Abstract: Laboratories are an essential part of the educational process in university faculties because of their importance in delivering scientific and applied material to students. There is great importance to the availability of safety conditions, professional staff, technical capabilities, and other laboratory requirements. Given the importance of quality in educational laboratories, the ranking of its must be done frequently. The evaluation information must be sound and available when needed. The objective of this research is to create an electronic Laboratory Quality Ranking (LabQR) program that simulates the paper evaluation process. The program converts all documents to electronic documentation and extracts the final score of the required conditions. Also, all the attached documents were saved in electronic databases, such as course certificates for employees and administrative orders. The program also provides ease of searching, retrieval, and archiving. The expansion and flexibility features have been considered in the program by adding other colleges, departments, and universities.

Abstract: Food products are an essential source of human life, so they have a very important place, and it will be important to monitor and determine their quality in a short time. Our study deals with a very important and indispensable food product, which is the milk product, which is considered the main and important element in people’s lives, especially children, because it is the main source of their growth, building their bones, and strengthening. Because it is a highly perishable product, it must be monitored and its specifications must be monitored, because any gram of milk that is of low or poor quality may cause tons of milk to spoil, and also cause major financial losses. Therefore, a study was conducted to determine the quality of dairy product through machine learning algorithms (ML), which are support vector machine (SVM) algorithm, nearest neighbors (KNN) algorithm, decision tree (DT) algorithm and Bagging algorithm using milk dataset taken from data warehouse Kaggle. This data consists of 1059 samples and seven features. The proposed models were trained and tested with the aim of finding the best and most accurate model for detecting milk quality and were evaluated using the evaluation metrics: accuracy, precision, recall, f1_score and confusion matrix. According to the evaluation results three models: SVM, KNN, and DT outperformed Bagging algorithm, as they obtained the highest level for all metrics 100%. The SVM algorithm was the most efficient because its execution time was 0.146 seconds, which was less than the other models.

Abstract: State Universities and Private Universities compete fiercely to produce quality students in line with the development of the world of education in Indonesia. Universities strive to improve quality and provide the best education to students and the number of students who graduate on time or not. In this research, a comparative test of the performance of the accuracy values of the K-Nearest Neighbor algorithm and the Support Vector Machine was carried out as a classification method for predicting the study period of students in the Bachelor of Law study program, Faculty of Law. Law, Sebelas Maret University, Surakarta, Indonesia using the RapidMiner application. In this study, a comparison of two classification methods was used, namely K-Nearest Neighbor and Support Vector Machine with 433 student data used. The data is divided into 70% training data and 30% test data. The test results for the highest K-NN prediction accuracy value were at K=5, namely 98.45%. While for the Support Vector Machine method, the accuracy value using the SVM model was 96.90%. Therefore, the results of this research are included in the good category in producing high accuracy, so that the contribution of the K-NN modeling research results using the value K=5 is getting the best accuracy compared to the SVM method using the SVM in predicting student study periods. class of 2021, Bachelor of Law study program, Faculty of Law, Sebelas Maret University.

Abstract: This research paper includes the design and implementation of a system for mining student and patient data at the College of Dentistry at the University of Mosul using the Microsoft SQL Server database management system to design and implement the database system and WEKA program for database mining, and the Microsoft Visual C# .NET 2012 language was used to program system interfaces. The main steps of the database included analysis, design and implementation, and the mining process included seven steps; data collection, data preprocessing, data exploration, data transformation, data modeling, evaluation, and deployment. The database mining process was divided into two parts; the first part is a smart cluster process for students of the Faculty of Dentistry for the fourth and fifth stages on laboratories (i.e. the number of chairs available for each laboratory) using three famous algorithms (Canopy, K-Means, EM), the second part is the process of classifying patients into four classes according to the type of treatment that each patient needs using three also famous algorithms (SVM, Naïve Bayes, Random Forest). ). After applying the system to the real data of the College of Dentistry at the University of Mosul, it was found that the best cluster algorithm is K-Means and the best classification algorithm is Naïve Bayes.

Abstract: In this research, we presented a new method for collecting data and performing calculations to obtain the required results differently from what have been studied before. In the beginning, we introduce new types of soft sets in soft topological spaces, explaining many properties such as soft ii-dense sets, soft ii-connectedness, soft ii-perfection, and soft ii-compactness. We proved that any soft set (S,E) could be soft ii-connected in (X,τ,E) when it is soft ii-connected in a soft partial sub-space ), In addition, we used the concept of soft topology in calculating the cost of service projects in several areas of the town of Bashiqa, in the Nineveh Governorate/north of Iraq, this project was achieved either in a specific region or several regions by using the theorem of soft sets in soft topological spaces. Infrastructure projects were undertaken in the areas of Bashiqa, Al-Darwish, Baibukht, and the villages of Al-Fadhiliya and Omar Qabji. Such as paving and covering various roads, building schools, and health centers, and extending groundwater networks.

Abstract: In this work, the energy levels of the ground state band (GSB), β-band and -bands for 158-160Er isotopes were calculated using the Interacting Boson Model(IBM-1), the Semi-Empirical Formula (SEF) and the New Empirical Equation (NEE). All three models were developed by IBM. In order to complete this study, the above-mentioned models and equations were applied. The results of the GSB, β-band and -bands showed that IBM-1, SEF, NEE, and the available experimental data are all in agreement with certain variations this was shown by the results of the GSB. The NEE calculations have a higher level of compatibility with the experimental data when compared to both the IBM-1 calculations and the SEF calculations. According to the findings of this research, the SEF and NEE equations are both capable of describing the energy spectra of Er isotopes in comparison to IBM-1. The electric quadrupole transition probabilities B(E2) transitions which obtained through IBM-1 for the above isotopes were calculated and found to be in agreement with the available experimental data, On the other hand, Isotopes of Er exhibit behavior that is consistent with a rotational SU(3) transition.

Abstract: Appropriate selection of features may lead to the specificity of classification methods and identify the most critical features from all sparse or dense impact data using a filter based on the recognition selection method characterized. Filtration is used to reduce sample complexity, improve the clarity of viscous samples, and reduce background signals, resulting in increased signal-to-noise ratios in analytical tests. Depending on the filtration method applied, particles are separated based on properties such as size. This study assessed the impact of filter selection and the variation in the number of projections on the final reconstructed artificial phantom images. Utilizing image reconstruction techniques, it delves into the application of mathematical transforms, including Radon and Fourier, to improve image quality and resolution, particularly in medical imaging modalities such as CT and MRI. The research predominantly focuses on the application of the Filtered Back Projection (FBP) algorithm to reconstruct images from changing numbers of projections. The results underscore the main role of filter choice in removing noise, with the Ramp filter presenting the most promising results. The investigation concludes that reducing the number of projections results in a decline in image contrast and an increase in image noise.

Abstract: Behavioral diagrams in Unified Modeling Language reflect the interaction between system components and give a comprehensive description and visualization of the system during the design phase. One of the most important behavioral diagrams is the sequence diagram which describes the chronological sequence of events between the components of the system. The process of extracting information and metrics from a sequence diagram is time-consuming so creating a special tool to help developers obtain information from the sequence diagram has become necessary because of the great advantages and ease it provides. This paper aims to build a tool that extracts information from the sequence diagram, creates a table that includes this information, and then calculates three categories of metrics related to the sequence diagram which are size, complexity, and level of detail. These categories include 15 metrics to give quantitative values that indicate software quality which is used to estimate the schedule, cost, effort, and other resources in the software development process. As a case study, the hotel reservation system is adopted and constructed as two versions of sequence diagrams for comparison purposes. The results showed a quantitative measurement of small and unnoticeable differences between the two diagrams.