Reviewerly/exHarmony huggingface dataset:
PERANCANGAN DAN PEMBANGUNAN ATAP HALAMAN MASJID AL ASEL, PERUMAHAN KANOMAN, BANYURADEN, GAMPING, SLEMAN, DIY

Al Asel Mosque is one of the mosques in Banyumeneng Hamlet, Banyuraden, Gamping, Sleman, DIY, which was established in 1985. Over time the number of worshipers has increased. The current size of the mosque is no longer sufficient to accommodate people who want to worship, especially Friday prayers and Tarawih prayers in the month of Ramadhan, so that they often spill out to the courtyard of the mosque. Problems arise when it starts to enter the rainy season. The mosque yard covering an area of 12x12 m2 which has been covered by concrete block and marked for prayer can not be used anymore. As a result, prayers had to crowd within the mosque and on the porch, even forced to pray on the terrace of the kindergarten room. This of course reduces the solemnity during worship. The committee of Al Asel Mosque planned to build a roof of the mosque courtyard so that the prayers can pray on the courtyard during rain. The purpose of this activity is to help the committee of Al Asel Mosque realize the roof structure of the mosque's yard covering an area of 12x12m2. The method of activities carried out include designing the roof structure and supervision during the construction process in a few weeks. The design process produced documents consisting of design drawings and budget plans. After the completion of the mosque roof construction, the capacity of pilgrims increased and it is expected that prayers would be more solemn during worship.
Exploring Impact of Requirements Engineering on Other IT Project Areas – Case Study

Requirements Engineering (RE) is recognized as one of the most important (yet difficult) areas of software engineering that has a significant impact on other areas of IT projects and their final outcomes. Empirical studies investigating this impact are hard to conduct, mainly due to the great effort required. It is thus difficult for both researchers and industry practitioners to make evidence-based evaluations about how decisions about RE practices translate into requirement quality and influence other project areas. We propose an idea of a lightweight approach utilizing widely-used tools to enable such an evaluation without extensive effort. This is illustrated with a pilot study where the data from six industrial projects from a single organization were analyzed and three metrics regarding the requirement quality, rework effort, and testing were used to demonstrate the impact of different RE techniques. We also discuss the factors that are important for enabling the broader adoption of the proposed approach.
Extraction of Food Product and Shop Names from Blog Articles Using Named Entity Recognition

Named Entity Recognition (NER) is an important research topic in natural language processing, and has been widely studied for a long time. Recently, NER models using neural networks have been proposed, and have achieved the high performance for formal texts written in English such as the dataset of CoNLL2003. We are currently developing a system that provides useful information about food souvenirs that can be purchased only at the particular location or area (called the local limited food souvenirs). Therefore, it is important to apply an efficient NER method to extract food souvenirs and shop names as named entities from noisy user-generated texts written in Japanese such as texts of blog, Q&A, and online review sites. However, most of the existing NER methods using neural networks have not been evaluated with noisy user-generated texts or texts in languages other than English. In this paper, we propose a Conditional Random Fields-based model and compare the performance of the proposed CRF model and the existing state-of-the-art models using neural networks on a dataset constructed by blog texts written in Japanese. From the experimental results, it turned out that a simple neural network model with part-of-speech embeddings for NER has shown the best performance for named entities that were not included in the training data, and the proposed CRF model has shown the best precision in our task.
Bayesian forward modeling of galaxy clustering

With the future large-scale structure (LSS) surveys being on the horizon, precision cosmology is seeing a unprecedented opportunity to constrain cosmological parameters and differentiate cosmological models. Such opportunities naturally bring also unparalleled challenges -- specifically in the form of understanding, examining and, especially, combining various datasets.Bayesian forward modeling and inference, in this context, provides a consistent and transparent framework to extract information from separate datasets while accounting for multiple systematic sources.This thesis is a dedicated effort to bring this framework one step closer to being ready for the upcoming challenges posed by high-precision Cosmic Microwave Background (CMB) experiments and large-volume galaxy redshift surveys. We systematically examine the constraining power of the Bayesian forward modeling approach to galaxy clustering on both cosmological and astrophysical observables, namely the initial conditions of our Universe, the clustering amplitude of galaxies and the kinematic Sunyaev-Zel'dovich (kSZ) effects of galaxy clusters. While the first two focus only on halo clustering in N-body simulation, the last one brings together observational datasets from separate experiments and surveys: the Planck CMB experiment, the Sloan Digital Sky survey (SDSS) and the maxBCG cluster catalog, which include both common and different sources of systematics.We find in chapter 5 that the Bayesian forward inference approach is able to, on large scales, recover up to ~90% the input initial conditions of the GADGET-2 simulation using halos identified in the same simulation as tracers. The framework is robust regarding to choices of gravitational forward model for the matter density fields and deterministic bias model for tracers. The LSS likelihood, on the other hand, might play an important role for unbiased inference of not only the initial conditions, but also the cosmological parameters. This is demonstrated in chapter 7, where we are able to recover the input $\sigma_8$ of the same simulation with systematic error under ~10%, using a Fourier-space likelihood derived from the effective field theory (EFT) approach to LSS with rigorously controlled theoretical systematics.In chapter 6, we use results from the Bayesian forward reconstruction of the BOSS/SDSS3 volume to measure the large-scale bulk flow and kSZ signal of maxBCG catalog. We find evidence of the kSZ effect at approximately 2-sigma, consistently in individual- as well as multi-scale measurements. Our reported signal-to-noise is the first to include uncertainties from the velocity reconstruction in this type of measurement.
JOHNSONS ALGORITHM IN FUZZY ENVIRONMENT

Adv. Math. Sci. J. Vol. 9, No. 4 Open Access JOHNSONS ALGORITHM IN FUZZY ENVIRONMENT K. K. Mishra DOI: https://doi.org/10.37418/amsj.9.4.94 Full Text Abstract Abstract Classical Johnson algorithm is extended to find fuzzy number job sequencing problem. The processing time is represented by trapezoidal fuzzy number. The trapezoidal fuzzy numbers are defuzzified by … page AMSJ9-N4-94 Read More »
Analysis of the Construction Path of Low-carbon City in Fuzhou

Abstract With global warming and urban pollution becoming more serious, high energy-consuming and polluting industries have also brought about a large number of carbon emissions and environmental pollution problems when solving employment and promoting economic growth. How to resolve the conflict between economic development and environmental protection is already an unavoidable economic and social issue. And building a low-carbon city can not only achieve sustainable economic development, but also meet the needs of people for a better life. This paper takes Fuzhou as the research object, firstly introduces the achievements made by Fuzhou in the process of building a low-carbon city in recent years; then it analyzes its remaining problems; and finally puts forward countermeasures and suggestions.
Discrete Cosine Transformation based Image Data Compression Considering Image Restoration

Discrete Cosine Transformation (DCT) based image data compression considering image restoration is proposed.An image data compression method based on the compression (DCT) featuring an image restoration method is proposed.DCT image compression is widely used and has four major image defects.In order to reduce the noise and distortions, the proposed method expresses a set of parameters for the assumed distortion model based on an image restoration method.The results from the experiment with Landsat TM (Thematic Mapper) data of Saga show a good image compression performance of compression factor and image quality, namely, the proposed method achieved 25% of improvement of the compression factor compared to the existing method of DCT with almost comparable image quality between both methods.
Error correction techniques in the context of teaching an esp course at a technical university

The article studies the practice of applying various correction methods in the process of teaching English to future specialists in the field of information technology at a technological university.The study, conducted in the form of a questionnaire survey of students' opinions concerning their attitude to error correction is aimed at drawing attention to this issue; increasing participants' awareness of the existing correction methods; identifying the differences in teachers' approach to correcting students' oral mistakes and finding the most "working" methods in a particular learning context.The target competence of future IT specialists is the ability to communicate in oral and written forms in a foreign language, to solve problems of interpersonal and intercultural interaction, speak a foreign language at the level of social and professional communication, to be able to use special vocabulary and professional terminology.In the authors` teaching context the individualized approach is of particular importance.It means varying the level of complexity of materials and evaluation criteria and approaches to correcting errors.Based on the results of the study and the teaching situation we focus on the following methods to correct mistakes in the students' speech: immediate correction; self-evaluation or self-correction ; the task repetition method and the teacher's positive feedback.
A COMPARISON OF CLUSTERING BY IMPUTATION AND SPECIAL CLUSTERING ALGORITHMS ON THE REAL INCOMPLETE DATA

The existence of missing values will really inhibit process of clustering. To overcome it, some of scientists have found several solutions. Both of them are imputation and special clustering algorithms. This paper compared the results of clustering by using them in incomplete data. K-means algorithms was utilized in the imputation data. The algorithms used were distribution free multiple imputation (DFMI), Gabriel eigen (GE), expectation maximization-singular value decomposition (EM-SVD), biplot imputation (BI), four algorithms of modified fuzzy c-means (FCM), k-means soft constraints (KSC), distance estimation strategy fuzzy c-means (DESFCM), k-means soft constraints imputed-observed (KSC-IO). The data used were the 2018 environmental performance index (EPI) and the simulation data. The optimal clustering on the 2018 EPI data would be chosen based on Silhouette index, where previously, it had been tested its capability in simulation dataset. The results showed that Silhouette index have the good capability to validate the clustering results in the incomplete dataset and the optimal clustering in the 2018 EPI dataset was obtained by k-means using BI where the silhouette index and time complexity were 0.613 and 0.063 respectively. Based on the results, k-means by using BI is suggested processing clustering analysis in the 2018 EPI dataset.
On stability of delayed differential systems of arbitrary non-integer order

This paper summarizes and extends known results on qualitative behavior of solutions of autonomous fractional differential systems with a time delay.It utilizes two most common definitions of fractional derivative, Riemann-Liouville and Caputo one, for which optimal stability conditions are formulated via position of eigenvalues in the complex plane.Our approach covers differential systems of any non-integer orders of the derivative.The differences in stability and asymptotic properties of solutions induced by the type of derivative are pointed out as well.MSC (2010)
Scientific and methodical provision of profile technologies training in high school

The article emphasizes the importance of profile training of engineering technologies and development of appropriate educational and methodological support in the form of special courses (elective courses) in technology. Systematization and generalization of the scientific research results of a number of topics (senior profile school) have been carried out in the department of technological education of the Institute of Pedagogy of the National Academy of Pedagogical Sciences of Ukraine with the purpose of systematic use of theoretical developments (conceptual and theoretical and methodological foundations, models; formulated hypotheses, innovations, ideas; developed methods, approaches, etc.) in the process of designing effective content of special courses for profile technology training. The results obtained formed the scientific and theoretical basis for the design of the textbook content for the special course of engineering and technical orientation «Designing and construction of engineering objects». The importance of the special course content for the formation of project-technological competence, creative technical potential, providing pupils with a conscious choice of their future professional activity of engineering and technical orientation has been substantiated. The role of the wide-ranging methodological apparatus of the manual has been highlighted for the effective realization of the special course content «Designing and construction of engineering objects» in the educational process of the high school and the tasks fulfillment of profile technologies training according to its content.
DCT versus DWT Chaotic based Color Image Encryption

Over the years, large amount of transferred information has been attacked by hackers; so it has been considerable to make all effort for securing data and encrypting the information.Color images represent a very vital and important type of multimedia; so many encryption techniques have been proposed to protect the color image against different types of attacks.In this paper two proposed techniques will be introduced which have had high robustness against complex composite form of attacks.Discrete Wavelet Transform (DWT) has been applied for image transformation in one method and Discrete Cosine Transform (DCT) has been applied in the other one.Six various chaotic maps have been used with different parameters to introduce the needed encryption keys for the proposed approaches.After many extensive comparisons with other traditional techniques it has been found that the proposed algorithms have given better performance against both friendly and hard forms of complex composite attacks.
A Traffic Anomaly Detection Method Based on Gravity Theory and LOF

In order to solve the problem that the traditional method cannot detect the anomaly well, we propose a new traffic anomaly detection method based on the theory of gravity and local outlier factor (LOF) in this paper. We improve the density peak clustering method based on the theory of gravity firstly. A new concept of potential energy is proposed, and a new potential energy–distance decision graph is used for clustering and anomaly detection. Considering the local characteristics of the sample points, we propose the concept of potential energy gradient with reference to LOF for further anomaly detection to improve the accuracy of detection. The simulation results show that the proposed method can detect more types of outliers and get more accurate results. The improved anomaly detection method has good anomaly detection performance.
Cryptography with Layered Algorithms for Text Security on Android

Android phone is one of the most widely used telecommunications devices today. The exchange of various forms of information ranging from text, sound, images and video through this media is inseparable from the threat of criminal crime through digital data theft. Data security aspects are very important to be considered, one of which is data in the form of text. Text data is commonly used in short message services (SMS), chat in various Android applications or in the use of logins and passwords. This research will create an application on Android for securing text data through cryptographic techniques with a layered algorithm using three types of algorithms namely Caesar, Blowfish and AES Algorithms (Advanced Standard Encryption). This application can run on Android 5.0 (lollipop) or above, which can be used to encrypt and decrypt text messages. The test results show that the results of the initial text that was encoded through the encryption process can be safely returned by the decryption process without the slightest mistake with the original text. The encryption test for capital letters, numbers, and punctuation can be completely decrypted.
Peningkatan Pemahaman Konsep Mahasiswa pada Teori Bahasa dan Automata Melalui Strategi MURDER

This study aims to describe the improvement of student’s conceptual understanding in Language and Automata theory through MURDER strategy. The population of this study were students of STMIK Tunas Bangsa in academic year 2019/2020 who studied the course of Language and Automata theory. Sample randomly choosed from students who have low mathematical abilities. Data were collected through conceptual understanding test instrument in essay form. Based on data analyzed using Wilcoxon test at 5% significant level, it was concluded that MURDER strategy improved student’s conceptual understanding in low category. DOI: http://dx.doi.org/10.23960/mtk/v8i2.pp100-109
Pemilihan Karyawan Terbaik Menggunakan Metode Simple Additive Weighting (SAW) pada Perusahaan Investasi Emas

In the assessment for the determination of the best employee is still done manually, and the lack of determination for the best employee. This study aims to build a decision support system for determining the best employees in accordance with what is expected by the company. The method used in this study is Simple Additive Weighting (SAW) with the provisions of predetermined criteria, namely, order, discipline, absenteeism, cooperation, creativity. This system was developed with the PHP programming language and also uses MySQL. From the results obtained manually accuracy with a percentage of 60%, While the results obtained from the accuracy of using the system reached 73.33%, namely the output of the system is able to choose one of the best employees. So, it can be concluded that this research can be used as a tool to determine the best employees so that the level of employee productivity can be better and can be beneficial for the company.
Developing English Learning Materials For Food And Beverage Service in Singaraja Hotel School

This research aimed at developing English learning material for food and beverage service in Singaraja Hotel School for D1 program. The research design followed 4D model. The steps of this study were: (1) Define,(2) Design, (3)Develop, and (3)Disseminate. There were two questionnaires employed in the research: (1) Needs analysis questionnaire (2) Expert judgment questionnaire. The materials needed are the English learning materials consisted of various activities and example for food and beverage service course. The activities of the materials were in the form of dialogues, detail explanation, illustration, and additional information related to food and beverage service course. Based on the data process, it was found that the score of the product quality was 256. Based on the criteria made, it can be concluded that the quality of the product was categorized asgood material. It means that the materials can be used in learning process.
The exploratory status of postconnectionist models

This paper aims to offer a new view of the role of connectionist models in the study of human cognition through the conceptualization of the history of connectionism - from the simplest perceptrons to convolutional neural nets based on deep learning techniques, as well as through the interpretation of criticism coming from symbolic cognitive science. Namely, the connectionist approach in cognitive science was the target of sharp criticism from the symbolists, which on several occasions caused its marginalization and almost complete abandonment of its assumptions in the study of cognition. Criticisms have mostly pointed to its explanatory inadequacy as a theory of cognition or to its biological implausibility as a theory of implementation, and critics often focused on specific shortcomings of some connectionist models and argued that they apply on connectionism in general. In this paper we want to show that both types of critique are based on the assumption that the only valid explanations in cognitive science are instances of homuncular functionalism and that by removing this assumption and by adopting an alternative methodology - exploratory mechanistic strategy, we can reject most objections to connectionism as irrelevant, explain the progress of connectionist models despite their shortcomings and sketch the trajectory of their future development. By adopting mechanistic explanations and by criticizing functionalism, we will reject the objections of explanatory inadequacy, by characterizing connectionist models as generic rather than concrete mechanisms, we will reject the objections of biological implausibility, and by attributing the exploratory character to connectionist models we will show that practice of generalizing current to general failures of connectionism is unjustified.
Evolution of the Library Space and Information and Communication Infrastructure of the KNUCaA Scientific Library

Review for the publication: Scientific Library of the Kyiv National University of Culture and Arts: Times of Change and Augmented Reality: to the 55th University Foundation Anniversary / Yu.Horban, O. Skachenko. Kyiv: Kyiv, Publishing House: Lira-K, 2019. 264 p.
Validity of Android Based Mobile Learning Media in Computer and Based Network Vocational High School

The purpose of this research is to produce a valid android based mobile learning media that is suitable for learning in Computer and Based Network subjects. This android based mobile learning media is designed to increase student interest in learning, to improve student understanding about learning material and also to improve learning outcomes. This is a Research and Development (R&amp;D) with 4-D model (Define, Design, Develop, Disseminate). In this study is limited to the development stage, is to know the validity of the mobile learning media from material and media experts. Data analysis techniques is descriptive analysis techniques to describe the validity of the android based mobile learning media. Media validity is measured through a validated instruments that has been previously validated. The validity results from this research are android based mobile learning media declared valid in terms of media aspects and material aspects. Based on the results of this validity, it is concluded that the android based mobile learning media was declared valid for use as Computer and Based Network learning media.