Reviewerly/exHarmony huggingface dataset:
Segmentation in Identifying the Development of Ground Glass Opacity on CT-Scan Images of the Lungs

Ground Glass Opacity (GGO) in the image of the lungs is an object that is white in color. The image was recorded using a Computerized Tomography Scan (CT-Scan). This object has very similar color features to other objects in the lung image, making it very difficult to identify precisely. Likewise by observing the development of this object every time from recording continuously. This study aims to segment the GGO on CT-Scan images that are examined repeatedly due to an increase in complaints against patients. The processed image is an image of the lungs from the CT-Scan equipment. Patients were recorded twice at different time intervals. The processed image is an axial slice of the data cavity as a whole, totaling 12 images for each patient in each recording. The tool used for recording is a CT-Scan with the General Electric (GE) brand model D3162T. The method used is parallel processing with a combination of Image Enhancement techniques, Convert to Binary Image, Morphology Operation, Image Inverted, Active Contour Model, Image Addition, Convert Matrix to Grayscale, Image Filtering, Convert to Binary Image, Image Subtraction and Region Properties. The results of this study can identify the development of the GGO pixel size well, where the increasing number of patient complaints, the larger the GGO area. The extent of development of GGO is irregular with respect to time and examination. Each patient experienced an expansion of GGO by an average of 0.54% to 1.89%. This study is very good and can correctly identify ARF, so it can be used to measure the level of development of ARF in patients with accuracy.
The Effect of Puzzle Media on Learning Motivation and Mathematics Learning Outcomes in Elementary School Students

Media Puzzle is one of the media for learning and playing with demonstration methods will be able to influence student motivation and learning outcomes. In this research, we will analyze the effect of the use of the demonstration method with puzzle media on learning motivation and learning outcomes in mathematics for class IV SDN 1 Rantepao. The following research was carried out using a quantitative approach and was designed using the pre-experimental one group pretest-posttest model. The following research has a population and sample of fourth grade students at SDN 1 Rantepao, a total of 81 students divided into 3 parallel classes. Using the cluster random sampling technique, class IVa was obtained with 27 samples. Data was collected by testing techniques, student activity sheets, questionnaires, and documentation. Based on the test results obtained t count = 20.634&gt; 1.70329, it can be concluded that there is an influence of the demonstration method with puzzle media on learning motivation. Based on the t test on learning outcomes obtained sig. (2-tailed) = 0.000 &lt;0.05, it can be concluded that there is an influence of the demonstration method with puzzle media on learning outcomes..
IMPROVING STUDENTS’ WRITING SKILLS THROUGH MIND MAPPING TECHNIQUE INTEGRATED WITH PICTURE SERIES

The present research aimed at finding out how mind mapping using picture series improved students’ writing skills and how it can encourage students’ interest in teaching and learning process. To reach the aims of the research, the present research used a classroom action research.There were 17 participants in the research which consisted of 8 females and 9 males of Bussiness Management Study Program Students at Darwan Ali University Unit II. The present research was conducted in two cycles. Cycle I had three meetings and the second II had two meetings. In this classroom action research, the researcher conducted the plan, action, observation, and reflection.The results of the finding showed that (1) The application of mind mapping using picture series can improve students’ skill based on the calculation of the percentage, the students who achieved score 65 and more were 100 %. It was higher than 80%; (b) Mind mapping using picture series made the students interested to learn English writing. Before the actions were conducted, the students were less motivated in the teaching and learning process. After the implementation of the actions, they were more enthusiastic to get involved in the teaching and learning process. They became active and paid attention during the lesson. Besides, the students were autonomous in learning without depending on their friend’s works in doing the tasks.
AN ANALYSIS OF STUDENTS WRITING ABILITY IN USING TRANSITION SIGNAL IN DESCRIPTIVE PARAGRAPH AT EIGHTH GRADE OF SMP ISLAM TERPADU DHU’AFA MERANGIN ACADEMIC YEAR 2021/2022

The students still difficult in using transition signal especially in writing descriptive paragraph. The researchers have conducted a research to analyze the students’ ability in writing a paragraph at SMP Islam Terpadu Dhu’afa Merangin. This research has focused on the students’ writing ability in using transition signal in descriptive paragraph. The type of this research is descriptive quantitative at the eighth grade of SMP Islam Terpadu Dhu’afa Merangin academic year 2021/2022. The students were consisting of 21 students. For representative sample, the researcher used total sampling. The technique in collecting data was used test. Then analyzing the data from the mean score of the students’ writing ability in using transition signal of descriptive paragraph. Based on he result of the test, it shown that the mean score of students was 70.24 (incomplete). It can be concluded that some students still confused in writing descriptive paragraph by using transition signal. Key words: Writing ability, Transition Signal, Descriptive Paragraph
KESULITAN BELAJAR PESERTA DIDIK DALAM PEMBELAJARAN DARING SELAMA MASA PANDEMI DI SMAN 1 TEMPURAN

Online learning is a big challenge for teachers and students, this is because teachers cannot see the learning process directly and students have learning difficulties. In addition, students cannot understand the material that has been delivered by the teacher online. This study aims to determine the causes of student learning difficulties in online learning and to determine efforts to overcome student learning difficulties in biology subjects.This research is a descriptive research. The subjects of this study were students who had learning difficulties and the biology teacher of class XI IPA SMAN 1 Tempuran with the object of this research being students who had learning difficulties during online learning. The sample used is class XI IPA with a population of 176 students. Data collection techniques using a questionnaire through the google form platform and interviews. Data analysis was carried out quantitatively and qualitatively.The results of data analysis showed that internal motivation indicators caused students' learning difficulties in understanding biology subjects during online learning, which was 75%. On external factors, social indicators cause students' learning difficulties in understanding biology subjects during online learning, which is 65%. Efforts to overcome students' learning difficulties do group study and independent study.
Design and Implementation The digital transformation of the student clearance system for Soran University

This project aimed at creating and implementing a web-based portal that allows students of the university of soran to be able to commence and complete the annual process of course clearance online instead of physically navigating sections offices. The student clearance system is an internet-based study initiative that will help facilitate the queuing system in the clearance process of the university. The student clearance system can provide an efficient handling of information that is very easy for universities to use since it is internet-based and can be viewed from anywhere and at any time, and this system or process is also performed every year at the end of the second Semester by students. Students at Soran University in all scientific departments can register through this web application and do end-of-year cleaning work at the university. In this way, we will avoid using paper and loss, and the creation of student crowds at the doors of departments. and facilitating students to do so via the Internet. The computer-based architecture in this project was introduced using the PHP language, JavaScript, CSS, HTML and the software database as MySQL. The program created would act as a more effective and productive way of clearing students, eliminating all types of delay and tension, as well as helping you to understand the process involved, as well as how to do your online clearance. This research work uses the compilation of data from the university, materials and the program has been designed to accomplish the project objective efficiently.
The Effect of Holding Pressure and Inject Pressure to Short Shot Defect in Injection Molding Cover Pot

The influence of inappropriate injection molding parameters often results in product defects, one of which is the short shot, which is a condition where the plastic to be injected into the cavity does’t reach the ideal capacity. The purpose of this research is to understand and be able to explain the parameters of holding pressure, inject pressure, and the interaction of these two parameters on short shot defects in cover pot products with the injection molding process. This research uses independent variables, namely holding pressure with variations of 20 Bar, 30 Bar, and 40 Bar and inject pressure with variations of 15 Bar, 30 Bar, and 45 Bar and dependent variables in the form of short shot defects. The method used in this research is a factorial experiment with replication of 10 (ten) times and data processing analysis using ANOVA with the help of Minitab 21.2.0 statistical software. The result of this research is that there is a significant influence of holding pressure, inject pressure, and the interaction of these two parameters on short shot defects in cover pot products with injection molding process. The average weight of the product produced at the interaction of the parameters holding pressure 40 Bar and inject pressure 45 Bar is 8.8 grams (normal) so as to minimize product defects to improve the quality and quantity of cosmetic packaging production cover pot.
Retracted: On the Intelligent Computing Model of Diagnosis Teaching in Preschool Education in Colleges and Universities under the Background of Big Data

[This retracts the article DOI: 10.1155/2022/7183032.].
Retracted: Artificial Intelligence-Based Semisupervised Self-Training Algorithm in Pathological Tissue Image Segmentation

[This retracts the article DOI: 10.1155/2022/3500592.].
Retracted: Simulation of Transmission System of Crawler Self-propelled Rotary Tiller Based on Deep Learning

[This retracts the article DOI: 10.1155/2022/6078223.].
Retracted: Smart Heart Disease Prediction System with IoT and Fog Computing Sectors Enabled by Cascaded Deep Learning Model

[This retracts the article DOI: 10.1155/2022/1070697.].
Retracted: Optimization of English Grammar Expression Based on the Discrete Dynamic Analysis Algorithm

[This retracts the article DOI: 10.1155/2022/8742711.].
Retracted: Blockchain and IPFS Integrated Framework in Bilevel Fog-Cloud Network for Security and Privacy of IoMT Devices

[This retracts the article DOI: 10.1155/2021/7727685.].
Diverse Gaussian Noise Consistency Regularization for Robustness and Uncertainty Calibration

Deep neural networks achieve high prediction accuracy when the train and test distributions coincide. In practice though, various types of corruptions occur which deviate from this setup and cause severe performance degradations. Few methods have been proposed to address generalization in the presence of unforeseen domain shifts. In particular, digital noise corruptions arise commonly in practice during the image acquisition stage and present a significant challenge for current methods. In this paper, we propose a diverse Gaussian noise consistency regularization method for improving robustness of image classifiers under a variety of corruptions while still maintaining high clean accuracy. We derive bounds to motivate and understand the behavior of our Gaussian noise consistency regularization using a local loss landscape analysis. Our approach improves robustness against unforeseen noise corruptions by 4.2-18.4 % over adversarial training and other strong diverse data augmentation baselines across several benchmarks. Furthermore, it improves robustness and uncertainty calibration by 3.7% and 5.5 %, respectively, against all common corruptions (weather, digital, blur, noise) when combined with state-of-the-art diverse data augmentations. Code is available at https://github.com/TheoT1/DiGN.
Data Mining Implementation Of Electronic Products Sales Using Apriori Algorithm (Case Study Of Fokus Komputer Shop)

Focus Komputer Store is one of the computer shops in Bengkulu City which is the destination for consumers in looking for computer-related goods and providing computer service services. Every day the sales transaction data in stores continues to grow and causes a very large data storage. Most sales transaction data are only used as archives without being put to good use. The process of selecting goods is carried out by taking into account the pattern of purchases in the previous month so that a list of items that must be provided is more extensive to meet current consumer needs. The problem is market interest or consumer needs are always changing depending on uncertain conditions. The process of selecting goods to fill stock is a very complicated process and takes a long time because you have to read the sales archives that were made the previous month. For this reason, it is necessary to have an application that can provide recommendations on what items are currently in demand by consumers based on last month's sales data. Applications that can be used for the process of extracting previous data are data mining applications. Data mining is an analysis of reviewing data sets to find unexpected relationships and summarize data in different ways that are understandable and useful to the data owner. To be able to get results that are more relevant to needs, applications must use suitable algorithms, one of which is the Apriori algorithm. The a priori algorithm is an algorithm that searches for frequent itemsets using the association rule technique. The application can be used as a sales cashier application at the Computer Focus store and can display the results of a priori algorithm calculations based on sales data that has been input into the application. The application that the author has built still has many shortcomings, especially in terms of appearance and data. The author hopes that there are criticisms and suggestions that can help in developing applications so that they are even better.
DRSU-net: Depth-Residual Separable U-net model for Semantic Segmentation

In recent years, semantic segmentation has become an increasingly important task in computer vision, with numerous applications in image analysis and object recognition. One popular approach for semantic segmentation is the use of convolutional neural networks (CNNs), such as the U-net architecture, which is known for its ability to capture both local and global contexts in images. However, the U-Net model can be computationally intensive and time-consuming, especially for large or high-resolution images. This paper proposes a depth-residual separable U-net (DRSU-net) model to improve the U-net model for semantic segmentation tasks. The proposed approach introduces an additional regularisation technique instead of dropout and L2 regularisation and modifies the network's structure to reduce the risk of overfitting and the number of model parameters. This reduces training time without losing model information, especially for large datasets. The effectiveness of the DRSU-net method is demonstrated through extensive experiments on several semantic segmentation benchmarks. The results show improved performance and lower temporal complexity compared to the basic U-net and state-of-the-art architectures.
General Intelligent Dataset Description Method and Application

Abstract With the development of the Internet, the growth rate of big data has exceeded the ability of human beings to obtain information from data. In the near future, faced with the sea of data, seemingly logically correct algorithms may come to the opposite conclusion, which will be a “data disaster” era. Therefore, letting data “speak” and enable data intelligence is an important problem that must be solved in the field of big data research. In this paper, we propose a “data intelligence” framework based on Brooks’s Subsumption Architecture for robotics. In this framework, we define a new dataset description method and try to encapsulate the dataset described by this method into a software container. Then, we set up the corresponding operations on the dataset container. Finally, we identify an interaction model for a “dataset agent” based on academic work on agents in the field of artificial intelligence. And we designed and implemented some functions of an intelligent document manager, which proves that our design ideas and methods are feasible.
Used Motorcycle Purchase Decision Support System Using Simple Additive Weighting (Saw) Algorithm

Motorcycle vehicles are one of the means of transportation that are needed by the community because motorbikes can provide good mobility in congested areas. The author will make a system analysis for the selection of used motorcycles in the Zakiyah Motor showroom based on a Decision Support System using the Simple Additive Weighting (SAW) method. This application is made using the PHP Programming Language and MySQL Database. The results of this study are that the decision support system for buying used motorcycles using the Simple Additive Weighting (SAW) algorithm can facilitate the admin or the Zakiyah Motor Bengkulu party in determining the decision to buy used motorcycles for consumers.
Hub-and-Spoke Conspiracies: Can Big Data and Pricing Algorithms Form the Rim?

A hub-and-spoke conspiracy is a metaphor used to describe an antitrust cartel that includes a firm at one level of a supply chain—such as a buyer or supplier—who acts like the “hub” of a wheel. Vertical agreements up or down the supply chain act as the “spokes,” and a horizontal agreement among the spokes acts as the “rim” of the wheel. Courts have considered hub-and-spoke conspiracies for more than eighty years, and there is large body of case law that pertains to the evidence that is necessary for proving this type of antitrust conspiracy. With the rise of modern digital technologies, firms have increased their reliance on “big data” and data-driven pricing algorithms to determine the prices for their products and services. Using big data, current pricing algorithms can quickly monitor market conditions, including the behavior of rival competitors, and adjust prices in near real-time. Analytical pricing tools that adjust prices based on supply-and-demand conditions and/or costs can create procompetitive benefits because they have the potential to increase efficiency. Anticompetitive effects can occur, however, when multiple competitors use the same pricing algorithm and data set supplied by a common service provider who acts as a hub. This article will explain the history, structure, and characteristics of hub-and-spoke conspiracies. It also will discuss agreements among competitors to exchange confidential price information, which itself can result in antitrust violations under certain circumstances. Finally, the article will summarize and comment on a new wave of antitrust lawsuits that allege hub-and-spoke conspiracies based on competitors’ mutual use of big data and algorithms to set prices.
Implementation Of The Dempster Shafer Method For The Diagnosis Of Sepsis

Sepsis is a disease that starts from infection. When an infection occurs, the body's organ systems will be damaged because when the blood flow is filled with chemical compounds produced by the body with the aim of fighting infection and triggering an inflammatory response that is damaged in the function of the body's organs, causing important organs to fail in working so that it leads to death. People often do not realize that the disease they suffer has reached the sepsis stage. Since sepsis is a rare disease and difficult to find an expert, a tool is designed to use an expert system to diagnose sepsis early from the symptoms felt by the user. This expert system was designed using the PHP Programming Language and MySQL database by implementing the Demster Shafer Method. The expert system created can make it easy for users to consult about Sepsis online..
Design and Build an Academic E-Reminder Application Using Mobile-Based Push Notification Technology

One of the activities carried out in tertiary institutions is academic activity. Academic activities are arranged in an academic calendar that is used to schedule academic activities both in the short and long term. Information on the academic calendar is usually announced on bulletin boards, social media and even distributed through online student groups. Even though academic activities are routines that are often carried out by students, with so many academic activities, it is not uncommon for some important things to be forgotten. To overcome the problems above, we need an application that can help remind these students wherever and whenever they are. One way is to take advantage of the sophistication of an Android smartphone that is equipped with a push notification feature. The results of the study show that the application can run well on an Android smartphone and notifications appear automatically according to the data entered by the application user.
Presence System Using QR Code at MAN 02 Kepahiang Web Based

MAN 02 Kepahiang is one of the schools in Kepahiang Regency which still uses a manual attendance process. In the process of teaching and learning activities students need a daily attendance process to process student attendance data which will be made as an attendance report which is one component of the assessment of the teaching and learning process. In implementing the manual attendance system carried out by students there are still deficiencies in terms of time efficiency in the process of recording attendance and preparing attendance reports for each class. In designing an attendance system using a QR Code in the form of a web base and using the PHP programming language with MySQL database processing also using the Waterfall method. This study aims to build an attendance system using the QR Code as a media for inputting student absentee data and in preparing student daily attendance reports it is made easier by having an attendance system built.
Implementation Of The Codeigniter 3 Framework For The Payment Of "Cafe Tik Tok" Employees Web-Based Bengkulu

Cafe Tik tok is a franchise engaged in the restaurant sector. In this tick tok cafe, in processing employee salaries, they still use manual calculations and use the Ms.Excel program. This can cause errors in calculating employee salaries and the process of printing employee payslips that takes a long time. In solving this problem, the authors designed an employee payroll information system. In this design, the author uses the PHP programming language, with the database format using MySQL. The result of this design is to produce an application program that will be used to process web-based employee salaries at the tiktok cafe and it is hoped that the company will find it easy to input data and compile payroll reports to be fast and more efficient.