Reviewerly/exHarmony huggingface dataset:
Development of Employee Payroll System using Rational Unified Process (RUP) on Odoo Platform

Payroll process mostly done manually in Indonesian companies. Manual process takes longer time than automated process. In this research, an employee payroll system was developed on the Odoo platform by implementing the Rational Unified Process (RUP) method. There are four phases in this method, the inception phase includes business process modeling activities both ongoing business processes (as-is) and proposed proposed business processes (to-be). Then from the business process needs analysis is carried out. The elaboration phase includes system design activities using use case diagrams, activity diagrams, configuration, use case scenarios, and salary rules. The construction phase includes implementation activities based on the system design in the previous phase. The results of the implementation will then be evaluated at the testing stage. In the final phase, namely the transition, the deployment or installation process is carried out to the user. The results obtained after testing the system by comparing salary calculations on Microsoft Excel and Odoo show that the total salaries of employees received are similar. The time needed to calculate an employee in Microsoft Excel is 15 minutes, while in Odoo the time needed is 6 minutes faster. In the User Acceptance Testing (UAT) test, the respondents involved were a limited circle of various departments at a sample company totaled 11 people by giving 12 statements from 3 UAT test criteria and obtained a final score of 86.97%. From the final score, the respondents accepted the developed system well.
PERSEPSI MAHASISWA TERHADAP PEMBELAJARAN BLENDED BERHUBUNGAN DENGAN PENINGKATAN HASIL BELAJAR

Nutritional counseling is an essential component of nutrition students to be equipped to address nutritional problems. The objective of the study was to analyze the correlation of nutrition students for teaching presence perception in blended learning to improve the learning outcomes of nutritional counseling stages. The study used a cross-sectional research design, nutrition students in nutritional counseling courses completed the 13-item Community of Inquiry (COI) questionnaire for teaching presence. The results showed that students had higher agreement across the level of teaching presence. The findings of this study suggest that perceived teaching presence was significantly related to improving the learning outcomes of nutritional counseling stages.
Double-Norm Constrained Image Denoising Algorithm Based on Dictionary Learning Sparsity and FCM Structure Clustering

To solve the problem of image smoothness and fuzzy edge texture information after image denoising, proposed a new image denoising method based on dictionary learning. Firstly, the external cycling principal component analysis reduces the dimensions of image data while retaining the main data and constructing the learning dictionary. Secondly, used the fuzzy c-means structure clustering method internally to implement structural constraints on learning dictionary training, which considered the internal structure of image pixels. Then, the learning dictionary under the double constraints of sparse and structural clustering is obtained by internal and external iteration. Finally, the sparse representation coefficient and redundancy dictionary are obtained by the orthogonal matching pursuit method and alternate direction multiplier method, and the denoised images are estimated and updated according to sparse coding theory. Using the grayscale image from Set12 data set, color image from the CBSD68 data set, real noise from RENOIR data set, and texture image from USC-SIPI data set. The experimental results show that compared with the model-based algorithms (KSVD, ISKR, EPLL, NCSR, and LR-GSC) and the learning-based algorithms(DnCNN, IRCNN, and FFDNet), the proposed algorithm preserves the edge and texture information of the image better, and achieves better subjective visual effects and objective numerical results, especially for the image with complex structure and content, and the running time is much less than learning-based algorithms.
Model Theory

This textbook gives a complete and modern introduction to mathematical logic. The author uses contemporary notation, conventions, and perspectives throughout, and emphasizes interactions with the rest of mathematics. In addition to covering the basic concepts of mathematical logic and the fundamental material on completeness, compactness, and incompleteness, it devotes significant space to thorough introductions to the pillars of the modern subject: model theory, set theory, and computability. Requiring only a modest background of undergraduate mathematics, the text can be readily adapted for a variety of one- or two-semester courses at the upper-undergraduate or beginning-graduate level. Numerous examples reinforce the key ideas and illustrate their applications, and a wealth of classroom-tested exercises serve to consolidate readers' understanding. Comprehensive and engaging, this book offers a fresh approach to this enduringly fascinating and important subject.
Improving Wireless Devices Identification Using Deep Learning Algorithm

Most existing security techniques could be severely affected by the dynamic changes in the communication links used. To circumvent this problem, an authentication algorithm is proposed through the use of Long Short Term Memory (LSTM) network. The authentication accuracy of the proposed security model is showed. Extensive results show that our scheme significantly reduces the impact of time-varying wireless environment on the identification of malicious attackers.
MANAJEMEN SISTEM PENERIMAAN PESERTA DIDIK BARU ONLINE DI SMA NEGERI 1 PONTIANAK

New student admissions (PPDB) for SMA Pontianak City still found problems in the implementation process, including: errors in the registration path, the zoning system, regional differences, website registration errors, invalid distances. This research uses a qualitative approach with case studies. The purpose of the study was to describe the planning, implementation, and evaluation of the recruitment, selection, and online new student admissions system at SMA Negeri 1 Pontianak. The research subjects were 4 people, aged 37-55 years, 1 male and 3 female, namely: the principal of SMA Negeri 1 Pontianak, the vice principal for student affairs, the executive committee, and parents of students. Interviewing, documenting, and observing are all methods used to collect data. The main findings of the study show the following: 1) planning through the determination of the RKS, the work program of the vice principal for student affairs, the determination of the PPDB committee decree, the use of online PPDB technical guidelines, 2) the implementation begins with prospective students creating accounts in the ready-to-busy application through the ppdb.dikbud page. kalbarprov.go.id, the school committee verifies the data, processes the data in the application and announces it, re-registers new students, 3) to overcome obstacles when PPDB is online the committee coordinates with the operators of the Provincial Education Office, and provides understanding to students' parents. The conclusion of online PPDB at SMA Negeri 1 Pontianak is in accordance with the online PPDB technical guidelines in 2021 and the implementation of online PPDB stages with management principles.
Effectively Incorporating Weighted Cost-to-go Heuristic in Suboptimal CBS (Extended Abstract)

Conflict-Based Search (CBS) is a popular multi-agent path finding (MAPF) solver that employs a low-level single agent planner and a high-level constraint tree to resolve conflicts. The majority of modern MAPF solvers focus on improving CBS by reducing the size of this tree through various strategies with few methods modifying the low level planner. All low level planners in existing CBS methods use an unweighted cost-to-go heuristic, with suboptimal CBS methods also using a conflict heuristic to help the high level search. Contrary to prevailing beliefs, we show that the cost-to-go heuristic can be used significantly more effectively by weighting it in a specific manner alongside the conflict heuristic. We introduce two variants of doing so and demonstrate that this change can lead to 2-100x speedups in certain scenarios. Additionally, we show the first theoretical relation of prioritized planning and bounded suboptimal CBS and demonstrate that our methods are their natural generalization.
Care Assistance and Abnormal Activity Warning System by Bluetooth Positioning

At present, the domestic demand for long-term care is growing rapidly. However, the replenishment of related services has been slow. This leads to an imbalance in the proportion of nursing staff. The result was a shortage of manpower and a hectic work schedule. If there is a system to assist caregivers in their daily work processes, the burden on caregivers reduces. The constructed system in this research has the functions of Bluetooth indoor positioning, abnormal state judgment, early warning with processing flow control, active reminder, and recording of nursing work. Indoor positioning is used to instantly locate the elderly, know their activity statuses, and determine whether the activity is abnormal. In the event of possible abnormal conditions, active and passive alerts are issued. Through the combination of software and hardware, the processing flow is controlled to achieve the optimal allocation of manpower. In addition, proactively reminding the attendant and recording the care items before carrying out the care needs are conducted to avoid omission or duplication of care items.
SYSTEM MODELING OF SOFT SKILLS AS A CONDITION FOR COOPERATION OF YOUNG PEOPLE OF DIFFERENT COUNTRIES

Introduction. The paper examines specific features of the system modeling of soft skills as a condition for constructive international cooperation of young people. Consideration is also given to pedagogical technologies and methods for building this type of skills. The study aims to identify the principles of and conditions for creating a digital and creative environment in which the future specialist will develop soft skills in the main disciplines of the basic level of training in the system of higher education. Materials and methods. The object of the study is the student community. Modern and relevant pedagogical technologies and methods that influence the formation of soft skills necessary for the international student cooperation were considered as effective tools for the system modeling of these skills. The study employs general scientific methods (analysis, synthesis, comparison) and dedicated research methods (the system-structural analysis and the method of pedagogical observation). The results of the study. Intermediate findings have identified the conditions for successful system modeling of soft skills in students. They have provided the understanding of the specifics of joint interaction and problem solving in the field of scientific integration, demonstrated the effectiveness of soft skills, because they make it possible to build constructive communication, to communicate, and show understanding. The identified block of specific soft skills included the skills such as empathy, self-management, self-learning, feedback through communication and mentworking. Conclusion. The technologies and methods proposed in the paper can be used in the process of generating a creative environment for building soft skills in students, i.e., system modeling. The use of the identified tools will allow creating a single educational space, stimulating international cooperation of students, and developing a mentoring system.
BUILDING VOCABULARY THROUGH SONG AS EFFECTIVE METHOD IN LEARNING ENGLISH

Abstract: This study aims to determine the effectiveness of songs in learning English vocabulary through quasi experiment method. The population is 287 students and used random sampling obtained for experimental class and control class. The research data gained is from English vocabulary test. Based on the instrument test, 10 items were valid and reliability was 0 ,346. Data analysis using application SPSS 23for windows.The results showed that the value of taccount 2.558 was highest than ttable 2.021 with a significance level (α) = 0.05 with db = 40. This shows that the value of taccount (th) was highest than ttable (tt) which means there was a significant difference in vocabulary learning between the experimental class and the control class.The average final score of the experimental class was 22.85, higher than the control class was 18.92. It could be concluded that the use of song media for learning English vocabulary is effective.&#x0D; &#x0D;
IMPROVING THE STUDENTS’ SPEAKING ABILITY USING ROLEPLAY AT 11th GRADE OF SMAN 12 MUARA BUNGO

This Classroom Action Research (CAR) was conducted to improve the students’ speaking ability using the roleplay. It was conducted at SMA N 12 Muara Bungo which involved the 11th grade students as the objects. The reseach found that using role play technique in teaching speaking was success to improve the students’ speaking skill. The criterion of action success is 75% of students could achieve the target score of the minimal mastery level criteria or KKM of English lesson was 76 (seventy six). At the beginning, there were 10 students or 35,71% of students in the class who achieved the standard criterion or KKM in pretest. And then, It was increased in the first cycle, there were 16 or 57,14% of students who achieved the standard criterion or KKM. In cycle 2, there were 24 or 85,71% students in the class who achieved the standard score (KKM). Not only that, based on the observation result showed that the students were braver and more confident in speaking, it is proved that the response of the students toward their interest in learning speaking using role play technique were 75.00% and 80.00% that means it falls into the good and very good category.
Extractive Multi-document Text Summarization Leveraging Hybrid Semantic Similarity Measures

Because of the massive amount of textual information accessible today, automated extraction text summarization is one of the most extensively used ways to organize the information.The summarization mechanisms help to extract the important topics of data from a given set of documents.Extractive summarization is one method for providing a representative summary of a text by choosing the most pertinent sentences from the original text.Extractive multidocument text summarization systems' primary goal is to decrease the quantity of textual information in a document collection by concentrating on the most crucial subjects and removing irrelevant material.In the previous research, there are several methods such as term-weighting schemes and similarity metrics used for constructing an automated summary system.There are few studies that look at the performance of combining various Semantic similarity and word weighting techniques in automatic text summarization.We evaluated numerous semantic similarity metrics in extractive multi-document text summarization in this research.In the extractive multi-document text summarization discussed in this research, we looked at numerous semantic similarity metrics.ROUGE metrics have been used to evaluate the model performance in experiments using DUC datasets.Even more, the combination formed by different semantic similarity measures obtained the highest results in comparison with the other models.
ANALYZING THE CONCEPT OF SELF-ACTUALITATION IN FREEDOM WRITERS MOVIE

This research analyze the concept of self-actualitation in “The Freedom Writers” movie based on the humanistic approach perceived by Carl Rogers. This study aims to determine the process of developing the self-actualization of one characters in the film “The Freedom Writers” named Eva and how it impacts her social life as a student. The writer used psychological literature for the approach of research. The data used in this paper is a movie entitled “The Freedom Writers” by Richard LaGravenese. This film is adapted from a novel entitled “The Freedom Writers Diary” by Erin Gruwell which is written based on a true story. The result of this paper is showing the self-actualization from Eva Benitez’s character and its provide from the uneducated girl to became one of the diary writer.
Design of a Speaking Training System for English Speech Education using Speech Recognition Technology

A good English speaking training system can provide an aid to the learning of English.This paper briefly introduced the English speaking training system and described the speaking training scoring and pronunciation resonance peak display modules in the system.The speaking training scoring module scored pronunciation with the Long Short-Term Memory (LSTM).The pronunciation resonance peak display module extracted the resonance peak with Fourier transform and visualized it.Finally, the speaking scoring module, the pronunciation resonance peak display module, and the effect of the whole system in improving students' speaking pronunciation was tested.The results showed that the LSTM-based speaking scoring algorithm had highest scoring accuracy than pattern matching and the recurrent neural network (RNN) algorithm, and its accuracy was 95.21% when scoring the LibriSpeech dataset and 90.12% when scoring the local English dataset.The pronunciation resonance peak display module displayed the change of mouth shape before and after training, and the pronunciation after training was closer to the standard pronunciation.The P value in the comparison of the speaking level before and after training with the system was 0.001, i.e., the difference was significant, which indicated that the students' English speaking proficiency significantly improved.
Experimental demonstration on quantum coherence evolution of two-mode squeezed state

As one of the most remarkable features of quantum mechanics, quantum coherence is regarded as an important quantum resource in the quantum information processing. The one-mode squeezed state and the two-mode squeezed state (Einstein-Podolsky-Rosen (EPR) entangled states) as the most representative examples of nonclassical states both have quantum coherence. The squeezing property of the squeezed state is described by the variance of quadrature components, and the positive partial transposition (PPT) criterion is used to describe the entanglement of the EPR entangled states. The research of the quantum coherence of Gaussian states is also a bridge between the properties of squeezing and entanglement. It has been shown that the quantum coherence with infinite-dimensional systems can be quantified by relative entropy. One of the widely used effective methods to obtain the value of quantum coherence experimentally is the quantum tomography. The covariance matrices of the quantum states are reconstructed via balanced homodyne detection and then taken into quantum coherence expression to calculate the corresponding value. The main factors affecting quantum coherence are the classical and uncorrelated noise in the actual experimental generation processing and the decoherence effect caused by the coupling between quantum resources and the surrounding environment. And the quantum coherence evolution in the generation and transmission process of the quantum resources is essential for the practical applications. Therefore, we analyze in detail the influences of the impurity of quantum resource on squeezing, entanglement and quantum coherence. The evolutions of quantum coherence of these Gaussian states in the lossy channels are demonstrated experimentally. The quantum coherence is shown to be robust against the loss in the lossy channels, which is similar to the case of squeezing and entanglement. The quantum coherences of the squeezed states and the EPR entangled states are robust against the thermal photons in the actual experimental generation processing, although the squeezing and entanglement of Gaussian states disappear at a certain number of thermal photons. Our research results provide a reference for the practical applications of quantum coherence of the squeezed state and entangled states in the lossy environment.
The Effectiveness of using Infographics as an Aid for Reading Comprehension

The Malaysian education system highly regards the English language that the language is being taught in both primary and secondary schools for 11 years long. However, the Malaysian pupils seem to have not acquired the reading skills good enough. Therefore, the pupils need to have a support system that would enable them to make a better connection with their reading materials especially English reading materials and to lessen the cognitive load that they experience during their reading session. The purpose of this action research is to determine the effectiveness of using infographics to enhance reading comprehension among primary school pupils with average and weak English language proficiency. Sixteen Year 5 pupils from a semi-urban primary school at Pahang, Malaysia were chosen as its research participants. This study was inspired by the theory of Multimedia Learning by Richard E. Meyer. The data of this research was collected through tests; before the intervention and after the intervention. The data were collected from the test and were analyzed. The finding of this research shows that there is a significant improvement in the mean score from the pre-test to the post-test. The pupils were able to comprehend the text better through the intervention.
Mapping the Security Events to the MITRE ATT &amp;CK Attack Patterns to Forecast Attack Propagation (Extended Abstract)

Modern information systems generate a lot of events. Analysis of the events allows detecting malicious activity within the system. There are a lot of event correlation techniques intended for the detection of cyber security incidents and different types of cyber attacks, as well as there are a lot of techniques for multi-step attack modeling. At the same time, most modern security event management solutions do not allow mapping the detected security incidents to the specific stage of the targeted multi-step cyber attack, forecasting the next steps of the cyber attack, and selecting the proactive responses automatically. In this paper the technique to map the detected incidents to the stages of the targeted cyber attacks is proposed. The technique is based on the set of correlation rules “Emerging Threats” for events correlation to get cyber security incidents and on the set of “Targeted Attack Analyzer (Indicators Of Attack)” rules describing security incidents (signatures) using Sigma language and integrated with the MITRE ATT &CK database. The developed technique allows mapping the events detected in the system under analysis to the MITRE ATT &CK attack patterns and in prospect forecasting the targeted cyber attack development and automatically responding against the detected cyber security incidents. The technique is implemented using Python language and tested to demonstrate mapping of the detected incidents to the known attack patterns using the deployed test environment.