Reviewerly/exHarmony huggingface dataset:
Informasi Anatomi MSCT Sinus Paranasal pada Suspek Sinusitis dengan Variasi Rekonstruksi Algorithma

Background: The standard operating procedure with the bone window technique and bone reconstruction algorithm is referred to the MSCT protocol for paranasal sinuses in Hospital. However, the majority of radiologists select a protocol that implements the algorithm reconstruction, which is still trial and error without an organized protocol development study. There is a chance that the accuracy of the MSCT SPN and the quality of the picture data may become crucial problems. This study set out to assess and examine the algorithmic reconstruction method that can yield more accurate SPN anatomical data in sinusitis suspects.Methods: A quasi-experimental technique was taken in conducting the research. Three filters (bone, boneplus, and edge) of the reconstruction method were used to get thirty SPN images from ten patients. The images were assessed by the two expert radiologist.Results: The results of non-parametric was obtained based on statistical tests using the Friedman test ρ-value of anatomy, namely 0.00 less than 0.05. These results indicate that H0 is rejected and Ha is accepted, meaning that there are differences in anatomical information between variations of bone, boneplus, and edge reconstruction algorithms on the MSCT scan examination of the paranasal sinuses with sinusitis suspect. The Friedman test results using the mean rank values of each anatomy show that Boneplus is superior in terms of visualizing anatomy. The Friedman test's mean rank value of the entire anatomy yielded the result that the boneplus reconstruction algorithm is superior to the bone and edge reconstruction algorithm in displaying anatomical information on the MSCT scan of the paranasal sinuses with sinusitis suspect.Conclusions: Based on value mean rank For each Friedman test anatomy and the results of the frequency distribution, variations of the bone plus reconstruction algorithm are more optimal in displaying anatomical information on the MSCT Scan of the paranasal sinuses compared with the edge and bone reconstruction algorithms.
Nilai Entrance Skin Dose Tiroid antara menggunakan Thyroid Shield dan tanpa Thyroid Shield pada Pemeriksaan CT Scan Kepala

Background: CT scans have a much greater dose than conventional radiographic examinations. The thyroid organ is an organ that is sensitive to radiation which is located near the head, precisely in the inferior part of the head so that when a CT scan of the head is carried out, the thyroid organ will be exposed to radiation. The aim of this study was to determine the difference in thyroid skin dose entry value between using a thyroid shield and without a thyroid shield on a head CT scan.Methods: This study is a type of quantitative research with a pre-experimental design. The object of research is Entrance Skin Dose (ESE) of ThyroidOrgan on non-contrast head CT Scan examination. The research location is at the Radiology Department at the Regional General Hospital Prof. Dr. Margono Soekarjo Purwokerto. Sample data number is 50 people (25 samples of non-contrast head CT scans without thyroid shield, and 25 samples of non-contrast head CT scans with thyroid shield. Data was obtained by measuring the radiation dose using a dosimeter placed over the thyroid area during a non-contrast CT scan between using a thyroid shield and without using a thyroid shield. Data analysis was performed using statistical tests Results: The results of measuring the radiation dose to the samples showed that the average radiation dose to the skin surface of the thyroid organ on a non-contrast CT scan without using a thoracic shield was 884.96 µSv and using a thyroid shield was 428.64 µSv. This shows that the average radiation dose from the skin surface of the thyroid organ decreased by 456.32 µSv (51.56%).Conclusions: There is a significant difference in the amount of radiation dose to the surface of the skin of the thyroid organ in non-contrast head CT scans between using a thyroid shield and without using a shield with a dose reduction of 51.6% of the radiation dose without using a thyroid shield.
Implementasi Pemahaman Radiografer terhadap Exposure Index dalam Optimasi Prosedur Pemeriksaan Radiografi Computed Radiography

Background: Increasing the exposure factor is often carried out by radiographers to reduce noise and maintain image quality in computer radiography (CR). Therefore, there is a need for awareness and understanding of the exposure index (EI) to implement optimization procedures in radiographic examinations. Methods: The research method is descriptive and analytical by providing questionnaires to radiographers in PA chest radiographic examinations. This research was carried out at hospitals A, B, and C in the Jakarta-Bogor area with the research carried out between August – October 2023. Statistical analysis used SPSS 27 with data coding previously. After that, the data is processed with descriptive statistics to determine the frequency, distribution, percentage, average, and standard deviation. Then, the test chi-square to determine the relationship between gender, age, education, and work experience in understanding CR optimization procedures. Next, to find out the relationship between age and weight and EI, a test was carried out by Pearson test to determine the level of relationship between the two variablesResults: was found that the level of awareness and understanding of radiographers regarding optimization procedures using EI is still low. Test results chi-square age-understanding 0.309, gender-understanding 0.772, education-understanding 0.036, experience-understanding 0.201. next are the test results Pearson for Hospital-A: age-EI 0.09, weight-EI -0.49, Hospital-B: age-EI -0.21, weight-EI 0.06, Hospital-C: age-EI -0.37, weight-EI 0.56. Conclusions: implementing EI in the optimization procedure, it needs to be confirmed by measuring the patient's radiation dose so that there are no errors in implementing the optimization.
Exploring the Potential Applications of Blockchain Technology in Accounting Practice: A Systematic Literature Review

This study aims to examine the potential of blockchain technology in revolutionizing conventional accounting processes and mitigating persistent inefficiencies and problems. This study introduces the potential of blockchain technology to revolutionize conventional accounting processes and address persistent inefficiencies and challenges. By employing a rigorous search methodology, establishing specific criteria for selection, and conducting meticulous data analysis, this paper presents significant discoveries pertaining to the implementation of blockchain technology in the field of accounting. The results suggest an increasing fascination with the potential of blockchain technology to bring about a transformative impact on the accounting sector. The use of blockchain technology in the field of accounting encompasses several areas such as the recording of transactions, automation of accounting operations, and enhancement of auditing procedures. Application of this technology contributes to the improvement of transparency, integrity, and efficiency in financial reporting. However, for widespread adoption to occur, it is imperative to overcome many difficulties like standardisation, interoperability, scalability, legal compliance, and data protection. The study emphasizes the importance of investigating the possibilities of blockchain technology in the field of accounting to address conventional accounting obstacles. The findings of this study may be utilized by researchers to discover potential areas for further research. Additionally, practitioners can acquire valuable insights into the advantages and difficulties associated with implementing these findings.
Game Multimedia tentang Sistem Tata Surya Berbasis Android sebagai Media Edukasi pada Anak Usia 6-12 Tahun

The solar system is one of the materials from natural science lessons taught in elementary school. However, many students have difficulty understanding and memorizing material about the solar system because of the many different characteristics of each planet. This happens because of the limited learning media provided by the teacher when introducing parts of the solar system. The delivery of material to students must be with a fun method so that students are not easily bored and easy to understand every side of learning. games have great potential in educating children about the solar system, of course, using games that are fun and fun will be more effective for children to absorb all the information contained in the games they play. The design of this game uses the Design Thimgking method, so it can be concluded that this design is a problem originating from a sense of empathy, the need for a solution to an existing problem, then continue to test for improvement. Then the game is created as the main media, then accompanied by other supporting media such as Posters, X-Banners, Game Cards, Stickers, Keychain, and Pins.
STRATEGI PENGGUNAAN FLYER DI MEDIA SOSIAL SEBAGAI SARANA UNTUK MENARIK MINAT BACA MASYARAKAT

The purpose of this study is to describe the activities conducted by religious counselors and to assess the public's interest in flyer media for guidance or counseling. Religious counselors have the task of conducting counseling guidance, developing guidance, and professional development. Before conducting counseling guidance, religious counselors must prepare monographs and activity plans, as well as develop guidance materials and evaluation instruments. This research method uses a qualitative approach, with data collection techniques through observation, interviews, and documentary studies. The method used is descriptive. This study concludes: First, the tasks of religious counselors in conducting counseling guidance for the community begin with guidance preparation, counseling/information services, work plan preparation, guidance or counseling material preparation, guidance implementation, counseling assistance, religious problem mediation, guidance monitoring and evaluation, cross-sectoral cooperation activities, guidance or counseling model development, and guidance or counseling guideline preparation; Second, Flyer media can attract the public's/ congregants' interest in reading. In this case, flyer media is distributed through social media, known as e-flyers. Flyers distributed through social networks are faster, more massive, and more focused on the recipients, accompanied by a call to action to encourage readers to continue reading on the religious counselor's blog.
THEORETICAL AND PRACTICAL PRINCIPLES OF FORMING THE SKILLS OF STUDENTS TO WORK ON THEMSELVES IN MUSIC LESSONS

This article provides a theoretical and practical basis for developing students' self-study skills in music lessons. Music culture classes focus on the importance of activities for students to work on a regular basis, and on how students can improve their musical knowledge through music literacy, listening to music, and singing as a group.
MODERN APPROACHES TO PROMOTING YOUTH CULTURE

The article examines the conditions and topical issues of comprehensive and cultural improvement of the culture of modern youth by further improving the educational process in the family and educational institutions.
Effective Teaching by the Association of College and University Educators (ACUE) in Undergraduate Mathematics Class

Teaching effectively in college is not only key for student’ satisfaction in classroom but also for performance. This research, as a pilot study, has analyzed the survey and course evaluation results from an undergraduate Mathematics class, where The Association of College and University Educators’ (ACUE) effective teaching practices are applied. Results have shown the positive effects from ACUE practices. At the same time, differences in student performance in the same courses from different semesters have been discussed. With the same course content and learning outcomes, teaching with ACUE practices has resulted in better performance throughout the semester. The research compared course evaluations from the same courses in different semesters when including and not including ACUE practices. Results show that students are more satisfied with the courses using ACUE practices. Researcher has made suggestion that ACUE practices should be recommended for use by faculty members in universities and colleges to improve student performance and course satisfaction.
Bibliometric Analysis of Research Trends in Problem Based Learning and Problem Solving Ability (2002-2022)

This study aims to analyze research trends in problem-based learning and problem-solving ability through bibliometric analysis in the Dimensions.ai databases from 2002 to 2022. The method used is bibliometric analysis with stages following the flow chart of Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). The results of the research show that the number of problem-based learning publications and problem-solving ability has continued to increase since 2018. The number of publications on problem-based learning and problem-solving ability ranks first in the field of education. While the most published journal is the Journal of Physics Conference Series. The first rank in the number of publications reviewed by the researcher, I Made Arnawa. Based on the keywords problem based learning and problem solving ability the two are not connected. Thus, the topic of problem-based learning and problem-solving ability can be used as novelty for research and will become a trend in the future. Articles that can be used as references in research that reviews problem-based learning and problem-solving ability are from the Journal of Physics Conferences Series. Meanwhile, the author who can be used as a reference is I Made Arnawa.
PENGARUH MODEL PEMBELAJARAN DISCOVERY LEARNING TERHADAP HASIL BELAJAR SISWA KELAS VII SMP NEGERI 5 MANIAMOLO

Based on the background of the problem, student activity seems to be lacking in the learning process, especially student activity in asking the teacher regarding the material being discussed, students do not understand the material presented, there is a reluctance of students to ask the teacher because they are embarrassed even though they are given the opportunity, but students only listen to the lecture. and do the exercises given. This research aims to determine the influence of the discovery learning model on the learning outcomes of class VII students at SMP Negeri 5 Maniamolo. This type of research is quantitative, descriptive in nature. The population of this research is class VII students, while the sample of this research is students of class VII-A and class VII-B of SMP Negeri 5 Maniamolo. This research data was analyzed using normality tests and hypothesis testing using the SPSS (Statistical product and service solution) application. The results of the two classes, namely the control class and the experimental class, can be said to be more students who have completed learning using the discovery learning model compared to the learning outcomes of students using the conventional learning model and while participating in learning activities using the discovery learning model it appears that in the initial test, students still did not understand the material presented, whereas in the final test after completing the learning process the students really understood what was conveyed by the teacher and were able to get through the assignments given with quite good learning results. Researcher suggestions (1) teachers should use the discovery learning learning model in learning activities because it makes students diligent and think more critically in learning and the attraction gained by studying social studies. (2) Future researchers should carry out this research with a broader scope.
Pelatihan Penggunaan Cairan Klorin Untuk Menurunkan Angka Mikroorganisme Pada Kaset Radiografi

Radiography has an important role in diagnosing a patient's disease, but the equipment used has a considerable risk as a place for the development of nosocomial bacteria which can endanger the patient and radiographer. Cassettes, one of the tools in radiography, have the potential to become a medium for disease transmission and based on previous research it has been proven that there are microorganisms and fungi on the cassettes, so the cassettes need to be cleaned regularly. One of the duties of a radiographer in the field of radiology services is the management of radiology equipment facilities and infrastructure. Cleaning the cassette with 70% alcohol can reduce the number of microorganisms on its surface. The methods in this activity are lectures, simulations, and practice cleaning cassettes with chlorine. The activities were carried out at the Laboratory of the Department of Radiodiagnosis and Radiotherapy Technique at the Semarang Health Polytechnic Ministry with radiographers from hospitals and clinical laboratories in the city of Semarang. The activity begins with the registration, opening, delivering material to the participants, and the simulation of resource persons. Evaluation is done by filling in the pretest and posttest. The evaluation results showed an increase in participants' knowledge of 63% about how to clean cassettes using liquid chlorine to reduce the number of microorganisms on radiographic cassettes. With this training, radiographers are expected to be able to apply cleaning radiographic cassettes with liquid chlorine 0,5% in their respective institutions.
Analysis of Quantum Machine Learning Algorithms in Noisy Channels for Classification Tasks in the IoT Extreme Environment

By 2050, there will be a 50% rise in energy demand, and existing natural and renewable resources will be under extreme scrutiny. Optimizing current power generation and transmission to reduce energy consumption, cost, and other factors is equally vital to upgrading methods for effectively harvesting renewable energy. However, it gets more challenging for conventional computers to perform optimization as the number of factors affecting power generation and transmission rises. Extreme environmental cases will consequently lead to the imperfect functioning of IoT systems. By utilizing quantum-mechanical properties, such as superposition and entanglement, quantum computers can computationally outperform classical computers while consuming much less energy. In this paper, we investigate various quantum machine learning algorithms on two datasets (TWTDUS and SDWTT18) related to IoT extreme environment and study the effect of a noisy quantum environment. We observe that for the TWTDUS dataset, the variational UU† with analytical clustering methods achieves the highest accuracy of 98.10%. Similarly, for the SDWTT18 dataset, the UU† method with k-Means clustering achieves an accuracy of 94.43%. The results show that the accuracy of the proposed quantum algorithms outperforms the existing classical methods and can be utilized to forecast output power generation daily by measuring the metrics required in energy sector decision-making situations. This will be useful to save energy and costs in an IoT-extreme environment, where energy organizations must decide instantly whether to start or stop generating units.
Specific Emitter Identification Using Adaptive Signal Feature Embedded Knowledge Graph

Specific emitter identification (SEI) plays an important role in secure Industrial Internet of Things (IIoT). In recent years, many SEI methods based on machine learning (ML) and deep learning (DL) have been proposed due to their great performance. However, DL-based SEI methods are accompanied by huge computation overhead, which is not suitable for IIoT applications. In addition, the existing ML-based SEI methods rely on feature extraction and a heavy and redundant classifier, which do not ensure optimal feature combination and efficient computation. To solve the above problem, we propose an improved DL-based SEI method using signal feature embedded knowledge graph (KG) composed of universal features. To the best of our knowledge, this is the first attempt to apply KG for SEI technology. Specifically, we explore an adaptive feature combination (AFC) strategy through attention mechanism to realize an efficient SEI classifier. The simulation results show that the proposed KG-AFC algorithm outperforms existing SEI methods in identification performance and computation overhead. At the same time, under the optimal compression rate, the average accuracy of the proposed SEI algorithm is higher than 99.2% and can effectively reduce complexity. The code and the dataset can be downloaded from https://github.com/Lollipophua/KG-AFC.
UAV Base Station Network Transmission-Based Reverse Auction Mechanism for Digital Twin Utility Maximization

Digital twin (DT) technology uses Internet of Things (IoT) devices to collect real-world data and build a virtual world in the DT cloud. However, many IoT devices collect data in harsh natural environments, and these data cannot be transmitted through fixed base stations. Thus, many DT services adopt dynamic data transmission methods, such as transmission through unmanned aerial vehicle base stations (UAV-BSs). However, UAV-BS approaches have many communication constraints, such as limitations on the transmission bandwidth, data throughput, and number of channels. In addition, when integrating a large amount of data submitted by IoT devices, DT service providers need a corresponding mechanism to select the most valuable device data, which can be described by a winner decision problem with the goal of maximizing utility. In this paper, we consider the problem of maximizing the utility of a DT model under UAV-BS network transmission, transform it into a mixed integer programming model with communication and computing constraints, and adopt a reverse auction mechanism to solve it. Specifically, we design an optimal reverse auction mechanism based on optimal allocation and Vickrey–Clarke–Groves (VCG) theory. Additionally, a reverse auction mechanism with polynomial execution time is designed based on monotonic allocation, network maximum flow and critical value theory. These two mechanisms are proven to satisfy individual rationality and truthfulness. Experimental results indicate the favorable performance of the designed mechanisms.
MG-GCN: Multi-Granularity Graph Convolutional Neural Network for Multi-Label Classification in Multi-Label Information System

Recently, many researchers have applied Graph Convolutional Neural Networks (GCN) to multi-label learning tasks by establishing relations among labels. However, these researchers have only used GCN as an auxiliary module and have lacked exploration of object relations, which has limited the inference capability of GCN. Applying GCN to multi-label classification in information systems poses significant challenges to address because information systems are considered as a graph with only nodes and no edges. This article proposes a multi-granularity graph convolutional neural network (MG-GCN) based on object relations to enhance the versatility of GCN and demonstrate its reasoning ability. The MG-GCN efficiently solves complex multi-label classification problems in information systems. Firstly, based on the multi-granularity thinking, the attribute set is divided into several attribute subsets based on granularity. Secondly, a graph of differences representing the relationship between objects is established under each attribute subset. Finally, based on the attention mechanism and multiple difference matrices of objects, MG-GCN is proposed and applied to multi-label classification within information systems. The effectiveness and significance of performance of MG-GCN has been verified through ranking-based indicators and hypothesis tests, respectively.