Reviewerly/exHarmony huggingface dataset:
Penerapan Augmented Reality dengan Markerless Pada Aplikasi Pengenalan Jenis Hewan Herbivora, Karnivora, dan Omnivora

An introduction to the types of herbivores, carnivores, and omnivores needs to be given to children aged 4 to 6 years, and elementary school students. Submission of material using books is not enough to stimulate the mind, feelings and attention, hence the children feel bored. Several studies that have implemented still have limitations, such as there are no animation features, sound and screenshot share. The purpose of the application of Augmented Reality (AR) with the markerless method in the application of the introduction of herbivores, carnivores, and omnivores is to be able to display the object in three dimensions accompanied by animation features, sound and share information about the animal to social media. This goal is expected to increase children's desire to know more about various types of animals, and applications made can be fun learning media. The method used in this research is waterfall, and the application software is Unity. Application testing is using the blackbox technique to test the functions of the buttons and features displayed in the application. The results of the application trials show that all the button functions that are tried to be pressed will display the scene as expected and the results are 100% valid. From the results of the application trials, it shows that the application has been successfully created in accordance with the desired goal, which can be used as a learning medium for children.
Embedded Mobile App Prototyping

Interactive systems on mobile platforms have characteristics that cause the emergence of challenges in design, development and use. They can be observed in the design processes, particularly in the prototyping and evaluation phases of the design and interaction of mobile applications. While design approaches and paradigms are flexible, the design process needs to be consolidated to meet the potential and diversity of mobile devices. Therefore, the study’s general objective is to evaluate the applicability of adopting a situated and embodied approach for usability tests of mobile applications. For this, Digital Ethnography was adopted, particularly the re-enactment technique, to capture evidence of the effectiveness of the use of the approach. As motivation, there is the theoretical-methodological evolution and the observation that using a post-modern and situated approach provides more complete results than a Cartesian approach. The results show aspects of experience and support for contextual complexity, the unpredictability of the activities carried out, the meanings, contingencies and creatives olutions using the application.
Development of Algorithms and Methods for the Simulation and Improvement in the Quantum Natural Language Processing Area

To achieve faster computational speeds than classical computing, quantum computing is rapidly evolving to become one of the most popular areas of computer engineering. The advent of Noisy Intermediate Scale Quantum (NISQ) devices has made it possible to perform this work on quantum computers in areas like chemistry or machine learning. In the field of machine learning, one of the sub-areas of interest is quantum natural language processing. One of the lines of research already allows not only the encoding of words into qubits, also the association of these words -segmented according to their syntactic categorization-, to quantum combinational circuits or ansatz to allow, for example, the association of this circuit to a neural network.
Prediksi Penentuan Program Studi Berdasarkan Nilai Siswa dengan Algoritma Backpropagation

In continuing higher education, the selection of study programs for students is considered difficult and confusing in choosing the right study program. Data Mining technique is a process of finding new knowledge from a set of databases that can help predict the selection of the appropriate study program. This prediction uses the Backpropagation Neural Network method which aims to assist in the selection of subjects according to student scores with a sample of 50 data to be trained and tested. There are seven input variables used, two hidden layers with varying number of nodes, and outputs that will be used as references in the selection of courses. In this study, the Artificial Neural Network Backpropagation method uses classification performance with Rapidminer software on the target that produces the greatest accuracy is 77.42%.
APPLICATION OF MINIMUM BAYES FACTOR TO A BALANCED TWO-WAY ANOVA WITH RANDOM EFFECTS

The current study applies the minimum Bayes factor proposed by Held and Ott to a Balanced Two-Way ANOVA in a bid to compare its conclusions when the factors are considered as fixed, random, or mixed.A design similar to a setup of the regular Two-Way ANOVA with five replicates per cell was generated using simulation.P-values were obtained from ANOVA summary tables of the simulated design.The P-values were then transformed to obtain the minimum Bayes factor under three cases, namely: Case 1: both factors are fixed; Case 2: both factors are random; Case 3: factor A is fixed and factor B is random.In all three cases considered, the Bayes factor indicates weak evidence against the null hypothesis of zero variability in the effects of the levels of the factors as well as the interactions.The methodology illustrated in this article provides a less complex computational alternative to obtaining Bayes factors for ANOVA designs, which could be helpful in Introductory Statistics Courses.It also provides minimum Bayes factors that are conservative in nature.
The Cultural Dilemma and Breakthrough of Improving Digital Literacy of Primary and Secondary School Teachers

Teacher's digital literacy refers to the ability of teachers to apply digital tools and solve practical teaching problems using digital technology, as well as their literacy in digital thinking, digital cognition, and digital security. It is a new requirement for the literacy of primary and secondary school teachers in the digital transformation of education. Cultivating teachers' digital literacy faces many cultural challenges, including the conservative value orientation of teachers' culture, the influence of teacher mosaic culture, and the tendency of competency in the field of school culture. In order to effectively break through the cultural dilemma of improving teachers' digital literacy, it is necessary to advocate the concept of teacher culture of cooperation and dialogue, empower teachers, and critically inherit traditional culture.
A Systematic Review of the Theory of Learning Progress

This study aims to provide a comprehensive overview of learning progression from five aspects: the origin, definition, components, development model and application status of learning progression, in order to provide reference value for future research.Through the study of previous literature, the following conclusions are drawn: the definitions of learning progression are mainly divided into five categories: process, description, method and hypothesis, and sequence; learning progression is composed of five elements: the starting and ending points of progression, progression dimensions, achievement levels, academic performance at each level, and assessment tools; there are four development models, namely The Assessment Triangle, Berkeley Evaluation and Assessment Research, the Construct-Centered Design, and the ChemQuery assessment system.The current state of research on progression of learning falls into two main categories, research on science concepts and research on science practices.
Disguised Face Recognition using Deep Learning

Abstract: The accuracy of facial recognition has significantly improved thanks to deep learning-based methods. However, several factors including facial ageing, disguises, and position fluctuations impair the efficiency of automatic face recognition algorithms. Disguises are commonly utilized to conceal one's identity or assume the identity of someone else by intentionally or unintentionally altering one's facial features. Here, we intend to make use of the Disguised Faces in the Wild (DFW) small-scale training data. Deep Convolutional Neural Networks(DCNNs) will be trained for general face recognition. The IIIIT-D testing data set will be used for model evaluation because it exhibits greater performance. The IIIT-D testing dataset is used to gauge the effectiveness of the model's performance when applied to faces that have been deliberately disguised. The performance of the results is encouraging and suggests that DCNNs have a chance of successfully recognizing disguised faces.
[Advances in heart failure clinical research based on deep learning].

Heart failure is a disease that seriously threatens human health and has become a global public health problem. Diagnostic and prognostic analysis of heart failure based on medical imaging and clinical data can reveal the progression of heart failure and reduce the risk of death of patients, which has important research value. The traditional analysis methods based on statistics and machine learning have some problems, such as insufficient model capability, poor accuracy due to prior dependence, and poor model adaptability. In recent years, with the development of artificial intelligence technology, deep learning has been gradually applied to clinical data analysis in the field of heart failure, showing a new perspective. This paper reviews the main progress, application methods and major achievements of deep learning in heart failure diagnosis, heart failure mortality and heart failure readmission, summarizes the existing problems and presents the prospects of related research to promote the clinical application of deep learning in heart failure clinical research.心力衰竭是一种严重危害人类健康的疾病，已成为全球公共卫生问题。基于医学影像、临床等数据进行心力衰竭诊断与预后分析能揭示心力衰竭的病程规律，从而降低患者死亡风险，具有重要研究价值。传统基于统计学与机器学习的分析方法存在模型能力不足、先验依赖造成的准确性差、模型适应性不佳等问题。近年来，随着人工智能技术的发展，深度学习方法逐渐开始在心力衰竭领域的临床数据分析应用中展现出新的前景。本文综述深度学习在心力衰竭诊断、心力衰竭生存风险、心力衰竭再入院等方面的主要工作进展、应用方式与主要成果，总结目前存在的问题，提出相关研究展望，以促进深度学习在心力衰竭临床研究的临床应用。.
Application Of The A-Star Algorithm On The Mapping Of Sports Team In The City Of Pematang Siantar Based On Android

Geographic information system is a system that has the function to build, store, manage, and display information related to geography. This geographic information system is very helpful for human work in any case. This Android-based GIS application design produces complete information and can be accessed online or can download the application on our cellphones. Currently the city of Pematang Siantar is developing, especially in the field of technology. This research designs a technology that can help people to find a shortest route solution in searching for information on sports teams and their training locations in the city of Pematang Siantar using the A-Star algorithm. The A-Star algorithm is very helpful because the time to find the nearest route is faster and the routes found can be different but at the same cost, making it easier for designers to code in worksheets. The results of this study are in the form of an android application that is connected to the internet network so that it makes it easier for people to find information about sports teams and the closest location to where the user is using only a mobile phone and anywhere that is reachable by the internet network. This android application displays detailed information about sports teams, training locations, and training schedules controlled by the admin who is responsible for adding and changing sports team data so that the application runs properly.
NOVEL MACHINE LEARNING-BASED APPROACH FOR REAL-TIME SUSPICIOUS ACTIVITY DETECTION IN CCTV FOOTAGE

The detection of suspicious human activities in public areas is critical for preventing terrorism, theft, and other criminal activities.In this study, we propose a novel approach for identifying suspect human activity in live CCTV footage using neural networks.Our method predicts a person's body part or joint placement from an image or video, enabling real-time tracking and classification of routine versus exceptional movements.We focus on public spaces such as bus stations, railway stations, airports, banks, shopping malls, schools and colleges, parking lots, and roads, where intelligent video surveillance is necessary for effective monitoring.To achieve this, we deploy state-of-the-art deep learning techniques for object detection and tracking, and demonstrate the efficacy of our approach on large-scale video datasets.Our results show that our proposed method outperforms existing methods in terms of accuracy and efficiency, providing valuable insights for improving public safety and security.
Penggunaan Media Powerpoint Interaktif Untuk Meningkatkan Hasil Belajar Siswa Sekolah Dasar

This research is motivated by low student learning outcomes. This is because some teachers consider this learning media to be less important, and still use conventional learning media. This study aims to describe the use of interactive PowerPoint media on the learning outcomes of elementary school students. The research method used is Systematic Literature Review (SLR) with the following procedures: (1) Formulate research questions (problem formulation) related to the title; (2) Conduct a search for journal data/Literature Systematic Review (enter keywords into the journal search database); (3) Conduct screening and selection for research journals that are following research problems; (4) The data used is then analyzed; (5) Conducts a critical review of the journals used to see the suitability of the relevant journal criteria; (6) The data has been analyzed, then concluded so that be a conclusion regarding SLR; and (7) Make a final report of the SLR research. The sample for the analysis is 9 published journal articles published in the 2013-2022 range. Based on the classification of journal articles divided into, the research method is 6 Classroom Action Research (PTK) journals and 3 Experimental journals, then based on the lower-class and upper-class categories, and based on subject analysis. It can be concluded that the use of interactive PowerPoint media can improve student learning outcomes in teaching and learning activities, help eliminate boredom, and motivate student learning.
Analyzing Technology Competitiveness and Core Technologies by Countries in the Safety Technologies Sectors Using Patent Statistics and Co-Classification Networks

본 연구는 안전 기술 분야 국가별 기술경쟁력 및 전문화 분야를 분석하고, 이를 통해 국내 안전 기술 분야에 대한 시사점을 도출해 보고자 한다. 이를 위해 국제특허분류 중 안전에 대한 것을 수집하였고, 이들 국제특허분류를 활용하여 미국에 출원된 안전 기술 특허 26,404건을 수집해 주요 특허 지표와 특허분류 동시출현 네트워크를 분석하였다. 연구 결과, 안전 특허 건수 측면에서 미국, 일본, 독일이 각각 11,837건, 4,023건, 2,955건 등으로 가장 많으며, 한국과 중국의 경우 2000년대에 비해 2010년대에 각각 287.1%, 1225.0% 등의 급격한 성장률을 보였다. 미국과 캐나다 등은 특허의 영향력에, 유럽 국가들은 특허의 시장확보력에 중점을 두고 있는 가운데, 한국은 영향력(0.878)과 시장확보력(1.008) 모두 중간 정도 수준을 나타내었다. 반면 상대적 특허활동력 측면에서 한국은 0.407로 최하위권에 머물고 있다. 특허분류 동시출현 네트워크를 통한 국가별 핵심 기술 분야로 볼 때, 세계적으로 제어 및 신호(G05B, G08B, G05D), 전기에 의한 디지털 데이터 처리(G06F), 공작기계(B23Q) 등이 공통적으로 주를 이루는 가운데, 국가별로 다른 특징을 확인할 수 있었다. 한국은 특허의 생산량, 영향력, 시장확보력에는 큰 문제가 없으나, 상대적 특허활동력은 최하위에 머물고 있어 이에 대한 개선이 시급하다. This study examined the technological competitiveness and specialization in the field of safety technology by country to draw implications for strategies in safety technology fields. International patent classifications (IPCs) of safety technologies were identified, and 26,404 safety technology patents filed in the US were used. The patents were analyzed using key patent indicators and co-occurrence network analyses. The result shows that the United States, Japan, and Germany had the most safety patents, with 11,837, 4,023, and 2,955 patents, respectively. Korea and China showed a rapid growth rate of 287.1% and 1225.0%, respectively. While countries like the US and Canada focused on the influence of patents and European countries on the market-securing power of patents, Korea showed a moderate level in both influence (0.878) and market-securing power (1.008). On the other hand, Korea remained at the bottom in relative patent activity with a score of 0.407. When looking at the core technology fields by country through co-occurrence networks of patent classifications, the control and signal fields (G05B, G08B, and G05D), digital data processing by electricity (G06F), and machine tools (B23Q) were commonly dominant worldwide, with different characteristics found among countries. Although Korea has no major issues with the production volume, influence, and market-securing power of patents, there is an urgent need to improve relative patent activity.
Pengelompokkan Daerah Rawan Bencana di Kabupaten Jember Menggunakan Metode K-Means Clustering

&#x0D; &#x0D; &#x0D; This research aims to classify disaster-prone areas in Jember Regency based on disaster-prone index indicators in 31 sub-districts in Jember Regency. The 6 indicators used in this study are the number of disaster events, the number of victims killed, the number of injured victims, the number of damaged houses, the amount of damage to infrastructure and population density. The clustering method used is the K-Means Clustering method. This method is considered quite effective and efficient for grouping large amounts of data. Researchers also used the Davies Bouldin Index (DBI) method to determine the optimal number of clusters (k) used in the clustering process. The results of this study are the optimal number of clusters (k) is k = 3 with the cluster test k = 2 to k = 10, by classifying groups of low vulnerability, medium vulnerability and high vulnerability.&#x0D; &#x0D; &#x0D;
Is Higher Economic Growth Possible Through Better Institutional Quality? Evidence from Nigeria

Using an ARDL model, this study analyzes the impact of institutional quality on economic growth in Nigeria.Employing time series data from the World Bank from 2002 to 2020, it was found that the variable for controlling corruption has a negative impact on economic growth both in the short and long run.More specifically, a one percent rise in corruption results in over nine per cent loss or decrease in economic growth.However, it was shown that long-term political instability has a negative impact on economic growth.Simply put, a rise in political instability by one per cent would lead to over six per cent decrease in growth rate.The findings support the idea that corruption eventually weakens economic performance.As a step in economic policy, it is important to make efforts to fight corruption in every facet of the economy.
Corrigendum: An overview of blockchain efficient interaction technologies

CORRECTION article Front. Blockchain, 03 May 2023Sec. Blockchain Technologies Volume 6 - 2023 | https://doi.org/10.3389/fbloc.2023.1176358
KELOMPOK RISET (KERIS): STRATEGI PENINGKATAN PUBLIKASI ILMIAH BAGI DOSEN DI JURUSAN AKUNTANSI FE UNNES

There still needs to be a higher level of participation as a lecturer in implementing the Tridharma of Higher Education in producing scientific publications. One solution is to initiate the Kelompok Riset (Keris) to increase scientific publications for lecturers, especially lecturers in the Accounting Department, FE UNNES. The approach method used in this community partnership program is AKPL Criteria, USG Analysis, Fishbone Analysis, and Mc Namara Filtering Technique Analysis for determining priority issues and root causes of problems. In addition, the 7M Analysis and Constraint-Solution-Recommendation Analysis were used to prepare and implement Kelompok Riset (Keris)’s technical guidebook. As a result, the Kelompok Riset (Keris) can become the smallest format unit in the technical implementation and substance of research activities by lecturers of the Accounting Department to facilitate the planning, implementation, monitoring, and evaluation of research activities. Hopefully, It will spearhead the reputation of the Accounting Department, Faculty of Economics, Universitas Negeri Semarang on a national and international scale. So the lecturers of the Accounting Department can achieve the targets of articles for publication in Scopus-indexed journals that the faculty has set.
PENGUATAN MASYARAKAT LITERASI MELALUI KOMUNITAS LITERASI “KARSA” DENGAN PENDEKATAN COMMUNITY BASED PARTICIPATORY RESEARCH (CBPR)

The low interest in reading is still a serious problem faced by the Indonesian government. One of them occurred in Kandangan Village, Senduro District, Lumajang Regency. This was due to the lack of public awareness about the importance of literacy culture, lack of interest in learning, and limited facilities and infrastructure that supported reading activities. So that researchers were interested in studying reading interest through the formation of a literacy community. This study aims to describe the community as an intermediary medium for strengthening public interest in reading through the Community Service Program research program. The method used in this research was CBPR (Community Based Participatory Research) by involving the community in program implementation as partners. The result of this research was the formation of a literacy community which is intended as an intermediary media to increase public literacy, with this it is highly expected for the advancement of literacy, especially at SMPN 2 Senduro. Community strengthening was carried out through several actions, including FGD (Focus Groups Discussion), literacy socialization, establishment of reading house and KARSA literacy community. With this, it can make the sustainability of literacy culture in Kandangan Village.
Skrining Fitokimia dan Aktivitas Antikoagulan Sari Buah Melon (Cucumis melo L) Secara In Vivo

Anticoagulants are drugs used to inhibit the development and enlargement of a blood clot. Melon is known to contain adenosime that function to stop clotting of blood cell chip. This study aims to identify secondary metabolites contained in melon juice, fruit juice identify anticoagulant activity in vivo melon, look for an effective dose melon juice as a potential anticoagulant and melon juice compared with aspirin. A total of 15 male mice were divided into 5 groups, i.e. groups of melon juice dose of 12.9 g/kg BW, melon juice dose group of 25.8 g/kg BW, melon juice dose group of 51.5 g/kg BW, positive control group and negative control group. The sample is given once a day orally and measured in hours to 3, 6 and 9 after administration. Anticoagulant effect was tested by using the parameters of bleeding time and coagulation time. The results showed that the melon juice dose of 12.9 g/kg BW, 25.8 g/kg BW and 51.5 g/kg BW may increase bleeding time and coagulation time. From these results it can be seen that the melon juice has anticoagulant activity. Based on statistical test is known that the variation of doses is very significantly affect on bleeding time and the coagulation time.Keywords : anticoagulant, melon juice, bleeding time, coagulation time
Effects of Learning-Based Action-Space Attacks on Autonomous Driving Agents

Vehicle cybernation with increasing use of information and communication technologies faces cybersecurity threats. This extended abstract studies action-space attacks on autonomous driving agents that make decisions using either a traditional modular processing pipeline or the recently proposed end-to-end model obtained via deep reinforcement learning (DRL). The action-space attacks alter the actuation signal and pose direct risks to the vehicle's behavior. We formulate the attack construction as a DRL problem based on the input from either an extra camera or inertial measurement unit deployed. Attacks are designed to lurk until a safety-critical moment arises (e.g. lane changing or overtaking), with the goal of causing a side collision upon activation. Our results demonstrate that the modular processing pipeline is more resilient than the DRL-based agent, due to the former's main focus of trajectory following. We further investigate two enhancement methods: adversarial training through fine-tuning and progressive neural networks, gaining an essential understanding of their pros and cons.