Reviewerly/exHarmony huggingface dataset:
VIDEO PENGAYAAN E- LEARNING POLIBATAM DALAM BENTUK ANIMASI

The development of technology today has taken many roles from various fields, one of which is in the field of education. At this time many educational institutions use internet technology to facilitate the learning process. The application of internet technology is implemented in the form of an online learning system or based on e-learning. With the development of this technology, it is necessary to have an information media that can make it easier for users to obtain information about how to use each feature in the learning system. One of the information media that is currently widely used is information media in the form of video in the form of animation. Submission of information in the form of animated videos will be more interesting and easy for users to understand. The purpose of this study is to create several 3D animated videos as information media regarding the use of features in the Politeknik Negeri Batam e-learning system. The research uses the method of designing or creating products consisting of several stages, namely pre-production, production, and post-production. The results of the research are in the form of four animated videos that contain the use of features in Politeknik Negeri Batam e-learning, each video lasting between 2-3 minutes. The results of this study are expected to provide information about the use of the learning features of Politeknik Negeri Batam so that the use of e-learning can make it easier for students and lecturers to carry out the learning process.
Early prediction in AI-enabled IoT environment

IoT is intelligent sensors and actuators which assemble to form an IoT device. The algorithms employed make the system make up a wise decision. These systems can use artificial Intelligence algorithms to make intelligent decisions. The previous work employs devices that compute normal from abnormal heart rates. These devices are intelligent machines that are carried with the individual. They are also used to calculate the ECG of the personnel. This information understands the behavior of the personnel. The knowledge is sensed and passed to the devices using the Bluetooth technique. This data segment into healthy or unwell being sections. The processing amalgamates transformation, conversion w.r.t format, and section labeling. The iforest approach excludes the outliers from the data set. The suggestion improves the previous work by predicting the abnormality before in hand by 17.5%. Many lives can be saved, and will help improve their lives by adopting this method.
PERANCANGAN KONSEP DESAIN KARAKTER PADA PROYEK PEMBELAJARAN CERITA “PETUALANGAN STEVE”

Recently, there are still many misconceptions among students in the learning process. Various studies recommend that students can collaborate actively and interactively in a practical approach. PBL (Project-Based Learning) is a project-based learning approach for conducting in-depth investigations of a topic. Each student must produce a product to gain deeper knowledge through active exploration of real-world challenges and problems. This product is related to the Character Design course which requires competence in making character concepts according to stories that have been made before, so as to support student assessment. The entire story concept and character visuals are made suitable for all ages in a light and entertaining way. The purpose of this study is to compile an infographic that contains the character concepts in Petualangan Steve. The research method used is a Design Triangle research method, with a focus on deepening the practice of character concept design which includes verbal information from the story. By designing this character concept, the audience can easily understand the visualization or shape of the character by predicting what the expression, physical form, and other details will look like based on the story concept.
Recent Trends in Smart Health Care: Past, Present and Future

Electronic gadgets, actuators, sensors, and software link every element of an active network. The Internet of Things is the name of this network (IoT). AI technology may help networks, sensors, and users create a large quantity of data by assisting in the collection of data and the development of applications. The combination of AI with IoT may advance fields including public safety, education, healthcare, energy, transportation, and other value-added services. Smart health care makes extensive use of the Internet of Things (IoT), notably in the areas of emergency services, intelligent computing, sensors, security, and remote monitoring. Data privacy, integrity, and freshness are just a few of the security issues that must be resolved in a smart hospital. Additionally, there are privacy risks for patients, data eavesdropping, data integrity, and unique identification. IoT technology may be used to monitor a patient's health as well as their data. A patient's status might be tracked remotely and in real time using the internet and other technologies. Additionally, it enables the early identification and treatment of diseases that pose a danger to life. Medical records may be gathered and statistical information on a patient's condition may be provided via an IoT-enabled gadget. With the correct software, huge amounts of data may be handled quickly and without errors. As a consequence of these advancements, which strive to fulfil patients' unique requirements while simultaneously enhancing treatment effectiveness, modern medicine is on the verge of a renaissance. The essential technologies that underpin smart healthcare are briefly described, together with the successes and challenges they have faced, the current status of these technologies in important medical areas, and the possibilities for the future of smart healthcare. Sensors gather data, which is subsequently sent over the internet of things (IoT) to supercomputers and cloud computing for processing and analysis.
Investigating Reading Comprehension and Its Problems: The Perceptions Of 3rd Year English Students, Quest, Pakistan

This research study investigated reading comprehension and its problems. The perceptions of 3rd year English students were recorded. The main aim of this study was to find reading difficulties while reading. This study used survey questionnaire as quantitative method. On the whole 24 students of 3rd year participated in the research. The data was analyzed through Word Excel and presented in percentage. The study gave very valuable results. The findings indicated that students should read a lot and practice in classroom activities. Findings also suggested that students should get help from their teachers in classroom and they should apply reading strategies.
Reconstructing Neutral Face Expressions with Disentangled Variational Autoencoder

This study tackles unsupervised learning for disentangled representations in facial expression generation. It introduces a novel deep architecture by combining FactorVAE and $$\beta $$ -VAE concepts, incorporating the Ranger optimizer and Dropout layers. The goal is to learn disentangled representations that capture essential facial expression factors, like the neutral expression, while ensuring independence between different expression dimensions. This approach achieves faster convergence and improved optimization, striking a better balance between disentanglement and reconstruction quality. The method enables accurate and diverse facial expression generation and enhances model generalization through adaptive learning rate adjustments. The learned disentangled representations also facilitate the generation of realistic and interpretable facial expressions, making it a promising approach for various facial expression generation tasks.
AI and Blockchain-based Solution for Implementing Security for Oral Healthcare 4.0 Big data

The patient's medical data is very valuable and sensitive. Hackers are always trying to steal or tamper with this patient's data. Cyber-criminals can misuse or sell this patient's data. Protecting medical data, and ensuring security and privacy of data is a statutory and ethical mandate for healthcare services providers. Implementation of blockchain technology enhances the security, confidentiality, and traceability of patient data. Secure sharing of patient data among all stakeholders of healthcare ecosystems ensures quality and high speed in services. Objective: This paper's objective is to review data security applications in the healthcare domain using blockchain technology and present the highlights from selected survey papers. The second objective is to implement data security using a web-based prototype based on blockchain technology. Method: This blockchain technology enables secure online sharing of data using open, distributed, denationalized, and immutable ledgers. Blockchain-based online transactions are taking place between sender and receiver directly. Blockchain-based transactions eliminate the need for third-party intermediate agents. Data. Authors applied blockchain technology for the implementation of oral health big data using a web portal. Results: The taxonomy of concepts applied in blockchain and EHR, Smart Contracts, and Healthcare 4.0 systems in healthcare from the literature are mapped. To identify research gaps, a comparative study of curated survey papers is conducted with specific variables. The results of web portal implementation are discussed. Conclusion: At the out, the authors tried to provide a holistic view of blockchain applications and presented insight into systems design by discussing algorithms, techniques and methods applied. Authors conclude that intelligent systems integrated blockchain systems are going to play a vital role in the healthcare industry and enhance the quality and efficiency of services.
Unveiling AI’s Ethical Impact in Marketing Through Social Media’s Darker Influence

Dr. Vijay Prakash Gupta, Associate Professor, Institute of Business Management, GLA University, Mathura, UP India
Promoting Open Science Principles and Primenjena psihologija (Applied Psychology)

At its heart, “open science” is a simple matter of sharing key parts of the research process that are traditionally not shared. These include detailed methods, protocols, and other materials needed to conduct the work: detailed analytical steps or code used for data analysis, the raw data collected during an investigation, and preliminary drafts of the manuscript. A default towards not sharing may be for many reasons, but for many years, the largest reason is that it was simply not possible to share raw data before online publication became the standard. That status quo became embedded in lab culture, and simply changing the status quo in a community as decentralized as the scientific community is always going to be a slow process. The fact that sharing more details about the process of scientific research represents a possible risk for the researcher, in a system where only statistically significant findings are publishable (Dickersin 1990; Komukai, Sugita, and Fujimoto 2023) and where others are not required to share their materials, makes it all the more challenging to move beyond the current state. By presenting activities at the Center of Open Science and efforts by the Primenjena psihologija editorial board, we appeal to our readers and fellow researchers to embrace the open science practice and use the examples provided in this special issue as a guidance for their future scientific endeavors.
A privacy-preserving publicly verifiable quantum random number generator

Abstract Verifying the quality of a random number generator involves performing computationally intensive statistical tests on large data sets commonly in the range of gigabytes. Limitations on computing power can restrict an end-user's ability to perform such verification. There are also random number-based applications where the user needs to publicly demonstrate that the random bits they are using pass the statistical tests without the bits being revealed. Here, we report the implementation of an entanglement-based protocol that allows a third party to publicly perform statistical tests without compromising the privacy of the random bits.
Preparing Future Teachers to Form the Foundations of Safe Behavior of Students in Cyberspace

The article presents one of the ways to improve the effectiveness of professional training of future teachers to form the foundations of safe behavior of students in cyberspace. The author substantiates the relevance of the issues under consideration, the degree of scientific elaboration, as well as the actual problems in the process of preparing future teachers to solve professional tasks of this type. To improve the process of professional training of future teachers to form the foundations of safe behavior in cyberspace for students, the author pro-poses and reveals the essence of two groups of conditions: substantive and procedural-technological. The list of substantive conditions substantiates the impact of the development and the introduction of the elective course “Fundamentals of security in cyberspace”, as well as filling the information and educational environ-ment of the university. Among the procedural-technological conditions, the author considers the importance of instructional assemblies and the inclusion of situational tasks in the educational process of professional train-ing of future teachers. The integrity and coverage of the conditions of all components of the activity allows the author to talk about improving the quality of professional training of future teachers to form the foundations of safe behavior of students in cyberspace.
On the Question of the Demand for Professional Postgraduate Studies in Russia: Analysis of Data on the Thesis Defenses in Technical Sciences

Modern Russian postgraduate school is institutionally oriented towards the reproduction of the personnel potential for science and higher education. Since the career trajectories of a significant part of PhD graduates go beyond the academic labor market, the scientific and pedagogical community is discussing the prospects for the development of the so-called professional postgraduate studies in Russia, which should provide targeted training of highly qualified personnel for knowledge-intensive sectors of the economy and the sphere of intellectual services. The discourse on professional postgraduate studies is focused on the possibility of adapting the effective practices of foreign universities, and, unfortunately, is currently not supported by quantitative data on the demand for such a format of postgraduate training in Russia. The purpose of this study is an empirical analysis of the demand for professional postgraduate studies in the field of technical sciences. Using data on PhD graduates who successfully defended dissertations in technical sciences in 2019 as an example, for the first time a quantitative assessment was made of the prevalence of practice-oriented dissertations, the authors of which are employees of organizations in the knowledge-intensive sectors of the economy. The empirical basis of the study was the publicly available data on the defense of dissertations for the degree of candidate of technical sciences in Russia in 2019 (N=1663). For a detailed analysis, dissertation materials were selected, which contained information about postgraduate studies and the place of employment of dissertators (N=715). As a result of the study, parameters were determined that characterize the degree of prevalence in Russia of practice-oriented dissertations on various disciplinary groups of technical sciences, including: the proportion of PhD graduates employed outside the academic sphere; the proportion of dissertations thematically related to the professional activities of their authors; prevalence of preparation of dissertations on the basis of enterprises of the real sector of the economy; differences in socio-demographic characteristics and publication activity of PhD graduates working on dissertations at universities and in science-intensive business organizations. On the basis of the analysis, a conclusion is made about the expediency of developing professional postgraduate programs in the field of engineering and technology aimed at staffing the innovation sphere, as well as legitimizing the special requirements for these programs and practice-oriented dissertations prepared during their implementation.&#x0D;
Limitations of and Lessons from the Learning of Large Language Models

It is argued that the Curry-Howard correspondence for classical logic implies limitations for logical reasoning that can be learned and performed by large language models. The correspondence establishes an isomorphism between proofs in logic and programs in functional typed lambda calculus. While intuitionistic logic maps to a version of lambda calculus that can be carried out in a local way, i.e., considering local parts of the code in isolation, the version of lambda calculus that corresponds to classical logic requires non-local relations – and this non-locality cannot be learned by large language models due to their restriction to investigate a relative short sequence of tokens. A possible way to go beyond this limitation is sketched as well. Implications for other areas are investigated as well.
Development of Adaptive Site based on NetCat Content Management System

Content management system NetCat 6 provides the development of adaptive websites with CSS3 layout for desktops and mobile devices. Websites are created in no-code mode based on ready-made components; a programming developer is provided with an API for creating components with new functionality. The possibilities provided by NetCat 6 are discussed on the example of a catalog of reconstructed houses with a geoinformation function. The development method consists in creating an interactive prototype of the site by a designer, with subsequent refinement of its automatically generated codes by a programmer. The site was created within the waterfall model of software development that turns project management to an unimprovable simplicity. The practical significance of the work lies in the application of the most predictable software development model in terms of time and cost to create a site with non-standard functionality and adaptive design. An improvement of the NetCat toolkit is proposed to increase the efficiency of the proposed approach.
EPIC THEATER AS A SPECIAL TYPE OF COMMUNICATION

Reviewing Brecht's theatrical system as communication reveals the symbolic nature of the process of transferring a message through theatrical language (code). Combining a significant number of arts, the theatrical code contains various artistic languages that together form a theatrical text. The coding of the idea of a work of fiction in epic theater is done through a gaming strategy of distancing, reminiscent of a demonstratively rational manner of storytelling. Like Lessing and Schiller, Brecht wants not only to entertain the audience, but also to educate them in the spirit of the Enlightenment, to stimulate learning processes, and to develop critical thinking.&#x0D; The transformation of The Beggar's Opera into The Threepenny Opera is a model that demonstrates mastery of applying the material, an exemplary set of rules, and a technique of modification. The "old material" remains visible, but at the same time, the new in it allows us to "perceive things differently." Recognizability of the craft is crucial, because only transparency of approach brings the aesthetics and logic of the performance to the main denominator that makes repeatability possible: communication based on observation. Brecht conceives of observation on the basis of the visibility of a pointing gesture that functions as spectacles that the wearer does not even realize they are wearing. Everyday events are recreated in the manner of an eyewitness, repeated through demonstration, which implies the process of showing itself. The performance shows characters and scenes in an emphatically epic manner. The declared intention to avoid merging of the actor and the character as much as possible, and to demonstrate this as well, alienates the naturalness of the "street scene" and shows it as an artificially created repetition of the stage.&#x0D; The staging of the play as an "opera" generates unexpected visual and acoustic effects. The viewer sees and hears twice: an opera about an opera, as well as a denial of the attempt to imitate an opera as an opera. This performance shows that the Threepenny Opera is no longer a traditional "old opera" and at the same time not the final version of the "new opera." Trivial ideas about groups such as beggars or romantic events such as weddings, stereotypical thinking are dramatized, thus exposing them and encouraging reflection.
Edge-Oriented Compressed Video Super-Resolution

Due to the proliferation of video data in Internet of Things (IoT) systems, in order to reduce the data burden, most social media platforms typically employ downsampling to reduce the resolution of high-resolution (HR) videos before video coding. Consequently, the loss of detail and the introduction of additional artifacts seriously compromise the quality of experience (QoE). Recently, the task of compressive video super-resolution (CVSR) has garnered significant attention, aiming to simultaneously eliminate compression artifacts and enhance the resolution of compressed videos. In this paper, we propose an edge-oriented compressed video super-resolution network (EOCVSR), which focuses on reconstructing higher-quality details, to effectively address the CVSR task. Firstly, we devised a motion-guided alignment module (MGAM) to achieve precise bi-direction motion compensation in a multi-scale manner. Secondly, we introduced an edge-oriented recurrent block (EORB) to reconstruct edge information by combining the merits of explicit and implicit edge extraction. In addition, benefiting from the recurrent structure, the receptive field of EOCVSR can be enhanced and the features can be effectively refined without introducing additional parameters. Extensive experiments conducted on benchmark datasets demonstrate that our method surpasses the performance of state-of-the-art (SOTA) approaches in both quantitative and qualitative evaluations. Our approach can provide users with high-quality and cost-effective HR videos by integrating with sensors and codecs.
Enhancing Ensemble Learning Using Explainable CNN for Spoof Fingerprints

Convolutional Neural Networks (CNNs) have demonstrated remarkable success with great accuracy in classification problems. However, the lack of interpretability of the predictions made by neural networks has raised concerns about the reliability and robustness of CNN-based systems that use a limited amount of training data. In such cases, the utilization of ensemble learning using multiple CNNs has demonstrated the capability to improve the robustness of a network, but the robustness can often have a trade-off with accuracy. In this paper, we propose a novel training method that utilizes a Class Activation Map (CAM) to identify the fingerprint regions that influenced previously trained networks to attain their predictions. The identified regions are concealed during the training of networks with the same architectures, thus enabling the new networks to achieve the same objective from different regions. The resultant networks are then ensembled to ensure that the majority of the fingerprint features are taken into account during classification, resulting in significant enhancement of classification accuracy and robustness across multiple sensors in a consistent and reliable manner. The proposed method is evaluated on LivDet datasets and is able to achieve state-of-the-art accuracy.