Reviewerly/exHarmony huggingface dataset:
Providing a Model to Estimate the Tax Capacity of E-Commerce

Today, the tax policies of countries have failed after the development of e-commerce.For this purpose, the current research was conducted with the aim of providing a model for estimating the tax capacity of ecommerce.This study was conducted in two parts: qualitative and quantitative.In the qualitative part, the dimensions and components of the tax capacity of e-commerce were identified by the grounded theory method (grounded data) and were categorized into six main networks of the foundation data method.In the quantitative part, the identified variables were modeled by structural equations, and thus, the tax capacity of e-commerce was obtained for each variable.The statistical population in the qualitative section consists of experts and specialists in the field of taxation and e-commerce, including university professors and experimental experts.The sample size was obtained by judgmental sampling, and the saturation level was equal to 15 people.Thus, semi-structured interviews were used as a data collection tool in the qualitative section.In the quantitative part, statistical data related to the components identified in the qualitative part were collected seasonally in the period of 2015-2016.Based on the results of the qualitative section, 6 main networks and 33 sub-components were identified for the tax capacity of e-commerce.Based on the results of the quantitative part, the variables of the nominal value of the volume of electronic transactions from the central phenomenon; the penetration rate of social networks from causal conditions; government income from background conditions; capital market circulation from interfering conditions; the welfare of consumers from the strategies and the contribution of internet shopping transactions to the total banking transactions have the greatest impact on increasing the tax capacity of electronic commerce.
Fine-Tuned Temporal Dense Sampling with 1D Convolutional Neural Network for Human Action Recognition

Human action recognition is a constantly evolving field that is driven by numerous applications. In recent years, significant progress has been made in this area due to the development of advanced representation learning techniques. Despite this progress, human action recognition still poses significant challenges, particularly due to the unpredictable variations in the visual appearance of an image sequence. To address these challenges, we propose the fine-tuned temporal dense sampling with 1D convolutional neural network (FTDS-1DConvNet). Our method involves the use of temporal segmentation and temporal dense sampling, which help to capture the most important features of a human action video. First, the human action video is partitioned into segments through temporal segmentation. Each segment is then processed through a fine-tuned Inception-ResNet-V2 model, where max pooling is performed along the temporal axis to encode the most significant features as a fixed-length representation. This representation is then fed into a 1DConvNet for further representation learning and classification. The experiments on UCF101 and HMDB51 demonstrate that the proposed FTDS-1DConvNet outperforms the state-of-the-art methods, with a classification accuracy of 88.43% on the UCF101 dataset and 56.23% on the HMDB51 dataset.
Diagnostic value of mammography density of breast masses by using deep learning

In order to explore the relationship between mammographic density of breast mass and its surrounding area and benign or malignant breast, this paper proposes a deep learning model based on C2FTrans to diagnose the breast mass using mammographic density.This retrospective study included patients who underwent mammographic and pathological examination. Two physicians manually depicted the lesion edges and used a computer to automatically extend and segment the peripheral areas of the lesion (0, 1, 3, and 5 mm, including the lesion). We then obtained the mammary glands' density and the different regions of interest (ROI). A diagnostic model for breast mass lesions based on C2FTrans was constructed based on a 7: 3 ratio between the training and testing sets. Finally, receiver operating characteristic (ROC) curves were plotted. Model performance was assessed using the area under the ROC curve (AUC) with 95% confidence intervals (CI), sensitivity, and specificity.In total, 401 lesions (158 benign and 243 malignant) were included in this study. The probability of breast cancer in women was positively correlated with age and mass density and negatively correlated with breast gland classification. The largest correlation was observed for age (r = 0.47). Among all models, the single mass ROI model had the highest specificity (91.8%) with an AUC = 0.823 and the perifocal 5mm ROI model had the highest sensitivity (86.9%) with an AUC = 0.855. In addition, by combining the cephalocaudal and mediolateral oblique views of the perifocal 5 mm ROI model, we obtained the highest AUC (AUC = 0.877 P < 0.001).Deep learning model of mammographic density can better distinguish benign and malignant mass-type lesions in digital mammography images and may become an auxiliary diagnostic tool for radiologists in the future.
PENERAPAN MODEL BELAJAR TUNTAS UNTUK MENINGKATKAN KEMAMPUAN MENULIS BUKU HARIAN/PENGALAMAN PRIBADI SISWA KELAS VII SMP NEGERI 3 LAHEWA

Diary writing or personal experience is one of a person's activities or activities to convey ideas of everything that is seen, observed, scrutinized, heard in written form so that the experience is hard to forget.The purpose of this study is to provide an increased ability for students to keep a journal or personal experience through both advanced learning models.Thorough study is a philosophy by saying that with whom students can learn with good results from almost all the lesson materials taught in school.To achieve the purpose of this study, action classes of the four procedures of execution are used (1) planning, (2) action, (3) observation, (4) reflection.The data was analyzed at three stages of data reduction, data exposure, conclusion, the subject of this study was the thirdyear civil rights class vii of the country's 3rd semester, 35 men of 16 and 19 women.Studies have shown that increased ability to keep a journal or personal experience through both advanced learning models (advanced learning) on cycles I score an average of 40 and a high of 90 atan average of 59.14.On the other hand, the results of the first semester of 2008 were 81.71% and the second cycle was 87.42%.Based on research, it may be concluded that the use of the model of learning (advanced learning) to provide increased diary writing or personal experience of the vii class 3 year (14/2015) 3rd year of 2014/2015 learning.Researchers suggest that (1) for Indonesian language and literary teachers in the 3rd land junior high may this study, it may be used asa source of information for teachers to monitor the extent of the ability of students in the journal writing or personal experience, (2) for the state junior high students 3 laheans, so that students can know the extent of the skills they have in keeping a journal or personal experience, (3) for the following researchers, These findings can add insight and experience to learning to write in schools.
Pedestrian detection in thermal and color images using a new combination of saliency network and Faster R-CNN

Pedestrian detection has been an important topic of research due to its increasing demand in the surveillance based applications.Thermal and color images are used to detect pedestrian under different illumination conditions.Recently people have used saliency maps to augment the images as an attention mechanism.This work employs different saliency based networks to evaluate their performances when used for augmentation and to determine the kind of saliency networks which derive better results in combination with Faster R-CNN.It also proposes an enhanced version of the KAIST multispectral dataset with corrected and extended set of annotations for both color and thermal channels separately.Pixel-level annotations for saliency networks are also proposed for thermal and color channels separately by using a subset of KAIST dataset.A detailed analysis of the saliency network performance is presented in terms of precision, recall, F-measure and mean absolute error.A new metric "region-level F-measure" is introduced to study the efficacy of saliency networks while used for augmentation.This work also presents the best combinations of saliency network and Faster R-CNN detector for both thermal and color channels maintaining a trade-off between detection performance and computation speed.The proposed detectors outperform existing detectors of similar type.
K3LH ELECTRONIC MODULE DEVELOPMENT AND INDUSTRIAL WORK CULTURE FOR VOCATIONAL HIGH SCHOOL LIGHT VEHICLE ENGINEERING EXPERTISE COMPETENCIES (ASSISTED FLIP PDF CORPORATE EDITION APP)

This study aims to develop electronic-based module teaching materials on K3LH material and Industrial Work Culture for light vehicle engineering competency competencies in Vocational High Schools by using the Flip PDF Corporate Edition application. This research method was carried out using the Research and Development method using the ADDIE development model, which went through the stages namely: 1) Analysis, 2) Design, 3) Development, 4) Implementation, 5) Evaluation. This stage of testing the feasibility quality of the electronic module was validated by material experts with a percentage value of 94% and media experts at 89%, and reinforced from supporting data for student evaluation of 89%, so that electronic modules were categorized as very suitable for use as learning modules in schools. This effectiveness test is carried out to determine the effect of using the module, then obtained the average pretest test results of 65.47 and 73.00 posttest so that there is an increase in the average value after the treatment is carried out and it is effective. The results lead to the conclusion that there is a difference between the use of electronic modules established with the PDF Corporate Edition flip application on K3LH material and Industrial Work Culture before and after treatment.
JOKOWI'S EMOTIONS ON INSTAGRAM FOLLOWING INDONESIA'S CANCELLATION AS U-20 WORLD CUP HOST

The cancellation of Indonesia as the host of the U-20 World Cup grabbed massive public attention. FIFA canceled due to rejection from various groups such as Bali Governor I Wayan Koster, Central Java Governor Ganjar Pranowo, several parties and mass organizations. President Jokowi also responded to this, starting from affirming that it is necessary to separate politics and sports, to expressing his enthusiasm after the cancellation by FIFA. This research seeks to find out what kind of emotions President Jokowi is trying to display on Instagram social media. Emotions and political communication have a close relationship, as both influence each other and shape public views on political issues. This qualitative research uses AWS Rekognition as a machine learning-based visual analysis tool to determine the emotions displayed. The result of the research is that Jokowi shows a calm emotion. One of the logical assumptions for showing calm emotions is to maintain stability and show that the President is in control of the situation.
Three-dimensional telomere profiling to predict risk of progression in smoldering multiple myeloma.

8056 Background: Multiple myeloma (MM) is preceded by monoclonal gammopathy of undetermined significance (MGUS). A transitional stage of smoldering multiple myeloma (SMM) can be identified between MGUS and MM. While MGUS carries a steady risk of progression of 1% per year, SMM is more heterogenous with nearly 40% of patients progressing in the first 5 years, 15% in the next 5 years, reaching the same low risk as MGUS after 10 years. SMM with its high risk of progression in the initial years after diagnosis presents a viable opportunity for early intervention. For implementing early intervention, the ability to identify SMM patients at the highest risk of progression is critical. This has led to the development of several risk stratification systems. Using these systems high risk SMM patients studied in phase 3 trials demonstrated delayed progression to MM and improved overall survival with early initiation of therapy. However, these approaches showed limited specificity exposing patients at lower risk of progression to therapy. To date, identifying high risk SMM patients and confirming disease stability in low risk SMM patients remain an important clinical need. Genomic instability has been shown to be a sensitive indicator of disease progression in cancer. Telomere dysfunction is an early event in genomic instability. The 3-dimensional spatial profiling of telomeres using TeloView technology allows for quantification of telomere dysfunction, and was shown to be instrumental in risk stratification of cancer patients generally, but particularly in selected hematological malignancies. Importantly, in a previous SMM proof-of-concept study telomeric parameters measured by TeloView technology was found to be significantly different between SMM patients who progressed to active MM within 2 years and those who remained stable for over 5 years. Methods: We analyzed a total of 162 SMM patients using TeloView technology. 88 patients were employed as training dataset in Receiver Operating Curve (ROC) modeling to develop a scoring model that stratifies individual SMM patients based on risk of progression to full stage MM. An additional cohort of 74 SMM patients was used for blind validation of the developed scoring model. Results: We report area-under-the-curve (AUC) in the ROC analysis of 0.8 (accuracy 80%) achieved by the scoring model developed using the training dataset. Furthermore, the independent blind validation achieved positive predictive value of 83% and negative predictive value of 71%, with sensitivity and specificity of 80% and 76% respectively. Conclusions: The result of this study supports presenting TeloView as an accurate prognostic biomarker which appears able to stratify SMM patients into their respective risk groups with high sensitivity and specificity. This will potentially allow for evidence-based treatment decisions for high risk SMM patients and confident monitoring of stable patients.
Pengaruh Model Discovery Learning terhadap Keterampilan Menulis Teks Eksposisi Siswa Kelas X SMA Negeri 2 Kota Sungai Penuh

The purpose of this study was to describe the effect of using the discovery learning model on the writing skills of exposition texts of class X students of SMA Negeri 2 Sungai penuh city. This type of research is a quantitative research with the one group pretest-posttest design experimental method. The population of this study were class X students of SMA Negeri 2 Sungai penuh City who were enrolled in the 2022/2023 academic year with a total of 212 students. The sample of this research was students of class X IPA 4, totaling 34 people who were determined using a purposive sampling technique. The data in this study were the scores of the exposition text writing skills test scores of class X students of SMA Negeri 2 Kota Sungai Penuh before and after using the discovery learning model. The research instrument was a performance test, namely a test of writing skills of expository text. Furthermore, the data were analyzed using the percentage formula, the arithmetic mean formula, and the t-test. Based on the results of the study concluded the following three things. First, the skills of writing explanatory texts for class X students of SMA Negeri 2 Kota Sungai Penuh before using the discovery learning model are in the Enough qualification (C) with an average value of 59.57. Second, the writing skills of exposition texts for class X students of SMA Negeri 2 Kota Sungai Penuh after using the discovery learning model are in the Good qualification (B) with an average score of 79.40. Third, based on the t-test, the alternative hypothesis (H1) is accepted at the level of confidence and degrees of freedom (dk) = (n-1) because tcount&gt;ttable (8.89&gt;1.80). In other words, the discovery learning model has an effect on the exposition text writing skills of class X students of SMA Negeri 2 Sungai penuh City.
Classifying Teaching Competency Types and Exploring Influencing Factors Using Latent Profiles Analysis: Focused on A University

Purpose: The purpose of this study was to classify college faculty members’ group types for the levelof teaching competency using latent profile analysis and to confirm the influencing factors of individualcharacteristics on latent profile group types. Methods: The data were collected from 482 faculty members at A University using an online survey,and 328 pieces of data were collected. After removing outliers through Z-score, 302 were used for latentprofile analysis. Results: The results of this study are as follows: (1) as a result of the latent profile analysis, four groupswere created according to the level of teaching competency, and we named the groups ‘adaptive’, ‘growth’,‘competent’, and ‘proficient’ referring to the expert development level, (2) individual characteristics (gender,major, career) had a statistically non-significant effect on teaching competency based on the latent profile,(3) faculty members who participated in sustaining teaching support programs were in a higher probabilityaffiliated proficient group rather than an adaptive group, and faculty members who applied programcontent in their classes showed a higher probability of belonging to the proficient group rather thanan adaptive, growth, or competent group. Conclusion: Based on these results, this study suggested a significant implication and the necessityof developing teaching support programs according to group types and constructing a system forcontinuous support. Also, this study suggested that colleges should encourage faculty members toapply the content of teaching support programs in their classes.
Peningkatan Hasil Belajar Materi Berbagai Kelompok Sosial Masyarakat Melalui Media Gambar Siswa Kelas V SDN Banyuajuh 5

If the learning media used is not in accordance with the concepts and activities required, then learning activities and student achievement can decrease. Therefore, one solution is to use appropriate learning media. This study aims to: (1) improve the learning outcomes of social group material through the use of media images in fifth grade students at SDN Banyuajuh 5, and (2) assess the effectiveness of media images on student learning outcomes. The subjects of this study were fifth grade students at SDN Banyuajuh 5, Bangkalan Regency, with a total of 12 students consisting of 7 male students and 5 female students. This study uses a type of classroom action research with data collection techniques through interviews, observation, and test evaluation. The results showed that there was an increase in the percentage of successful learning outcomes in cycle I by 50% and increased to 87% in cycle II. From these results it can be concluded that the use of media images can improve learning outcomes of social group material effectively.
DESKRIPTIF KUALITATIF ALASAN MAHASISWA AKUNTANSI FAKULTAS EKONOMI UNPATTI MEMILIH KONSENTRASI AKUNTANSI SEKTOR PUBLIK

&lt;p align="justify"&gt;This study aims to find out the reasons students majoring in accounting at the Faculty of Economics, Pattimura University decided to choose a concentration in public sector accounting, to be precise, students in their sixth semester of the 2022/2023 academic year. This research is a type of qualitative research using an interpretive paradigm. Retrieval of data using interviews packaged in the form of Fucus Group Discussion. The results showed that the reasons for students choosing the ASP (Public Sector Accounting) concentration were due to the preparation of their final project, preferred career goals, factors of interest in Public Sector Accounting, perceptions of wider availability of employment opportunities, perceptions of ASP courses tend to be easier, as well as factors teaching lecturer. Another finding is that almost all respondents are interested in a career as a government employee, although not all stated that the reason for choosing the ASP concentration was because of this.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords&lt;/strong&gt;: Concentration, Accounting, Public, Qualitative, Interpretive&lt;/p&gt;
Application Study of "Blockchain + OTC Market" Model

Blockchain technology has a broad application prospect and application value in the financial industry due to the characteristics of decentralization, programmability and information immutability, and the traditional financial industry is facing new opportunities and challenges. The application scenarios of blockchain technology in OTC market fund registration, electronic contract and data exchange and management are selected to analyze their respective status, application value and compliance, to summarize the application value of blockchain technology in OTC market, to effectively play the innovative effect of "blockchain + OTC market" in the financial industry, and to explore the new application path of blockchain technology.
Analisis penentuan prioritas media promosi ITDA menggunakan Analytical Hierarchy Process (AHP)

The development of the world of education in Indonesia has increased quite highly. This increase can be seen from the increasing number of educational institutions that have been established and grown from elementary schools to universities. One of the influences of promotional activities to run effectively and efficiently is the selection of the right promotional media. This study aims to analyze decision-making using the AHP (Analytical Hierarchy Process) method to determine media promotion priorities. This decision support model will describe complex multi-factor or multi-criteria problems into a hierarchy, according to Saaty, a hierarchy is defined as a representation of a complex problem in a multi-level structure where the first level is the goal, followed by the factor level, criteria, sub-criteria, and so on down to the last level of the alternative. This system can be a companion for decision-making regarding the selection of promotional media. The most important factors and sub-factors that are taken into consideration in choosing Promotional Media, namely: Reach factors with national reach sub-factors, while ITDA uses several promotional media, namely social media, Websites, Billboards, and Banners. Based on the results of this research, the priority order of promotional media that will be used by ITDA is Social Media, with a priority weight of 0.31656293. Website, with a priority weight of 0.31656293. Billboards, with a priority weight of 0.203506909. Presentation, with a priority weight of 0.11560247. Brochure, with priority weight 0.093740094. Banner, with a priority weight of 0.05074091.