1,286 research outputs found
Development and experimental study of an intelligent water quality monitoring system based on the internet of things
No full textThe goal of this work is to create an intelligent internet of things (IoT)-based water quality monitoring system that will effectively monitor and analyze water parameters, collect real-time data, and provide critical information for decision-making in water management and environmental issues. Provide data transfer over wireless networks such as Wi-Fi or Bluetooth. The scientific novelty of the project lies in the development of an innovative system that combines modern IoT technologies and machine learning methods to provide comprehensive and accurate water quality monitoring, which is a significant contribution to water management and environmental safety. Five sensors are connected to Arduino-Mega 2560, ESP-32-E in a discrete manner to determine water parameters. The extracted sensor data is transferred to a desktop application developed on the Blynk App platform and compared with World Health Organization (WHO) standard values. Based on the measurement results, the proposed system can successfully analyze water parameters using the fast forest binary classifier to determine whether the tested water sample is potable or not. An intuitive user interface has been created that will allow users to monitor and analyze water quality data in real time. Provide the ability to create graphs, charts, and reports for visual presentation of data
Analisis Kepuasan Pengguna E-Learning pada Universitas Pembangunan Nasional Veteran Jawa Timur Menggunakan Model Kano
No full textE-learning is a distance learning method without having to meet face to face. Because in conventional learning there are often problems with limited time, distance, and costs, particurally due to the current pandemic. UPN Veteran Jawa Timur has implemented the e-learning information system in teaching and learning activities. The involvement of users in accessing the web utilizing information system technology will determine the success of the quality of the system and information applied. The researcher conducted a literature study related to the research. Among them are E-learning, Kano Model, and quantitative research methods. Respondent data were collected using the "Simple Random Sampling" method. Data collection was carried out in this study by indirectly distributing questionnaires. The attributes of the questionnaire were identified using the Kano method to determine the level of user satisfaction with the E-learning system at UPN Veteran Jawa Timur. In this research questionnaire, there are 29 attribute questions with the results of 7 attributes that according to respondents are satisfactory, and 14 attributes according to respondents including dissatisfaction. It was found that the one-dimensional category was still included in the dissatisfaction quadrant where this category greatly influenced user satisfaction. The suggestions that the author can suggest are to pay attention to the attributes that fall into the one-dimensional and must-be categories, especially for the high value of dissatisfaction. For a high satisfaction value, the author suggests that it should be maintained, and it is better if these attributes are developed by paying attention to user satisfaction
Using Machine Learning Algorithm for Diagnosis of Stomach Disorders
No full textMedicine is one of the rich sources of data, generating and storing massive data, begin from description of clinical symptoms and end by different types of biochemical data and images from devices. Manual search and detecting biomedical patterns is complicated task from massive data. Data mining can improve the process of detecting patterns. Stomach disorders are the most common disorders that affect over 60% of the human population. In this work, the classification performance of four non-linear supervised learning algorithms i.e. Logit, K-Nearest Neighbour, XGBoost and LightGBM for five types of stomach disorders are compared and discussed. The objectives of this research are to find trends of using or improvements of machine learning algorithms for detecting symptoms of stomach disorders, to research problems of using machine learning algorithms for detecting stomach disorders. Bayesian optimization is considered to find optimal hyperparameters in the algorithms, which is faster than the grid search method. Results of the research show algorithms that base on gradient boosting technique (XGBoost and LightGBM) gets better accuracy more 95% on the test dataset. For diagnostic and confirmation of diseases need to improve accuracy, in the article, we propose to use optimization methods for accuracy improvement with using machine learning algorithms
SISTEM INFORMASI PENGELOLAHAN DATA BERBASIS WEB DI DINAS TENAGA KERJA DAN TRASMIGRASI PROVINSI JAWA TIMUR
No full textAn information system is a people’s made system that generally consists of a set of computer-based components and manuals that are created to collect, store and manage data and provide output information to users. With the development of technology makes people think to be able to work more effectively and efficiently. One of them is making a conventional system into a computerized system.
In this research, a web-based data management information system is designed which is expected to be able to overcome the various needs to manage data so that it becomes effective and more efficient. From the results of research that has been carried out the author implements the results of the research into the Information System Design for managing data from the Office of Manpower and Transmigration of East Java Province
A Comparison of Machine Learning Algorithms in Predicting Lithofacies: Case Studies from Norway and Kazakhstan
No full textDefining distinctive areas of the physical properties of rocks plays an important role in reservoir evaluation and hydrocarbon production as core data are challenging to obtain from all wells. In this work, we study the evaluation of lithofacies values using the machine learning algorithms in the determination of classification from various well log data of Kazakhstan and Norway. We also use the wavelet-transformed data in machine learning algorithms to identify geological properties from the well log data. Numerical results are presented for the multiple oil and gas reservoir data which contain more than 90 released wells from Norway and 10 wells from the Kazakhstan field. We have compared the the machine learning algorithms including KNN, Decision Tree, Random Forest, XGBoost, and LightGBM. The evaluation of the model score is conducted by using metrics such as accuracy, Hamming loss, and penalty matrix. In addition, the influence of the dataset features on the prediction is investigated using the machine learning algorithms. The result of research shows that the Random Forest model has the best score among considered algorithms. In addition, the results are consistent with outcome of the SHapley Additive exPlanations (SHAP) framework
Dynamic Simulation of a Solar Hot Water Heating System for Kazakhstan Climate Conditions
No full textKRITIK SOSIAL DALAM TIGA CERPEN DI KORAN MANUNTUNG TAHUN 1980-AN DI KALIMANTAN TIMUR
No full textAbstrakPengkajian ini memaparkan gambaran kritik sosial dalam tiga cerpen yang dimuat dalam koran di Kalimantan Timur pada tahun 1980-an, yaitu “Nomer”, “Suatu Sore di Pinggiran Desa”, dan “Tatkala Takbir Menggema”. Fenomena sosial di masyarakat dalam cerpen yang dimuat dalam media cetak berbentuk koran ini layak diungkapkan. Pengungkapan fenomena sosial dalam tiga cerpen tersebut sangat diperlukan untuk melihat kondisi sosial masyarakat di tahun 1980-an karena pada tahun-tahun tersebut dapat dikatakan sebagai awal kemunculan karya sastra berbentuk cerpen dalam media cetak berbentuk koran di Kalimantan Timur. Metode kualitatif digunakan penulis untuk mengungkapkan gambaran sosial yang terjadi pada tahun 1980-an di Kalimantan Timur. Pendekatan sosiologi sastra digunakan sebagai alat untuk mengungkapkan masalah sosial dalam tiga cerpen ini. Namun, sebagai pijakan awal, penulis akan memanfaatkan struktural untuk mengungkapkan salah satu unsur intrinsik yang terdapat dalam karya cerpen yang dibahas. Gambaran masalah sosial yang terdapat dalam tiga cerpen di atas adalah masalah kemiskinan, disorganisasi dalam keluarga, disorganisasi keluarga, generasi muda dalam masyarakat modern, pelanggaran terhadap norma masyarakat, kependudukan, lingkungan hidup, dan birokrasi. Kata kunci: kaltim, kritik sosial, koran, cerpen Abstract This study presents a picture of social criticism in three short stories published in newspapers in East Kalimantan in the 1980s, namely "Nomer", "Suatu Sore di Pinggiran Desa", and "Tatkala Takbir Menggema". Social phenomena in the society in those short stories are worth disclosing. It is necessary to see the social conditions in the society in the 1980s. It can be considered to be the beginning of literary works in the form of short stories in print media of newspapers in East Kalimantan. The author uses qualitative methods to reveal the social picture in the 1980s in East Kalimantan. It also uses the sociological approaches to literature to show social problems in these three short stories. However, as a starting point, the writer will use the structure to reveal one of the intrinsic elements in the short stories. Social problems in those short stories are poverty, disorganization in the family, family disorganization, young people in modern society, violations of social norms, demography, environment, and bureaucracy. Keywords: East Kalimantan, social criticism, newspaper, short stories
MATHEMATICAL MODELING OF WATER MOVEMENT DURING A DAM BREAK USING THE VOF METHOD
No full textRiver valleys in mountainous areas are often subject to heavy rains and melting glaciers, resulting in the risk of mudflows and the destruction of hydraulic protective structures. In order to minimize the potential risk and negative outcomes of a disaster, both on an individual and environmental scale, it is crucial to possess essential information. This includes understanding the timing, location, and extent of flooding, as well as comprehending the force of water flow impact on protective structures. In the research, the numerical process of the movement of the water flow caused by the breakthrough of the dam is investigated. A two-dimensional numerical model of water flow during a dam break was constructed using the VOF method to describe the described process. With the help of the VOF method, the movement of the water surface is captured, while maintaining the law of conservation of mass. The mathematical model consists of Reynolds-averaged incompressible Navier-Stokes equations and includes the interphase equation. The turbulent k-e model was used to close the system of equations. The numerical algorithm used is PISO (Pressure-Implicit with Splitting of Operators). The obtained numerical results agree with the experimental data, indicating the developed algorithm’s reliability and accuracy. The results are presented as comparative graphs and images showing the contour of the free surface movement along the experimental reservoir. A numerical model that has been tested in this way can provide significant support in preventing the devastating consequences of a dam break and providing timely assistance during the evacuation of the population
VALUES OF A. GAIDAR’S HEROES (“TIMUR AND HIS TEAM”)
No full textThe purpose of the article is to show values of A. Gaidar’s heroes as a system and prove that its
roots can be found in pre-revolutionary culture. Such approach helps to disclose deep connection of author’s
works with Russian classical literature. The novel “Timur and his team” became the object for analysis as it
has seriously influenced behavioral strategies of teens. The analysis of the work in the aspect of axiology
helps to overcome ideological approach to estimating Gaidar’s art. Such guidelines as living in team, doing
good things, saving world from injustice, labour as happiness are pointed out. Special accent is made on
depicting episodes of Timur’s team help to the inhabitants of the village, the structure of such episodes is
carefully studied. It is shown that help is being planned as a military operation, which results in actions
being coordinated and swift, also pointed out methods, which helped Gaidar achieve dynamism, swiftness
in these episodes: lack of detailed descriptions, the predominance of verbs, a vivid comparison, a curious ending. As a result work is
presented not as exhausting, but hard and joyful occupation. Also several principles of creating Timur’s team members are characterised: the author uses telling surnames, gives his heroes a stable portrait feature, a special manner of speech. The main conclusion of the
article is that Gaidar finds the origins of new soviet culture in old, pre-revolutionary culture, that’s why in his novel a lot of references
to key works of Russian literature (e.g. to Gogol’s “Taras Bulba”, Pushkin’s “Capitain’s Daughter”) and art (Repin’s painting “Cossaks
of Zaporozhye write a letter to the Turkish sultan) can be found, the usage of symbolic character images (ravine, garden, chapel with
the pictures of hell) is marked. Gaidar brings back traditional values, which were abandoned in the era of revolutionary reorganisation
of society, but fills them with new, actual for his time ideas. The conclusions of the article may be used in the practise of teaching in
schools and universities
Machine learning algorithms for stratigraphy classification on uranium deposits
No full textMachine learning today becomes more and more effective instrument to solve many particular problems, where there are difficulties to apply well known and described math model. In other words - it is a great tool to describe non-linear phenomena. We tried to use this technique to improve existing process of stratigraphy, and reduce costs on site by applying computer leaded predictions on the basis of existing on-field collected data. Article describes usage of machine learning algorithms for stratigraphy boundaries classification based on geophysics logging data for uranium deposit in Kazakhstan. Correct marking of stratigraphy from geophysics logging data is complex non-linear task. To solve this task we applied several algorithms of machine learning: random forest, logistic regression, gradient boosting, k nearest neighbour and XGBoost
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