Reviewerly/exHarmony huggingface dataset:
A Modeling Study of a Multi-modal Knowledge Graph of Children's Medical Information

With the rapid development of the application of information technology in the medical field and the gradual improvement of medical information storage standards, medical data presents a multi-modal form while growing rapidly. For managing, organizing and analyzing multi-modal medical data effectively, this paper takes children's medical data as an example, and uses the computer vision processing technology to realize knowledge acquisition, knowledge extraction, entity linking, knowledge storage of multi-modal children's medical data. The structured and unstructured medical data are organized together to achieve the multi-modal children's medical information knowledge graph.
Infosphere, Humans as Inforgs, and Human Agency

This paper is an attempt to shed light on the nature of the information revolution we are facing by focusing on Floridi’s philosophy of information, specifically his book The Fourth Revolution. I will first briefly explain the concepts of hyperhistory and the infosphere, and then identify the core claim of the Fourth Revolution in anthropology, along with the concept of the “inforg.” Copernicus, Darwin, and Freud each contributed in different ways to the rupture of anthropocentrism and the decentering of the human subject. In Floridi’s Fourth Revolution, the decentering of the human subject is related to the fact that we understand ourselves as inforgs, or information organisms. Focusing on the role of technology in mediating the relationship between human perception (experience), action, and reality (the world), I argue that the decentering of the human subject in the Fourth Revolution can be found in a shift in our perception of human agency.
COMPARISON OF SUPPORT VECTOR REGRESSION AND RANDOM FOREST REGRESSION ALGORITHMS ON GOLD PRICE PREDICTIONS

This research was conducted to test how the Support Vector Regression and Random Forest Regression algorithms predict gold futures prices. The data used in this research was taken from the Investing.com website which will later be processed into a prediction model by comparing the SVR and RVR algorithms. The Support Vector Regression and Random Forest Regression algorithms will be tested to see the performance of each prediction model. The test results show that the Support Vector Regression model is superior in terms of accuracy with a value of 83%. However, the Random Forest Regression algorithm is superior with a smaller error rate, namely with an MSE value of 270.85 and an MAE value of 12.53. Keyword: Comparison, Prediction, Support Vector Regression, Random Forest Regression.
DEVELOPMENT OF WEB-BASED REPOSITORY TECHNOLOGY FOR LECTURER'S PERFORMANCE MONITORING

Higher education performance assessment on Accreditation requires the results and evidence of lecturer performance. Currently, the Faculty is already using FTP and Google Drive technology. However, the weakness of using these technologies is that the Faculty still has to process data manually, so it is not effective and efficient. Therefore we need technology that can help effectively and efficiently monitor and record performance along with supporting document evidence. With this web repository, the Faculty can monitor and, at the same time, be able to draw supporting evidence for the preparation of accreditation forms. The research method used in this study is a combination method between Design Thinking and Scrum methods as a method for application development.
IMPLEMENTATION OF THE BEST EMPLOYEES SELECTION IN WANAPOTENSI GUNA (WPG) COMPANIES USING TOPSIS METHOD BASED ON WEBSITE

The number of employees at PT. Wanapotensi Guna will make it difficult for companies to find the best employees, the aim is to improve employee performance to be better every year, the best employee selection is held. The problem that occurs in the process of selecting the best employees so far is that data processing is still manual so it takes a long time. Based on the problems above, the researcher provides a solution to make a decision support system for selecting the best employees using the Topsis method and the Waterfall development method and the programming language used is PHP. Results with DSS for selecting the best employees at PT. Wanapotensi Guna can also minimize the risk of losing employee data, making selection evaluation criteria. the best employees according to predetermined criteria, Keywords :SPK,Best Employee, Topsis, Waterfall .Php.
APPLICATION OF THE FUZZY TIME SERIES MODEL IN CLOTHING MATERIAL STOCK FORECASTING

The application of fuzzy time series is used to view the stock of clothing materials. As for the problem so far, CV Duta Express does not have a model for seeing the stock of complete materials in the warehouse, so the process is not optimal. This will have an impact on orders that come in at the same time and in large quantities. to avoid stock shortages, which resulted in the company experiencing losses. The purpose of this study is to make it easier to predict the stock of clothing materials and to be able to analyze every stock management at CV Duta Express with a fuzzy time series model. The variables used are stock needs, the amount of stock of school clothes, batik clothes, and pants. The research methodology in data collection consists of product type data from 2018–2021 at CV Duta Express Aceh Utara. Data analysis needs consist of school clothes, school pants, and clothes. Next, the fuzzy time series process determines the actual data is the type of school clothes, and what is forecast is sales for January 2018–2021 at the end of December. For a value of 1108 A2 fuzzification value, 172 A4 fuzzification value for batik clothes, and 894 pants with an A1 fuzzification value, then the value of the universe set used is U = [26, 323]. The value of forming a linguistic set is based on the length of the interval U3 = [111,153], U4 = [153,196], and U5 = [196,238]. The result of the fuzzification value from historical data for the value of 172 fuzzification is A4, for data of 133 fuzzification is A3. The formation of Fuzzy Logic Relationship (FLR) values for the period 1/7/2021 to 1/13/2021 is obtained from the data range A4=174 and range A3=125 in each period to be related. The results of forecasting with fuzzy time series testing at the end of December 2021 are 196 stocks of clothes that must be optimized in the following month. The test results in this study are to see if the error value using the AFER model is 0.4511% while the RMSE test value has an error value of 5.0199. After being calculated for the forecast every month, the average obtained for AFER is 0.50154 % and the RMSE is 9.86518.. Keywords : Forecasting, Fuzzy Time Series, stock
Technology trends in deep learning networks for real-time object detection in drone environment

With the recent announcement of the Defense Innovation 4.0 Basic Plan by the Ministry of National Defense, the role and operational scope of drones are expanding as a key force in AI-based, unmanned, and autonomous systems. Consequently, the significance of real-time object detection technology is emphasized as drones take on diverse missions, including delivering, analyzing, and assessing real-time, target-related information. The emergence of recent deep learning has led to substantial advancements in the field of computer vision, particularly in object detection. Deep learning-based object detection is actively being researched, with a focus on algorithms suited for embedded and mobile environments such as drones. This research predominantly aims to develop deep learning-based object detection models that ensure real-time performance and accurately identify objects’ various forms and sizes. Recent object-detection models have been categorized into backbone networks, neck networks, and head networks. By utilizing these three network components, design considerations can be tailored to fulfill the requirements of drone operations. In this paper, we investigate the technology trends of deep learning network models that can be loaded into drones for real-time object detection. Thus we contribute to strengthening effective drone operation in military operations and supporting research and decision-making processes.
Android-Based Internal Quality Audit Application Development at the Faculty of Educational Sciences State University Surabaya

Internal quality audit is considered an important tool to control the governance and operations of an organization. As an independent and objective assurance and advisory function, internal quality audit is designed to increase value through audits of internal control systems, risk management, and governance processes. Awareness of the importance of internal quality audit and also the fact that its effectiveness can be measured is what led the author to conduct research and development of an Android-Based Internal Quality Audit Application, which aims to facilitate the Internal Quality Audit process at the Faculty of Education, State University of Surabaya. The development of the Internal Quality Audit Instrument is carried out by adapting the ADDIE research and development model. The results of the study showed that each category tested got the results, namely: 90% for the functional category; 90% for the design category; 89% for the ease-of-use category; 87% for the suitability need category. The results of the study also explained that the Android-Based Internal Quality Audit Application, Faculty of Education, State University of Surabaya has been effective in each category and is good to be implemented.
Development of E-Book Based Instructional Design PjBL Model Integrated Science Literacy To Improve Critical Thinking Abilit

The aim of the research is to develop e-books based on PjBL model instructional design integrated with scientific literacy to improve students' critical thinking skills. To find out the feasibility validation test of e-books based on the instructional design of the PjBL model integrated with scientific literacy. To find out the E-book Effectiveness test on Critical Thinking Ability. The method to be used in this research is to use the research and development (R&amp;D) method. The research stages are determining the material, preliminary research, analysis, design creation, material creation, initial product development, valid, feasibility test, valid, practicality test. The research data is in the form of feasibility test data by validators and the effectiveness of E-books. In critical thinking skills, the research results show that the feasibility test obtained from validation by material experts and biology teachers is reviewed based on presentation, content and language components obtained an average value of due diligence of 92.50% which is in the category very feasible to use. Meanwhile, the results of the N-gain test on the level of students' thinking abilities after using this e-book obtained a score of 0.80% in the good category in improving critical thinking abilities
Transformers in Machine Learning: Literature Review

In this study, the researcher presents an approach regarding methods in Transformer Machine Learning. Initially, transformers are neural network architectures that are considered as inputs. Transformers are widely used in various studies with various objects. The transformer is one of the deep learning architectures that can be modified. Transformers are also mechanisms that study contextual relationships between words. Transformers are used for text compression in readings. Transformers are used to recognize chemical images with an accuracy rate of 96%. Transformers are used to detect a person's emotions. Transformer to detect emotions in social media conversations, for example, on Facebook with happy, sad, and angry categories. Figure 1 illustrates the encoder and decoder process through the input process and produces output. the purpose of this study is to only review literature from various journals that discuss transformers. This explanation is also done by presenting the subject or dataset, data analysis method, year, and accuracy achieved. By using the methods presented, researchers can conclude results in search of the highest accuracy and opportunities for further research.
MULTI-TASKING LEARNING FOR THE PROBLEM OF DETERMINING THE POSITION AND DIRECTION OF PERSON AT THE TIME

With many practical applications print human life today such as manufacturing surveillance cameras, analyzing and processing customer behavior, …, the problem of face detection and head pose estimation on digital images is being noticed by many researchers. A large number of proposed deep learning models have state-of-the-art accuracies such as YOLO, SSD, and MTCNN, solving the problem of face detection or HopeNet, FSA-Net, and RankPmodelsodel used for head pose estimation problems. According to big many state-of-the-art methods, the process of this task consists of 2 parts face detection to head pose estimation. These two steps are completely independent and do not share information with each other. This makes the model clear print setup but does not leverage most of the featured resources extracted in each model. In this thesis, we proposed the PoseMultitask model with the motivation to leverage the features extracted from the face detection model, sharing them with the head pose estimation branch to improve accuracy. Also, with the variety of data, the Euler angle domain representing the face is large, our model can predict results in the 360° Euler angle domain. Applying the multi-tasking learning method, the PoseMultitask model can simultaneously predict the position and direction of the human head. To increase the ability to predict the head direction of the model, we change the representation of the human face from the rom Euler angle to vectors from the Rotation matrix.
Acute Effects Of Virtual Environment Design On Gait And Balance Control-an Exploratory Study

The lay population is rapidly adopting virtual reality (VR) technology for a number of applications related to education, such as reading. Recent research on VR use reports that it can affect how visual depth is perceived in VR, which could in turn cause disorientation and downstream negative effects on gait and balance. Thus, it is important to determine relationships between VE design and gait and balance control. PURPOSE: The purpose of this ongoing study is to evaluate the acute effects of VE design on gait and balance control following VR use. METHODS: 60 young, healthy participants read a story in one of three VEs for 45 minutes: 1) dark outer space (space), 2) a bright snowy landscape (snow), and 3) a cluttered library (library), which were selected based on their large differences in visual clutter and lighting. Before and following the reading task, participants were asked to perform three standing balance and two gait tasks of varying difficulty. Kinematic and kinetic data were collected during these tasks through an 8-camera 3D motion capture system and two force plates. These data were used to quantify standing balance metrics related to participants’ center of pressure (COP), as well as gait measurements such as velocity and margin of stability. RESULTS: Preliminary findings (n = 12) indicate that reading in the space VE hindered balance, as participants exhibited greater mean COP velocity (0.004 m/s) during single-leg balance compared to the snow (0.001 m/s) and library (0.001 m/s) VEs. Further, participants who read in the space VE walked at a slower velocity (0.67 m/s) following VR use compared to the other two groups (snow = 1.09 m/s, library = 0.8 m/s). The space and library groups had smaller margins of stability during walking following VR use (0.17 m and 0.15 m, respectively) compared to the snow group (0.25 m). CONCLUSIONS: Findings indicate that VE design can influence control of gait and balance following use. Those who read in a dark space environment exhibited the most negative outcomes, which can potentially be attributed to a lack of visual anchors in the space environment, thereby increasing visual fatigue and disorientation. In populations with compromised balance (such as in older adults), the type of VE used should be considered for long-term use.
DECISION SUPPORT SYSTEM IMPLEMENTATION IN DETERMINING STUDENTS TO RECEIVE BOS FUNDING USING THE WASPAS METHOD

Success in learning and learning activities at SMA Asy-Syafiiyah Medan, is not only influenced by teachers, but also by student aspects such as attendance, parental income, activity participation, achievement scores, and discipline. To obtain optimal results, the authors designed an application using the Weighted Aggregated Sum Product Assessment (WASPAS) method that can determine students who receive BOS funds. After calculating 5 times with predetermined criteria, Rizki Ridho Silalahi's final result was 0.9197. The system designed for receiving BOS Fund assistance at SMA Asy-Syafiiyah Medan has been tested by inputting criteria data and carrying out the calculation process using the WASPAS method.
A Study on History &amp; Future Direction of Korean Youth Policy

The purpose of this study was to examine Korean youth policies of each regime from the early 2000s when youth problem became an issue to the present and, using news data, to analyze youth and youth policies of each regime through big data analysis. The period was divided into ① Roh Moohyun regime (2003/03 - 2008/02), ② Lee Myungbak regime (2008/03 - 2013/02), ③ Park Geunhye regime (2013/03 - 2017/04), and ④ Moon Jaein regime (2017/05 - 2022/04). The ‘Youth’ of each regime was analyzed, and the ‘Youth Policy’ was also analyzed for the Moon Jaein and Yoon Seokyeol regimes, the period when the Youth Basic Act was institutionalized into law. Based on the analysis results, plans and directions for the development of youth policies were suggested, including (1) the level of interest in ‘Youth’ and ‘Youth policies’, (2) youth participation and communication, (3) efforts by central government departments and local governments, and (4) comprehensive and comprehensive establishment and promotion of policies.&#x0D; This study contributed to this field by examining and summarizing the change and flow of social interest in youth and youth policies by regime over the past 20 years and, through big data analysis, suggesting development plans and directions for youth policies. Research on youth policy has a short history since it began before and after the enactment of the Basic Youth Act in 2020. For the development of youth policy, many studies on various topics are required.
Forming communicative competence in future specialists of the socio-economic sphere

This article explores the cultural tendencies of verbal etiquette among future professionals in the socio-economic field in the context of postmodern society during their professional training. The aim of the article is to investigate the formation peculiarities of communicative competence in education seekers of socio-economic professions regarding the development of speech culture related to the problem of verbal etiquette in postmodern society. The components of communicative competence in future professionals of the socio-economic field include subjective, praxeological, and gnoseological aspects, which are interdependent and contribute to the development of communicative interaction in their professional activities. The research was conducted within the educational process of higher education institutions, employing identical measurement techniques, time, and duration of training, which allowed for diagnosing the level of communicative competence of future professionals in the socio-economic field according to the criteria of speech culture. Communicative competence of future professionals in the socio-economic field is defined as the integration of scientific knowledge, intellectual and practical skills and abilities, virtual literacy in interpersonal interaction, competence in overcoming communication barriers, general culture, and personal qualities of education seekers capable of solving life-creative tasks.
A Comprehensive Ensemble Deep Learning Method for Identifying Native Advertising in News Articles

Native ads are a popular form of online advertisement that has a similar style and function to that of the original content of the platform they are displayed on. There are several problems in the sponsorship disclosure of native ads, namely their positioning, eminence, and lucidity of meaning, causing readers to not recognize them as advertisement. Unlike the selling message of traditional ads that are explicit, the selling message of native ads are implicit. This study aims to carry out the detection of native ads using deep ensemble-based models. The ensemble learning approach is adopted by combining two deep learning models using dense layers. Furthermore, to overcome the overfitting problem, an attention mechanism using a dense layer is implemented within the model. The experimental results show that the BiLSTM-CNN model with attention mechanism and parameter tuning was able to overcome the overfitting problem and achieve the highest accuracy of 95% for the detection of native ads.
16. Where is ‘victimology’ in an era of #MeToo?

This chapter covers the field of victimology reflecting the increasing recognition of how victims experience crime and other forms of ill-treatment. Sexual abuse gained much attention recently, especially with individuals self-disclosing their personal experiences on social media platforms through the #MeToo movement. Additionally, social media platforms facilitated the new collective potential. The chapter clarifies that victimology is centrally concerned with the understanding of the experience of suffering that recognizes antecedents and risk factors for offending identified in longitudinal studies. The possibility of suffering provides an integrative concept for criminology that correlates to the notions of victimization, offending, and the operation of criminal justice.
Phatic Communication in Online English Class Discussions through Facebook Comments

Phatic communication refers to small talks that aim to form ties of personal union between people or the speakers. Especially in this digital age, phatic communication is somehow still used. This research aims to uncover the kinds and functions of phatic communication used by Indonesian students who have been doing online classes through Facebook, responding to their classmates’ material presentations, and having discussions in the comment column. This current study employs the qualitative method with the document analysis technique. The data of this recent study is the phatic communication used by students during the online course through Facebook, and the data was examined through document analysis techniques from the students’ Facebook comments activity in the form of words, phrases, clauses, and sentences related to phatic expressions. Moreover, the data was analyzed through the following steps: 1) labeling the related data; 2) classifying the data into its types and functions; 3) interpreting the data findings; and 4) drawing conclusions. The study’s main finding is the appearance of phatic expressions, for instance, greeting, thankfulness, compliment, apology, encouragement, and wishing to each other. As the typical conversation is made online through social media platforms such as Facebook, we suggest that some language or conversation styles like abbreviations, non-standard spelling, and emojis have also appeared.