Reviewerly/exHarmony huggingface dataset:
Application of mixed reality and artificial intelligence to assist medical students in learning injection technique

Introduction: The usage of immersive technology has advanced in a number of areas of life because of the development of technology that keeps pace with the times. Another immersive technology that combines VR and AR is mixed reality (MR), which enables us to interact with 3-dimensional objects in the real world. Since MR technology gives a more nuanced experience, the market is highly promising. This study aims to evaluate the application of mixed reality and artificial intelligence to assist medical students in learning injection technique. Methods: This type of research is analytic with a quantitative and qualitative approach to prove the purpose of the research. This research involved 40 students. Due to the creative nature of immersive technology, it must be combined with other technologies to produce an even more complicated and engaging experience. In order to enhance the quality of the user experience, we will merge MR immersive technology with AI in this research for medical educational field. The integration of these two technologies via an application that can be launched on a Hololens 2 and Magic Leap 1 device and can identify person in a laboratory to support in student learning. Results: For instance, students can utilize artificial intelligence (AI) to learn the names of objects in the lab and do simulation about injection technique. The study 's outcomes are presented in software testing (FPS, CPU, GPU, and load scene) an in the form of user testing utilizing the PIECES Framework (Performance, Information and Data, Economy, Control and Security, Efficiency, and Service), which evaluates the application's utility or significance as well as the satisfaction of its users. Conclusion: The system was able to develop a combining application of artificial intelligence and mixed reality for detecting objects in laboratories to assist learning students, according to the study's conclusions.
Enhancing Security via Speaker Recognition

In this era of globalization, networking, and the bulk of the information they demand reliable identity verification is quintessential. An efficient means to do this is using biometrics as a method of identification. The current biometric method, voice biometrics, may be an inexpensive and precise confirmation technology widely utilized in recent decades. Voiceprint, human biological characteristics, possess unique physiognomic features for every individual who is difficult to counterfeit, imitate, and replace. As a non-contact identification technology, the users are accepting Voice Recognition Technology and extensively deployed in authentication and assisting systems. The procedure of recognizing or refusing the individuality claim of a user is established on the individual’s exclusive information present in the speech wave shape. Recently it received expanding interest in the past two decades, as an accessible, comprehensible way of substituting (supplementing) basic password-type matching.
Artificial Intelligence in Detecting Cyberbullying

Cyberbullying is the use of technology to harass, intimidate, or harm others. It can take many forms, such as online harassment, cyberstalking, and the sharing of embarrassing or compromising photos or videos. It is a serious issue that can have severe consequences for victims, including depression, anxiety, and even suicide. It is important for individuals to be aware of the signs of cyberbullying and to take steps to prevent and address it.
IMPLEMENTASI METODE NAIVE BAYES CLASSIFIER UNTUK KLASIFIKASI SENTIMEN ULASAN PENGGUNA APLIKASI NETFLIX PADA GOOGLE PLAY

The COVID-19 pandemic has led to restrictions on activities in public places or facilities, such as cinemas. This has resulted in increased users of streaming service applications such as Netflix where users can access videos or movies online. Netflix users continue to increase from year to year, but its users began to decrease along with other streaming applications. Related to this, sentiment analysis was carried out on the classification of positive and negative reviews given by users on the Google Play website. The classification is expected to produce good accuracy and be analyzed so that it can be useful information for Netflix and potential users of streaming applications. The Naive Bayes Classifier method is a classification algorithm that is easy to apply and has high effectiveness for classifying text. This method utilizes the concept of conditional probability and has a strong assumption of independence. This study uses 2.850 Netflix application review data on Google Play which is then processed and divided into training data and test data with a ratio of 80:20. Classification with the Naive Bayes Classifier produces an accuracy value of 87,33%, a precision value of 87,6%, a recall value of 93,53%, and an F-measure value of 90,47% so it can be concluded that the performance of the Naive Bayes method is good for classifying user reviews of the Netflix.
Reinforcement Learning-based Knowledge Graph Reasoning for Explainable Fact-checking

Fact-checking is a crucial task as it ensures the prevention of misinformation. However, manual fact-checking cannot keep up with the rate at which false information is generated and disseminated online. Automated fact-checking by machines is significantly quicker than by humans. But for better trust and transparency of these automated systems, explainability in the fact-checking process is necessary. Fact-checking often entails contrasting a factual assertion with a body of knowledge for such explanations. An effective way of representing knowledge is the Knowledge Graph (KG). There have been sufficient works proposed related to fact-checking with the usage of KG but not much focus is given to the application of reinforcement learning (RL) in such cases. To mitigate this gap, we propose an RL-based KG reasoning approach for explainable fact-checking. Extensive experiments on FB15K-277 and NELL-995 datasets reveal that reasoning over a KG is an effective way of producing human-readable explanations in the form of paths and classifications for fact claims. The RL reasoning agent computes a path that either proves or disproves a factual claim, but does not provide a verdict itself. A verdict is reached by a voting mechanism that utilizes paths produced by the agent. These paths can be presented to human readers so that they themselves can decide whether or not the provided evidence is convincing or not. This work will encourage works in this direction for incorporating RL for explainable fact-checking as it increases trustworthiness by providing a human-in-the-loop approach.
Linguistic Alignments: Detecting Similarities in Language Use in Written Communication

Human language has many functions. Our communication on social media carries information about how we relate to ourselves and others, that is our identity, and we adjust our language to become more similar to our community - in the same way as we dress and style and act to show our commitment to the groups we belong to. Within a community, members adopt the community's language, and the common language becomes a unifying factor.
Developing a Web-Based Information System for Sub-Districts in North Sulawesi

This research aims to create an information system in sub-districts in North Sulawesi that can be used easily by sub-district officials to process sub-district data and information. This research uses the Prototype Cycle method which has five stages, namely Quick Plan, Modeling Quick Design, Construction of Prototype, Deployment Delivery &amp; Feedback, and finally Communication. The results of the development of this information system have been created and tested for use. From the test results, it was found that the website-based information system in the Tataaran 1 sub-district, South Tondano sub-district, can be used as a forum for collecting data and information for sub-district officials and can help the community with information related to activities in the sub-district and is easily accessible to all levels of society.
Comparison of Naive Bayes and Dempster Shafer Methods in Expert System for Early Diagnosis of COVID-19

COVID-19 is a respiratory infection disease caused by the corona virus. Transmission of this virus can spread very quickly so that the number of cases of the corona virus continues to grow and becomes an epidemic that spreads not only in Indonesia but also in other countries in the world. The purpose of this study is to build an expert system that is able to diagnose Covid-19 early by using a comparison of the Nave Bayes method and the Dempster Shafer method. The amount of data used in this study is 550 data, consisting of 500 training data and 50 testing data. While the variables used are symptoms related to COVID-19 as many as 17 symptoms consisting of G01, G02, G03, G04, G05, G06, G07, G08, G09, G10, G11, G12, G13, G14, G15, G16, G17. The diagnostic data consists of Suspected (PDP), Non-Suspected, and Close Contact (ODP). The results of the percentage test by comparing system diagnoses with expert diagnoses, for the nave Bayes method it has an accuracy of 96% with 48 diagnoses according to expert diagnoses from 50 tested data. Meanwhile, the Dempster Shafer method has an accuracy of 40% with 20 diagnoses according to expert diagnoses from 50 tested data. Based on the results of this study, the Naive Bayes and Dempster Shafer methods can be applied to an expert system for early diagnosis of COVID-19, from the results of the system testing the Naive Bayes method has better accuracy than the Dempster Shafer method.
ETHNOGRAPHIC SUBJECT IN EXHIBITION ACTIVITIES ALTAI STATE MUSEUM OF LOCAL LORE IN 2023

Using the example of two temporary exhibition projects of the Altai State Museum of Local Lore, the place of ethnographic materials in the exhibition activities of the museum is considered. Today, a significant part of ethnographic objects is taken into account not only as part of the ethnographic collection, but also in the historical and household collection and the collection of decorative and applied arts, which is due to errors in the museum accounting system in the 20th century. Despite this, relying on the concept of «ethnographic object» formulated by A. V. Konovalov and E. Ya. Timofeeva, AGKM employees actively use ethnographic materials in the construction of exhibitions on various subjects using collection (systematic), museum-shaped, ensemble, illustrative and thematic methods
WORKSHOP-QUARRY OF PALEOLITHIC TIME ON THE CHARYSH RIVER (CHARYSHSKY DISTRICT OF THE ALTAI TERRITORY)

The article discusses the materials of the Paleolithic quarry workshop at the outlets of red-brown jasper in the left bank of the Charysh river. The monument is located 20 km upstream from the village. Charyshskoye (Charyshsky district of the Altai Territory). The monument contains chips and fakes, nucleoid products, tools, bifaces, bumpers. Some of the chips have remnants of faceted impact pads. This is evidence of a fairly early dating of the complex within the Paleolithic period.
Z-Score and Floyd Warshall Algorithms for Determining Alternative Routes of Mugging-Prone Areas in Medan City, Indonesia

This study analyzes and implements the Floyd Warshall algorithm using Z-Score to track alternative routes to areas in Medan City, Indonesia that are prone to mugging. The data was obtained from Porlestabes (Police station) Medan-Indonesia. This study employed the Z-Score rank method to rank specific values and determine the levels of crime-prone areas. The highest and lowest levels of crime-proneness were identified using the Z-Score method, and the Floyd Warshall Algorithm is used to identify alternative routes to avoid such areas. The language used in this study adheres to objective and formal writing principles, with value-neutral and clear terminology employed throughout. The results of this analysis showed that out of 99 roads across 18 districts, 4.04% of them were classified as very high prone, 9.09% as high prone, 11.11% as prone, and 75.76% as low prone. The search results from conducting alternative route analysis with the Floyd Warshall algorithm on Perintis Kemerdekaan street indicate the identification of the safest routes.
IDENTITY MANAGEMENT, SSI AND BLOCKCHAIN: A REVIEW

As an individual, in the social and digital world, the burden of managing multiple online IDs and passwords, while handling a host of documents e.g passports, driver’s licenses, Social Security/Aadhar cards and medical insurance cards is cumbersome. Identities both in the social and digital world requires security and privacy: managing these identities efficiently is called Identity Management. Once these identities established, they are produced, shown, send, verified in some way or the other for various processes in Government and non Government purposes. Lately it is established that Blockchain technology has immense use to control over identities (Identity Management) with complete secrecy and privacy. Self-sovereign identity (SSI) is undergoing a transformative evolution, driven by the integration of blockchain technology and Facial Recognition Technology (FRT). This envisioned future entails a paradigm shift where unique facial features serve as the secure key for unlocking one's identity. Blockchain, functioning as a decentralized and secure repository, facilitates the storage of facial data. This convergence of SSI, blockchain, and FRT not only augments security but also streamlines authentication processes, reducing the reliance on conventional passwords and identification documents. It’s a future where individuals can seamlessly access their data, marking a significant advancement in secure and personalized identity management within an academic context.
Phenomenological Study of Teachers in the Virtual Classroom During the PANDEMIC

The study delved into modifications and adjustments that educators underwent in a virtual classroom. It analyzed fundamental practices, guidelines, supervision, and teaching-learning methodologies that were employed in a wired learning environment. It anlyzed the phenomenology in a virtual learning platform during the pandemic that reshaped teachers’ theoretical and practical views on education. The study used Cognitive Constructivism of Jean Piaget. Learning from this frame of reference is known as a self- regulating process of resolving inner conflict that often is apparent through pragmatic experience, collaborative discourse, and reflection (Brooks and Brooks, 1993). The study assessed the process of construction, deconstruction and reconstruction in education. The study used in- depth interviews and focus group discussions of selected faculty members of a private higher education institution in Manila which has fully adopted the online platform at the onset of the pandemic. Some results included deconstruction on authority i.e., teachers face some limitations in instilling discipline and principles normally applied in a face-to-face classroom interaction; reconstruction on active learning i.e., learners are not forced to join synchronous virtual discussions due to erratic internet connection so teachers find other means to provide new avenues to allow student participation; and construction on inclusion as the guiding philosophy in learning. Common narratives among teachers are casualties brought about by the pandemic, mental stability issues, the difficulty of communicating with learners, and the problems and possible improvements of virtual learning. The study’s findings gave way to opportunities for improvements that may be used when revisiting institutional plans of actions, techniques, and educational schemes for virtual learning.
Students’ Perception on English Teaching Effectiveness in the Classroom Activities at SMP Negeri 4 Kota Gorontalo

This research is aimed to find out the students’ perception on English teaching effectiveness in the classroom activities. This research sought students' perceptions on teaching effectiveness in the classroom activities which prompt the utilization of mixed-method. This research was conducted at SMP Negeri 4 Kota Gorontalo. In conducting this research, the participants were the eighth-grade students in SMP Negeri 4 Gorontalo. The eighth-grade in SMP Negeri 4 Kota Gorontalo itself is divided into five classes in which every class contains 25-30 students. The number of participants were 40 students selected from five classes of the eighth-grade. The data was collected using questionnaire and analysed using scoring, analysing problems, and concluding/interpreting. The results showed that English teaching effectiveness in the classroom is good. It was judged from four indicators of effectiveness itself. Those were instructional delivery, student assessment, learning environment, and personal qualities. Based on the research, the four indicators of effectiveness were categorized well. It was proven by the fact that most of the students in the position of agree.
IMPROVING STUDENTS' SPEECH ABILITY THROUGH A COMMUNICATIVE APPROACH TO LEARNING THE INDONESIAN LANGUAGE IN CLASS III ELEMENTARY SHOOL GMIM V TOMOHON

This study aims to improve students' speaking abilities through a communicative approach to learning the Indonesian language of third-grade students of GMIM V Tomohon Elementary School. The research problem formulation is how to improve speaking ability through a communicative approach of third-grade students of GMIM V Tomohon Elementary School. The subjects in this study were third-grade students of GMIM V Tomohon Elementary School with 21 students, while the object of this study was to improve students' speaking abilities through a communicative approach. This research was conducted in two cycles, and each cycle was conducted twice a meeting, so this class action research was successful. Based on the results of the study, it is known that improving students' speaking abilities through a communicative approach in learning Indonesian, from before the action, cycle I and cycle II. In cycle I action, it was known that seven students were complete or classical completeness only reached 60%. In cycle II, the completed students increased to 21 or a classical completeness of 87.61%. Thus, a communicative approach can improve students' speaking ability in learning Indonesian for third-grade students at GMIM V Tomohon Elementary School.
Toward Improving Robustness of Object Detectors Against Domain Shift

This paper proposes a data augmentation method for improving the robustness of driving object detectors against domain shift. Domain shift problem arises when there is a significant change between the distribution of the source data domain used in the training phase and that of the target data domain in the deployment phase. Domain shift is known as one of the most popular reasons resulting in the considerable drop in the performance of deep neural network models. In order to address this problem, one effective approach is to increase the diversity of training data. To this end, we propose a data synthesis module that can be utilized to train more robust and effective object detectors. By adopting YOLOv4 as a base object detector, we have witnessed a remarkable improvement in performance on both the source and target domain data. The code of this work is publicly available at https://github.com/tranleanh/haze-synthesis.
Towards sustainable consumer mhealth apps adoption: Perceived risks versus organizational facilitators review

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Twitter Facebook Reddit LinkedIn Tools Icon Tools Reprints and Permissions Cite Icon Cite Search Site Citation R. Aljabali, N. Ahmad; Towards sustainable consumer mhealth apps adoption: Perceived risks versus organizational facilitators review. AIP Conf. Proc. 21 March 2024; 2750 (1): 090008. https://doi.org/10.1063/5.0148634 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAIP Publishing PortfolioAIP Conference Proceedings Search Advanced Search |Citation Search
Kesalahan Berbahasa Tataran Sintaksis Pada Penulisan Pengalaman Pribadi Siswa Kelas X SMA Bakti Negara

This research aims to describe the level of syntax errors that include aspects of phrases and sentences on writing personal experience grade X SENIOR HIGH SCHOOL Stella Gratia Atambua. This research uses qualitative research designs with the kind of descriptive research. The results of this study indicate that many students make a mistake on a sentence structure that covers ten aspects. These findings prove that students pay attention to the use of grammar in writing, lack of vocabulary which belonged to the students, the influence of the use of local languages, and teachers less use of grammar in writing.
UNSUR DRAMATIK PADA FILM ALI &amp; RATU RATU QUEENS DALAM MEMBANGUN PESAN KEKELUARGAAN

The film "Ali &amp; the Queens" is an example of a family-themed movie. This film has an intriguing storyline as it utilizes dramatic elements to emphasize the message of family bonds. The relationship between Ali and the Queens is predominantly focused on conveying the message of kinship. Ali and the Queens are a family without any blood ties. Their relationship initially starts from a mutually beneficial arrangement. Moreover, their familiarity grows as they are fellow immigrants from the same country. The sense of family between Ali and the Queens develops while living in the same apartment, fostering closeness and care for each other. The purpose of this study is to explore how the dramatic elements in the film "Ali &amp; the Queens" contribute to conveying the message of family. This research employs a qualitative descriptive method. Data collection techniques involve observation, documentation, and literature review. The results of the study indicate that there are ten scenes supported by dramatic elements in conveying the message of family. Three scenes are supported by conflict, three scenes by suspense, two scenes by curiosity, and two scenes by surprise.
Research on smart classroom learning paths and effect testing and evaluation technology based on machine learning algorithm

With the maturity and popularization of artificial intelligence technology, all fields in the country have begun to transform towards intelligent and smart applications. This paper establishes a smart classroom learning path based on machine learning based on bottleneck issues such as the difficulty in systematically, completely, and accurately quantifying the subject ability objectives in the construction of smart learning models, the difficulty in obtaining learning behavior data, and the lack of training in learners' problem-solving abilities and creative thinking abilities. , and finally combined with the algorithm model, this result was applied in specific classrooms. Finally, through statistical analysis, the average accuracy reached more than 85%. It provides a foundation for the application of artificial intelligence in the field of education and the development of smart learning, and provides a reference for subsequent research on smart learning models.