom Action Research (PTK) entitled the application of the NHT (Number Head Together) cooperative learning model assisted by instructional video media to improve learning outcomes for class II elementary school students. The objectives to be achieved in this study include: to find out the implementation of the NHT type cooperative learning model assisted by learning video media, to determine the increase in student learning outcomes after being given the NHT type cooperative learning model assisted by learning video media. This research is a class action research with the Kemmis and Mc Taggart. This research was conducted in class II SDN 013 Pasirkaliki with 26 students. This study measures the cognitive learning outcomes of students. The collected data were analyzed using descriptive statistical analysis and the research results from each cycle there was an increase, cycle I obtained a percentage of 64.76% in cycle II increased to 78.57%. it can be concluded that the application of the cooperative learning model of the NHT type assisted by learning video media can improve student learning outcomes.&#x0D; Keywords: Classroom Action Research, Cooperative Learning, learning outcomes.
Analysis of Supermarket Product Purchase Transactions With the Association Data Mining Method

The development of business world is entering the era of big data. In meeting supermarkets' sales and purchase targets, the management needs to improve themselves in managing the goods available in the store. The research aims to determine the pattern of purchases that occur in a transaction, find out related and related products in supermarkets, and improve supermarket services to customers. The method applied uses the association rules approach to data mining. Several purchasing data from customers have been able to be analyzed by displaying a diagram as a visualization of the number of specified association rules. The processing results show a relationship above 90%: sugar and coffee with a confidence of 94.4%, shirts and trousers with a confidence of 93.4%, and sugar, milk, and coffee with a confidence of 92.0%. Decisions that can be taken by supermarket management in providing places and goods need to consider and follow product relationships and proximity based on the highest confidence value to provide services to customers effectively and efficiently.
The Effect of the Cooperative Model With the Assistance of LKS on Class III Students' Learning at SDN Bumianyar II

Learning in general is a process of interaction between educators, students and their environment. Learning is a series of complex activities, in essence not only conveying subject matter but also requires the teacher to use all the basic skills in teaching. This study aims to examine: 1) significant differences in learning outcomes using the cooperative model with the help of LKS and conventional learning; 2) student activities in learning by using cooperative models with the help of worksheets. This type of research is experimental research. This experimental research design uses a control group pre-test-post-test design pattern. Data collection techniques using observation, interviews, documentation and tests. The data analysis technique uses the t-test statistical test formula and the percentage of student activity. The results of this study showed that there was a significant difference between learning outcomes using the Cooperative Model with LKS Assistance and conventional learning, as well as the percentage value of student activity while participating in learning using the Cooperative Model with classical LKS Assistance of 78.43% included in the active criteria. The conclusion of this study is that there is a significant difference between learning outcomes using the Cooperative Model with the help of LKS and conventional learning in Class III students of SDN Bumianyar II Academic Year 2020/2021 and the learning activities of class III students of SDN Bumianyar II Academic Year 2020/2021 while participating in learning using The Cooperative Model with the Help of LKS is included in the active category.
Ontology-based Conversational Recommender System for Recommending Camera

The camera is a product that has developed very quickly in terms of specifications and functions. In addition, the cameras available on the market are becoming increasingly varied, so customers need more time to find a camera that suits their needs. Currently, many recommender systems have been developed to assist users in finding suitable products, especially the conversational recommender system (CRS). CRS is a recommender system that recommends products through conversations between the user and the system. However, many developed CRS still forces users to have knowledge of the product's technical characteristics. In the real world, many people are not familiar with the technical features of products, especially cameras. People interact more easily with CRS by stating the camera function they want. In this study, we call that statement functional requirements. Therefore, we proposed a CRS for recommending cameras that interact with users using functional requirements. This CRS uses semantic reasoning techniques on ontologies. To evaluate system performance, we use two parameters, i.e., user satisfaction and recommendation accuracy. The evaluation results show that the accuracy of the recommendations is at a value of 82.35%, and the level of user satisfaction reaches 0.66. With these results, the system can provide recommendations accurately and satisfy users.&#x0D;
Robust T-Loss for Medical Image Segmentation

This paper presents a new robust loss function, the T-Loss, for medical image segmentation. The proposed loss is based on the negative log-likelihood of the Student-t distribution and can effectively handle outliers in the data by controlling its sensitivity with a single parameter. This parameter is updated during the backpropagation process, eliminating the need for additional computation or prior information about the level and spread of noisy labels. Our experiments show that the T-Loss outperforms traditional loss functions in terms of dice scores on two public medical datasets for skin lesion and lung segmentation. We also demonstrate the ability of T-Loss to handle different types of simulated label noise, resembling human error. Our results provide strong evidence that the T-Loss is a promising alternative for medical image segmentation where high levels of noise or outliers in the dataset are a typical phenomenon in practice. The project website can be found at https://robust-tloss.github.io
Adversarial learning of neural user simulators for dialogue policy optimisation

Reinforcement learning based dialogue policies are typically trained in interaction with a user simulator. To obtain an effective and robust policy, this simulator should generate user behaviour that is both realistic and varied. Current data-driven simulators are trained to accurately model the user behaviour in a dialogue corpus. We propose an alternative method using adversarial learning, with the aim to simulate realistic user behaviour with more variation. We train and evaluate several simulators on a corpus of restaurant search dialogues, and then use them to train dialogue system policies. In policy cross-evaluation experiments we demonstrate that an adversarially trained simulator produces policies with 8.3% higher success rate than those trained with a maximum likelihood simulator. Subjective results from a crowd-sourced dialogue system user evaluation confirm the effectiveness of adversarially training user simulators.
Better Private Linear Regression Through Better Private Feature Selection

Existing work on differentially private linear regression typically assumes that end users can precisely set data bounds or algorithmic hyperparameters. End users often struggle to meet these requirements without directly examining the data (and violating privacy). Recent work has attempted to develop solutions that shift these burdens from users to algorithms, but they struggle to provide utility as the feature dimension grows. This work extends these algorithms to higher-dimensional problems by introducing a differentially private feature selection method based on Kendall rank correlation. We prove a utility guarantee for the setting where features are normally distributed and conduct experiments across 25 datasets. We find that adding this private feature selection step before regression significantly broadens the applicability of ``plug-and-play'' private linear regression algorithms at little additional cost to privacy, computation, or decision-making by the end user.
An Overview of Generative Adversarial Networks

Generative adversarial network (GAN), put forward by two-person zero-sum game theory, is one of the most important research hotspots in the field of artificial intelligence. With a generator network and a discriminator network, GAN is trained by adversarial learning. In this paper, we aim to discusses the development status of GAN. We first introduce the basic idea and training process of GAN in detail, and summarize the structure and structure of GAN derivative models, including conditional GAN, deep convolution DCGAN, WGAN based on Wasserstein distance and WGAN-GP based on gradient strategy. We also introduce the specific applications of GAN in the fields of information security, face recognition, 3D and video technology, and summarize the shortcomings of GAN. Finally, we look forward to the development trend of GAN.
Browser Extensions For The Stretched Health Librarian

Given the multitudes of extensions available, health librarians in Australia, the US, the UK and Europe were asked what extensions they found useful in a work context. From those responses, as well as personal experience using particular extensions, a set of extensions are briefly described below. Focus was given on extensions that are free and potentially useful in a health librarian work setting.
RESEARCH OF EDUCATIONAL SITUATIONS USING THE FOCUS GROUP METHOD IN THE TRAINING OF FUTURE PROFESSIONAL PSYCHOLOGISTS

Introduction. The training of specialists with higher education of various specialties in modern conditions requires the search and implementation of new approaches to teaching various educational subjects. In particular, this concerns the psychological analysis of various situations, which must be taught to be carried out during the training of future professional psychologists. As educational, it is advisable to use situations depicted in movies, artistic ones in particular, selected in a certain way. But even if there is an opportunity to acquaint stu-dents with the procedure of increasing psychological analysis, they are exposed to significant difficulties in its implementation. Therefore, it was decided to use the focused interview method to activate this process. This circumstance makes the task of careful consideration of this topic urgent.Purpose. To consider the possibilities of studying edu-cational situations by the method of focused interview in the preparation of future professional psychologists.Methods. Analysis, synthesis, systematization, speci-fication, generalization.Results. The possibilities of using the focused inter-view method for psychological analysis of various situa-tions in the educational process in the training of future professional psychologists are considered.Originality. For the first time, the application of the fo-cused interview method for the psychological analysis of real situations for educational purposes in the training of future professional psychologists was considered and implemented in practice.Conclution.1. The review of scientific publications on the topic of the study made it possible to find out that in the works of scientists there are developments necessary for the use of the focused interview method, in particular, for the implementation of psychological analysis in the educational process.2. Known scientific developments, as well as our own experience in training professional psy-chologists, allow us to clarify the peculiarities of the pro-cess of psychological analysis for educational purposes, using the focused interview method, which can be used in the educational process.3. The proposed procedure for conducting psychological analysis proved to be suitable for solving educational tasks in the process of training future professional psychologists, meets the current re-quirements for training specialists in higher education, takes into account theexisting features of their training and education, and allows for the optimization of the educational process
The Effect of Using Live Worksheet-Based Electronic Worksheets to Measure Cognitive Learning Outcomes

This study aimed to determine the effect of using live worksheet-based Electronic Student Worksheets (LKPD) to measure cognitive learning outcomes. This research approach uses quantitative research. The subjects in this study were students at Cimanggung State Senior High School class XI for the 2022/2023 academic year, totalling 72 respondents. The data collection method used in this research is a questionnaire method by giving questionnaires and tests to respondents as assessment material. The data analysis used was univariate and bivariate analysis through SPSS software. The results showed that the average value of the group given live worksheet-based LKPD was higher than the group that was not given live worksheet-based LKPD. The average value of the control class is 40.8 (low) to 66.7 (high). At the same time, the average value of the class given the treatment of giving Live Worksheet-based LKPD with a pre-test score (of 41.3), which means low, and a post-test score (of 75.7), which means very high. There is a significant difference in the effect of pre-test and post-test learning outcomes on students who use Live Worksheet-based LKPD in PPKn class XI SMA N Cimanggung lessons.