Reviewerly/exHarmony huggingface dataset:
Analysis of Consensus Mechanisms: PoW and PoS

Along with the trend of Bitcoin blockchain, the concept behind all virtual currency has be-come popular in the study of the Internet. This essay mainly researches two kinds of common consensus mechanisms for the current blockchain network and looks forward to the future development of the technologys usage in daily life. This research aims to overview the two most common consensus mechanisms in the construction of blockchain. By reviewing re-sources from other research, an explanation of the goal of the consensus method, the ad-vantages, and disadvantages of each approach and the future development of these two meth-ods are summarized and developed. The result of the review explains the shifts of mature vir-tual currencies from proof of work to proof of stake and advises what mechanism should be used at starting stage and why a shift is necessary for proof of stake currencies.
The Exploration of AR on Intelligent Packaging

Augmented Reality is a technology that enhances the physical world by adding virtual elements to it, making our physical world more interactive and engaging. AR has been applied to a variety of industries, including education, healthcare, and entertainment. The field of intelligent packaging, on the other hand, is expanding and uses a variety of technologies, like sensors and QR codes, to add value to packaging by improving their usability, convenience, and safety. This essay introduced the use of AR on intelligent packaging. How AR enhance the user experience of a product. Compared the difference between AR + intelligent packaging and traditional packaging and explores the potential of augmented reality (AR) on intelligent packaging. Finally, the paper summarizes and looks forward to the full text.
Breast Cancer Prediction Based on RF-SVM

Breast cancer prediction is crucial in identifying women who may be at risk for developing the disease. By doing the prediction, doctors can make the rapid diagnosis. Additionally, breast cancer prediction can also help guide research efforts and inform public health policies aimed at reducing the incidence and mortality of breast cancer. SVM (Support Vector Machine)is a classic method in machine learning, Random Forest is also widely used but they all have some shortcomings. Random Forest dont have high accuracy. So RF-SVM(Random Forest and Random Forest) is be chosen to do the prediction. The goal of this research is to train a model that can achieve high accuracy in a relatively short time. As for the result, it shows that RF-SVM has achieved a high accuracy(0.95), compared with other method although RF(Random Forest) has the highest accuracy(0.97), it has the lowest precision(0.95). Over all, RF-SVM has the best overall performance. After trial, traditional machine learning methods turns out to be more stable.
PENERAPAN MODEL PEMBELAJARAN QUESTIONING UNTUK MENINGKATKAN KETERAMPILAN MEMBACA PEMAHAMAN SISWA SEKOLAH DASAR

This research is conducted due to the low achievement of students reading comprehension skill on the theme of healthy food material hw the body processes food in the class V SDN 005 Empat Balai On of the solusion to evercome the problem by implementing questioning model. This is a classroom action research with two child each cycle consists of two meetings. The subject of this research is grade V students, total 29 students, 16 male students and 13 famale students. The data collection teachique employed are documentation, observasion, and tes. While technical data analysis uses quantitative and qualitative data analysis. Based on the result of data analysis, it can be seen that the student’s classical completeness in the pre action was 37,93%, then in the first cycle the first meeting in creased to 55,17%, the first cycle the second meeting increased to 68,98%. Furthermore, cycle two meeting one increased to 75,86% and cycle two meeting two increased to 82,76%.. It can be inferred concluded that the application of the questioning model can improve students reading comprehension skills on the reading text material for grade V SDN 005 Empat Balai
Automating Model Comparison in Factor Graphs

Bayesian state and parameter estimation are automated effectively in a variety of probabilistic programming languages. The process of model comparison on the other hand, which still requires error-prone and time-consuming manual derivations, is often overlooked despite its importance. This paper efficiently automates Bayesian model averaging, selection, and combination by message passing on a Forney-style factor graph with a custom mixture node. Parameter and state inference, and model comparison can then be executed simultaneously using message passing with scale factors. This approach shortens the model design cycle and allows for the straightforward extension to hierarchical and temporal model priors to accommodate for modeling complicated time-varying processes.
A Survey of Blockchain IoT Integration

The Internet of Things (IoT) brings people increasingly more convenience nowadays. However, due to the simple structure of most IoT devices and the limited budget when designing and building IoT systems, there are often security vulnerabilities in IoT systems. In addition, the accelerated growth of IoT devices and the data they generate also puts greater pressure on traditional centralised computing centers. Due to its openness, transparency, secure communication, and decentralisation, blockchain technology may solve these problems. This paper mainly studies the research trends of blockchain, IoT, and their integrated systems in recent years and puts forward issues worthy of attention in future development. This paper aims to help beginners get started with blockchain and IoT by providing an overview of blockchain, IoT, and their integration through reviewing and analysing literature. It recommends focusing on chain-chain communication security, new information compression and extraction methods, multi-dimensional evaluation of blockchain IoT systems, information security mechanisms against quantum computers in blockchain IoT integrated systems, and so on.
Pelatihan Dasar Software SketchUp Kepada Remaja RT.04 RW.01 Desa Pepe Kecamatan Tegowanu Kabupaten Grobogan

&lt;p align="justify"&gt;&lt;span&gt;The world of education is one of the sectors that has been affected and has undergone drastic changes in teaching and learning activities from face-to-face to online. The activities that students must participate in, namely the student study service (KKN), must also be carried out independently around their environment. In the current pandemic situation, teenagers in the village have much free time that can be filled with beneficial activities and increase knowledge and abilities, so it is necessary to carry out additional skills training. This KKN is a community service activity carried out by one of the students of the Civil Engineering Department, Faculty of Engineering, Universitas Semarang is conducting basic SketchUp software training for teenagers in RT.04 RW.01 Pepe Village, Tegowanu District, Grobogan Regency. KKN students conduct training by making videos to explain the material and doing hands-on practice from house to house with several teenagers in the village. The teenagers seemed enthusiastic and interested in the software used and in the world of civil engineering and architecture. The activity went smoothly and provided benefits in increasing knowledge and abilities after training.&lt;/span&gt;&lt;/p&gt;
Deep Learning Based Automated Image Captioning System

With the rise of deep learning in recent years, the merging of computer vision and natural language processing has inspired a huge interest. Image captioning is an unique deep learning application that has advanced rapidly in recent years. The ability to train a computer to properly describe the content of an image or an environment like a person has huge implications in computer vision, economics, and a variety of other fields. Across the year, this has been a difficult issue in the field of artificial intelligence, and many researchers have made tremendous progress. In this paper, we describe various deep neural network-based picture caption generation models, including RNN-based decoding and CNN-based accessing and Reinforcement-based framework. We also created captions for some of the images and compared the various feature extraction and encoder models to see which one provides the best accuracy and produces the desired outcome. Extensive experiments on the dataset reveal that the proposed framework outperforms the existing encoder based approach.
Pelatihan Pembuatan Pemodelan Dan Simulasi Banjir Di Kawasan Pesisir Kota Semarang Menggunakan ArcScene 10.4

&lt;p&gt;&lt;em&gt;In the field of regional and urban planning, several media can be used to convey information about the problems of an area. The most commonly used medium is using maps. The analysis carried out to present information in the form of maps varies according to needs. To represent and present flood and tidal information in the coastal area of Semarang City, 3D modeling training was conducted using ArcScene 10.4 software, which is part of ArcGIS software. This modeling is carried out by utilizing DEM (Digital Elevation Model) data and data on the addition of water discharge in coastal areas which will then be processed and simulated in the 3-dimensional form that can be watched in video form. It is hoped that this community service in the form of training can provide further knowledge and understanding regarding mapping activities so that it can be applied in student learning and research activities. So second-semester students of the Urban and Regional Planning Department, Faculty of Engineering, Universitas Semarang have a basic understanding of planning and a more sensitive to urban issues and how to do the right analysis according to the goals and needs of urban planning.&lt;/em&gt;&lt;/p&gt;
Community Policing Information Sharing in Security Enhancement in Gasabo District, Rwanda

In Rwanda, in the aftermath of the 1994 genocide against Tutsi, the security situations were critical and the government adopted mechanisms such as community policing as a strategy for security enhancement. However, the country still struggles with insecurity challenges despite the introduction of community policing. The purpose of this study was to determine the influence of community policing information sharing on security enhancement in Gasabo District, Rwanda. The study adopted a mixed methodology approach and a concurrent triangulation design. The study targeted approximately 139,358 household heads of Gasabo District, 73 Community Policing Committee (CPC) chairpersons, 15 Community Liaison Officers, and 260 Police Officers. The study sampled 576 household heads for quantitative data whereas the CPC chairpersons, Community Liaison Officers, Police Officers, and Opinion leaders were used for qualitative data. A multistage sampling technique was used to select the participants. Questionnaires, interview guides, and discussion guides were used to collect data. The findings indicated that information sharing had a positive and significant influence on security enhancement. The study concludes that information sharing contributes significantly to security enhancement in Gasabo District, Rwanda. The study recommended the need for RNP to strengthen information sharing for security enhancement. In particular, the institution should focus on enhancing information sharing aspects including information sharing through social media, music, word of mouth, acting, and training.
The Effect of the Indonesian Smart Card Program Policy Implementation on Student Learning Motivation (Case Study in SMPN 17 Bekasi)

The purpose of this study was to determine the Effect s of the Implementation of the Smart Indonesia Card Policy on Student Learning Motivation at SMP Negeri 17 Bekasi. The data used in this study is primary data where the primary data data collection method is by means of a questionnaire technique (questionnaire). After the writer did the analysis and was careful, it could be seen that there was an influence between the implementation of the smart Indonesian card program policy on student learning motivation by obtaining a t-count of 2.710 and a t-table of 0.679 at a significance level which showed the level of relationship was in the low category. Meanwhile, the magnitude of the influence of the implementation of the smart card program policy on student motivation was 12%.
Pelatihan Pengenalan Autocad 2D Bagi Siswa Di SMA Kesatrian 2 Yayasan Pendidikan Kesatrian Semarang

&lt;p align="justify"&gt;&lt;em&gt;The rapid development of technology today makes people adapt. In the field of education, especially in the field of engineering drawing design, several computer programs have been very helpful in completing work with good results. Human resources are needed who are willing to learn and able to adapt to technological advances so that they can run computer programs optimally. For high school students who are interested in continuing their education in engineering at the university, skills in using computer programs will be very helpful. Therefore, the Civil Engineering Department, Faculty of Engineering, University of Semarang carries out community service, especially for students of SMA Kesatrian 2 Semarang, namely "Training for Introduction of 2D AutoCAD for Students at SMA Kesatrian 2, Semarang Kesatrian Education Foundation". This training is carried out to provide an introduction to skills in technical drawing with computer programs for high school students so that they can complement the knowledge learned at school. The method used is to do tutorials and practice directly in the Planning &lt;strong&gt;L&lt;/strong&gt;aboratory of the Civil Engineering Department, Faculty of Engineering, University of Semarang. The number of participants in this activity was 25 students. The activity was carried out on August 19, 2019, at the Planning Laboratory of the USM Faculty of Engineering. The students are mostly able to follow the theory and exercises given in this training module.&lt;/em&gt;&lt;/p&gt;
The Impact of SDeaf Design Lab on Creative Design Skills of Deaf Students

The SDeaf Design Lab was established under the Special Education Integration Program of SMK Taman Sutera, Johor. The lab provides a unique opportunity for deaf students to acquire creative skills in graphic design. It is an interactive, multi-sensory environment that allows students to engage with digital media to best develop their design creativity through assigned projects. This study aimed to investigate the impact of assigned projects on the creative design skills of deaf students. In this study, a qualitative focus group research method was used to explore the opinions, experiences, and attitudes of a group of 8 deaf students by having an in-depth discussion about the assigned projects they had worked on. Data were collected through the discussions with these 8 deaf students and the in-depth interviews with the 2 managers from the related graphic design industry. The results of this study demonstrate that the design projects assigned at the SDeaf Design Lab have a significant positive impact on the creative design skills of deaf students. These projects provide opportunities for self-expression, collaboration, and skill development while boosting confidence and preparing students for future professional endeavors in the field of graphic design.
Impact of Managerial Credibility on Employees’ Turnover’s Intentions

INTRODUCTION/BACKGROUND. The paper will examine the impact of a largely unexplored variable, managerial credibility, on employees’ turnover’s intentions. The research paper aims to add value to the existing literature which has cited job satisfaction, job security, and compensation plan to be the variables that influence employees’ turnover’s intentions. Existing literature revealed three major determinants of managerial credibility, trustworthiness, competence, and good will. Moreover, to observe the relationship more closely, turnover was specified as voluntary, avoidable, and dysfunctional turnover. METHODOLOGY. The research program uses quantitative data gathered through 326 respondents, who were employees who had been working in both private and public sector organizations in Karachi for more than a year. The respondents were contacted personally, and were asked to fill out questionnaires. For turnover intention, close-ended questionnaire based on 3-point Likert scale was used, and for managerial credibility, 5-point Likert scale was used. These variables were entered into the multiple regression models for analysis. RESULTS. Overall the employees’ turnover’s intentions increased by 14.7% due to variance in Goodwill (reciprocal), Competence, and Trustworthiness. Furthermore, intent to turnover and the independent variables had a relationship of 39.3% between them (p&lt;0.05). A unit increase in intent to turnover is associated with a statistically significant decrease of 44% (p&lt;0.000) in Trustworthiness, 40% in Competence (p&lt;0.001), and 277% in Goodwill (p&lt;0.010). DISCUSSION. The credibility of the manager does have an impact on the employees’ intent to turnover. Increment in the determinants of managerial credibility can decrease the employees’ intent to turnover, and potentially save the organisation from dysfunctional turnover. CONCLUSION. The results unearthed a new variable that has an impact on the employees’ turnover’s intentions. The impact is low, but nonetheless, it is a factor that organizations should strive to nullify.
Using Convolutional Neural Network for Detection of Face Mask

The COVID-19 pandemic has had a sweeping impact across the globe, resulting in enormous economic losses and significant changes to people's way of life. Despite the World Health Organization's (WHO) assertion that the COVID-19 pandemic will conclude by 2023 and people's lives will begin to settle down, the possibility of a resurgence of the virus cannot be overlooked. In crowded public places, it is essential to have a system that can rapidly and accurately detect whether people are wearing masks and adhering to proper usage protocols. Therefore, it is crucial to make necessary preparations for such a system. Fortunately, there have been notable advancements in facial recognition technology, which can aid in this endeavor. This paper aims to build a model for face-mask-detection with convolutional neural network to help perform a rapid mask-wearing check and carry out the system model training with a final accuracy reaching 0.95. In the end, high accuracy is observed in the classification of correctly wearing masks and incorrectly wearing masks, demonstrating that the model is capable to identify whether people wear masks and wear correctly with the final accuracy reaching 0.97.
Spam Email Filtering Leveraging Improved Text Convolutional Neural Network

This paper outlines the development of anti-spam technology in the last two decades and introduces a novel approach using a convolution neural network (CNN) to tackle the problem of spam filtering. The study uses the TREC06c dataset, containing Chinese spam email data, the dataset is split between a training set and a test set. The paper also introduces the concept of word embeddings, which converts each word in the text into a real-valued vector, better reflecting the semantic relationships between words. The TEXT-CNN algorithm is then discussed, which applies convolutional neural networks to text data and is generated by modifying the TEXT-CNN model to improve its performance in the spam filter. The conclusion of this article is that TEXT-CNN model demonstrates great results in the task of identifying spam emails, and the classification efficiency can be further improved by introducing an attention mechanism and batch processing mechanism by improving the model. The article also provides some ideas for further improvement.
IDENTIFYING FACTORS CONTRIBUTING TO STUDENTS’ OBSTACLES IN UNDERSTANDING READING DESCRIPTIVE TEXT

This study aimed to analyze the students’ obstacles in understanding reading descriptive text since there were many problems that the students encounter in understanding reading text. The method used in this study was a descriptive quantitative through test and questionnaire as data collection instruments. The questionnaire consisted of items to gain the students’ responses towards 3 categories of students’ difficulties factors in reading, namely: learners’ background, teaching technique, and learners’ environment. Seventeen first-grade students in a senior high school in Aceh Besar were involved as participants. The result of students’ reading comprehension test showed that 86,6 % of students were not able to identify references in the text, and 70,6 % of students found difficulty in making inferences in the text. The result of the questionnaire further showed that 71,9% of students agreed toward a lack of interest in reading descriptive text, and 73,5% of students agreed that students’ background knowledge affects their reading comprehension, especially in reading descriptive text. It can be concluded that most of the students found difficulty in identifying and making references in the text, whereas the questionnaire result showed that most of the students lack of background knowledge and interest in reading descriptive text
Enhancing Face Recognition Accuracy Using Data Pre-processing Method and YOLO

The recognition of objects is an essential aspect of visual perception and finds extensive usage in diverse fields such as self-driving vehicles, security, robotics, and image retrieval. In this study, we investigate the performance of the YOLOv5 (You Only Look Once) algorithm for object detection on the VOC2007 dataset. The YOLOv5 model achieved a moderate overall accuracy and precision, demonstrating its potential for object detection tasks. However, the performance varied across different categories, with lower accuracy observed for less frequent categories and difficulties in distinguishing between closely related categories. We identify potential improvements to the YOLOv5 model's performance, including class balancing using weighted sampling and data augmentation, which may help the model to better learn to detect objects from under-represented categories and improve its ability to distinguish between similar objects. The results of our study imply that the YOLO algorithm has potential for object detection and classification projects in computer vision, however further study and refinement are necessary to broaden its efficacy across a greater variety of object classes and real-world scenarios.
IMPLEMENTASI BLENDED LEARNING MELALUI APLIKASI WHATSAPP DALAM MENINGKATKAN LISTENING SISWA DI SMA NEGERI 2 LHOKSEUMAWE

This study aims to determine the listening skills of class XII students at SMA Neg. 2 Lhokseumawe Academic Year 2022/2023 through the implementation of Blended Learning using the WhatsApp application as a media. This research is a classroom action research (CAR) This research consisted of one cycle that consisted of four steps, they are: planning, action, observation, and reflection. To collect data, researchers carried out three steps, namely: Pre-test, Treatment, and Post-test. To analyze the data, researchers used a quantitative research design. Quantitative data were obtained from the pre-test and post-test scores of class XII students. The results showed that there was a significant increase in students' listening skills through the application of the Blended Learning model using the WhatsApp application. The increase can be seen from the pre-test and post-test values in one cycle. In the pre-test, the main score is 60.95 and in the post-test, the main score is 90.55. The average value of the post-test is higher than the pre-test, with an increase of 48.56%. Based on the findings, it can be concluded that the implementation of Blended Learning through the WhatsApp application can improve students' listening skills