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Information system for diagnosis in pregnant chronic energy deficiency using a rule based system algorithm 10

Information system for diagnosis in pregnant chronic energy ...

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10th International Seminar on New Paradigm and Innovation of Natural Sciences and itsApplication, ISNPINSA 2020

作者： Sustamy, R.P. Widyawati, M.N. Suryono, S. Master of Applied Science in Midwifery Program Poltekkes Kemenkes Semarang Indonesia Departement of Physics Faculty of Science and Mathematics University Diponegoro Semarang Indonesia

The condition of Chronic Energy Deficiency (CED) has become one of the causes of high maternal mortality. Improper handling of CED will have an impact on the health problems of both mother and baby. This is because when the diagnosis is still using conventional methods, so it takes a long time or is not time efficient, an alternative is needed to improve the quality of information system-based services in diagnosing mothers with CED. In this research, an information system design was carried out using the SDLC (System Development Life Cylce) method with the waterfall model which includes: needs analysis, design, implementation, and offer. Analysis of speed data using respondents 15 chronic energy deficiency pregnant and static test using Mann Whitney obtained p-value 0.000 p © Published under licence by IOP Publishing Ltd.

关键词： Information systems

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Predicting Potential Fires in Indonesia by Analyzing VIIRS Night Data during 2018 – 2022

Predicting Potential Fires in Indonesia by Analyzing VIIRS N...

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International Symposium on Grids and Clouds 2023 in conjunction with HEPiX Spring Workshop, ISGC and HEPiX 2023

作者： Suhardiman, Basuki Hermanto, Benni Rio Directorate of Information Technology Institut Teknologi Bandung Jl Ganesha 10 Bandung Indonesia Master’s Program in Computational Science Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl Ganesha 10 Bandung Indonesia Biomedical Engineering Department School of Electrical Engineering and Informatics Institut Teknologi Bandung Indonesia

Forest fires have been detected to occur in Indonesia since 1998. The forest fires mostly resulted from human activities in order to expand their land, especially oil palm lands. Once a land clearing is carried out, it covers areas of tens to hundreds of thousands of hectares. The peak of the forest fires occurred in 2015 when almost half of the world was affected especially by smoke from the fire. In 2011, VIIRS (Visible Infrared Imaging Radiometer Suite) was launched by NOAA (National Oceanic and Atmospheric Administration). In their collected data, there is data on Indonesia issued daily for areas in the islands of Java, Sumatra, Kalimantan, Sulawesi, and the general areas of Indonesia. The VIIRS night data shows the possibility of some burning at night. We need to identify burnings that potentially become fires, which are potentially producing smoke. It is important to observe areas where large-scale forest fires frequently occur, so the authority could do some prevention beforehand. Using existing data released per day per area, we utilize an ANN (Artificial Neural Network) to identify a potential fire. The processes start with data cleaning and processing, Neural Network creation, and finally ANN training and testing. By using the ANN prediction model with the MinMax Scaler, we choose variables Temperature, Radiant Heat Intensity, and Source Footprint. Simulations are made to show the ranges of these variables that predict the possibility of’flame’ status occurring. We conclude that the ANN method can give more accurate results than the existing classification. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Fires

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Long Short-Term Memory-based Models for Sleep Quality Prediction from Wearable Device Time Series Data 8

Long Short-Term Memory-based Models for Sleep Quality Predic...

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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Hidayat, Alam Ahmad Budiarto, Arif Pardamean, Bens Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia

Several studies suggest that sleep quality is associated with physical activities. Moreover, deep sleep time can be used to determine the sleep quality of an individual. In this work, we aim to find the association between physical activities and deep sleep time by modeling the time series data such as heart rate and a number of steps captured from a commercial wearable device. Our previous study demonstrates that deep learning-based time series modeling is well suited for our problem since the temporal patterns in the two physical parameters need to be captured to obtain more accurate results. We first preprocess our series data to have a time-step size of 10 minutes. To improve our previous effort in this modeling, we compare four different variants of Long Short-Term Memory (LSTM)-based models, ranging from single input to dual input models. Our result shows that the simple stacked LSTM model performs better for our data because the remaining models suffer from overfitting due to a larger number of the trained parameters. © 2023 The Authors. Published by Elsevier B.V.

关键词： deep learning forecasting sleep quality time series wearable devices

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Multivariate Time-Series Deep Learning for Joint Prediction of Temperature and Relative Humidity in a Closed Space 8

Multivariate Time-Series Deep Learning for Joint Prediction ...

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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Gunawan, Fergianto E. Budiman, Arief S. Pardamean, Bens Juana, Endang Romeli, Sugiarto Cenggoro, Tjeng W. Purwandari, Kartika Hidayat, Alam A. Redi, Anak A.N.P. Asrol, Muhammad Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia PT Impack Pratama Industri Jakarta14350 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

An accurate predictive model of temperature and humidity plays a vital role in many industrial processes that utilize a closed space such as in agriculture and building management. With the exceptional performance of deep learning on time-series data, developing a predictive temperature and humidity model with deep learning is propitious. In this study, we demonstrated that deep learning models with multivariate time-series data produce remarkable performance for temperature and relative humidity prediction in a closed space. In detail, all deep learning models that we developed in this study achieve almost perfect performance with an R value over 0.99. © 2023 The Authors. Published by Elsevier B.V.

关键词： closed space deep learning humity prediction indoor temperature prediction

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Dielectrophoretic force characteristics toward Lactobacillus casei on an oblique-patterned electrode 10

Dielectrophoretic force characteristics toward Lactobacillus...

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10th Asian Physics Symposium 2023, APS 2023

作者： Khazanna Fitriyani, S. Safitri, R. Lahna, K. Yusibani, E. Irwansyah Iswardy, E. Master Program in Physics Department of Physics Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Banda Aceh23111 Indonesia Department of Dental Materials Faculty of Dentistry Universitas Syiah Kuala Banda Aceh23111 Indonesia Department of Physics Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Banda Aceh23111 Indonesia Department of Mechanical Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Research Center Universitas Syiah Kuala Banda Aceh23111 Indonesia

Dielectrophoresis-based biochips with various microelectrode configurations have been extensively studied within the last five deca des. However, wide-field application is still challenging. This study aims to fabricate an oblique-configuration microelectrode and then utilizes it to determine the dielectrophoretic (DEP) characteristics of Lactobacillus casei based on the generated non-uniform electric field. The electric field distribution on microelectrodes was simulated with Quickfield 6.6 student version. The microelectrodes were fabricated using a copper film on a glass substrate. The DEP characteristic of Lactobacillus casei was investigated by applying a sinusoidal AC signal to microelectrodes in medium solution with an electrical conductivity of 0.05 S/m. The electric-field simulations show that the strongest electric-field was generated on the tip of electrodes spacing, and the weakest electric-field was generated on the inner of electrodes spacing. The negative-DEP force on Lactobacillus casei was observed at the frequency of 60-130 kHz, while the positive-DEP force was observed at the frequency of 380-700 kHz, both at voltage of 2-6 Vpp. The nDEP force led Lactobacillus casei to be pushed toward the weak electric field on the inner of electrodes spacing, and the pDEP force induced Lactobacillus casei to be attracted toward the strong electric-field on the tip of electrodes spacing. This study implies that the proposed oblique-microelectrode platform has promising application for bioparticles separation. © Published under licence by IOP Publishing Ltd.

关键词： Microelectrodes

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Practicality of interactive multimedia of natural science integrated with the theme of motion in life using an integrated scientific approach to 21st-century learning 3

Practicality of interactive multimedia of natural science in...

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3rd International Conference on Research and Learning of Physics, ICRLP 2020

作者： Kurniawati, Annisa Ratnawulan Fauzi, Ahmad Physics Education Master Study Program Faculty of Mathematics and Natural Sciences Universitas Negeri Padang Jl. Prof Hamka Padang25131 Indonesia

This interactive multimedia was developed using a scientific approach and integrated with the characteristics that exist in 21st-century learning. The practicality test aims to assess the practicality of the interactive multimedia products being developed. The practicality test was carried out by distributing a questionnaire in the form of an instrument sheet for the practicality of the response of educators and the responses of students to 2 educators and 15 students. The data analysis technique to assess the practicality of the product is the Likert scale. The result is an Integrated Natural Science interactive multimedia developed with very practical criteria so that students and educators can use it in teaching and learning activities. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Air Quality Prediction Based on Air Pollution Emissions in the City Environment Using XGBoost with SMOTE 4

Air Quality Prediction Based on Air Pollution Emissions in t...

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4th IEEE International Conference of Computer Science and Information Technology, ICOSNIKOM 2022

作者： Nababan, Adli A Sutarman Zarlis, Muhammad Nababan, Erna B Universitas Sumatera Utara Faculty of Computer Science and Information Technology Department of Computer Science Medan Indonesia Universitas Sumatera Utara Faculty of Mathematics and Natural Sciences Department of Mathematics Medan Indonesia Binus Graduate Program-Master of Information Systems Management Bina Nusantara University Department of Information Systems Management Jakarta Indonesia

ISBN: (纸本)9798350399073

Air pollution makes it worse in populated regions. Indonesia's major cities are also impacted by air pollution. Due to rising traffic, material consumption by vehicles, industrial growth, land burning, and garbage collection, air quality has altered significantly. Accurate measurement and classification of air quality are required. Results of accurate classification aid in forming governmental regulations. To reach the criteria for livable air quality, we intend to manage controls. Some of the characteristics of air pollution include particulate (PM10) or PM25, sulfides (in the form of SO2), carbon monoxide (CO), ozone (O3), and nitrites (NO2). Using the XGBoost algorithm and synthetic minority oversampling (SMOTE) methods based on the Air Pollution Standard Index (ISPU) category, this study seeks to uncover factors that affect air quality. XGBoost, an ensemble machine learning approach built on a decision tree and applying a gradient reinforcement framework, is the classification algorithm in use. Air quality categorization has been tested and shown to work with the XGBoost algorithm. The dataset used in this study is air quality in 2021 which was collected by the Jakarta Environmental Ministry The proposed classification model will be evaluated using the Repeated k-fold cross-validation method for objective results. The results of the study prove that SMOTE and XGBoost have better performance than using only the XGBoost method in predicting air quality, where the overall accuracy value of SMOTE with XGBoost is 99.60%, The overall precision value is 99.60%, the overall recall value is 99.60% and the overall f1-score is 99.60% and the overall ROC AUC value is 99.96%. The overall SMOTE method with the proposed XGBoost has given better performance in air pollution prediction. © 2022 IEEE.

关键词： Air quality

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Interval graphs for Genome-Fragment combinations

Interval graphs for Genome-Fragment combinations

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2023 International Conference on Mathematical and Statistical Physics, Computational Science, Education and Communication, ICMSCE 2023

作者： Kao, Shin-Shin Wu, Tzong-Yuan Department of Applied Mathematics Program of International Master of Business Administration Chung Yuan Christian University No. 200 Jong-Bei Road Chung-Li District Tao-Yuan320314 Taiwan Department of Bioscience Technology Chung Yuan Christian University No. 200 Jong-Bei Road Chung-Li District Tao-Yuan320314 Taiwan

ISBN: (纸本)9781510671768

The main purpose of this research work is to apply the theory of "interval graphs" to a specific viral genome, reconstruct the sequence from the unknown-ordered fragments for possible combinations for further studies. We use the restriction digestion method to cut the chromosome into many segments with several restriction enzymes. These cut segments can be separated by agarose gel electrophoresis according to their molecular size and are not in order of the original sequence. Besides, the segments cut out by each enzyme are different, so there will be intersections (sub-segments). The method of interval graph, suggested by14, attempts to use the information at the intersection to reorganize the original sequence. We selected our own patented insect viral gene sequence and conducted research on the above-mentioned interval graph method. More specifically, the isolated recombinant baculovirus, tentatively named ABM, and the widely-used prototype of baculovirus species, which is Autographa californica multiple nucleopolyhedrovirus (AcMNPV), were used as the model system. Although the length of the insect viral genome sequence we used is relatively short as compared with the genome of organisms, this study failed to achieve the purpose of sorting by the method of interval graph. The two main reasons can be summarized as follows: First, the enzyme experiment detected multiple short segments that did not intersect with other segments, and the interval graph method could not determine their positions in the original sequence. Secondly, any "graph" is made up of vertices and edges. Representing gene sequences with interval graphs means translating segments and intersecting segments with vertices and edges. Even if the improved method was adopted, the number of vertices and edges that can be loaded by the existing hardware makes this research unable to complete all the steps of the basic interval graph construction. This paper illustrates the experimental methods, mathematic

关键词： Enzymes

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Design of Drone Remote-Control System using Human Motion Recognition 5

Design of Drone Remote-Control System using Human Motion Rec...

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5th IEEE Eurasian Conference on Educational Innovation, ECEI 2022

作者： Chen, Shyh-Wei Lai, Yu-Chun Liu, Chia-Hui Kuo, Chin-Guo Tunghai University Department of Computer Science Taichung Taiwan Tunghai University Master Program of Digital Innovation Taichung Taiwan Chinese Culture University Department of Applied Mathematics Taipei Taiwan National Taiwan Normal University Department of Industrial Education Taipei Taiwan

ISBN: (纸本)9781665433181

At present, the most common and low-cost method to control the drone is to use a mobile phone with an APP. The operator takes his mobile phone screen as a human-machine interface, and at the same time controls and receives the images returned by the drone. The control mode can be divided into two symmetry modes according to how the operator views and knows the location of the drone: exocentric viewing and egocentric viewing mode. In the exocentric viewing mode, the operator directly visually confirms the position of the drone, while in the egocentric viewing mode, the drone is equipped with a camera and transmits the flight image to the operator in real-time. Since the drone cannot be far away from the operator in the exocentric viewing mode, the relative egocentric mode allows the operator to feel immersed in the environment to control the drone more accurately. Therefore, by adapting the egocentric viewing and using human motion recognition, an unmanned vehicle remote-control system is designed. The low-speed, small-scaled, nature-stability UAVs are ideally suited for the proposed system. The system was designed with a PID controller to improve the UAV's handling. The experimental results verified the feasibility of the UVA control system and it could stabilize the posture of the drone. © 2022 IEEE.

关键词： Drones

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The practicality of natural science learning devices on the concept of environmental pollution with problem-solving learning models

The practicality of natural science learning devices on the ...

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National Seminar of Physics Education 2021, SNPF 2021

作者： Fahmi Fajeriadi, H. Irhasyuarna, Y. Suryajaya Abdullah Master Program of Natural Science Education Postgraduate Program University of Lambung Mangkurat South Kalimantan Banjarmasin City Indonesia Master Program of Biology Education Postgraduate Program University of Lambung Mangkurat South Kalimantan Banjarmasin City Indonesia Study Program of Natural Science Education Departement of Mathematics and Natural Science Education Faculty of Teacher Training and Education University of Lambung Mangkurat South Kalimantan Banjarmasin City Indonesia Study Program of Physics Faculty of Mathematics and Natural Science University of Lambung Mangkurat South Kalimantan Banjarbaru Indonesia Study Program of Chemistry Faculty of Mathematics and Natural Science University of Lambung Mangkurat South Kalimantan Banjarbaru Indonesia

Less varied learning methods make learning activities boring. Emphasis on mastery of concepts and teacher dominance make students' activities passive. The correct methods are needed to achieve the learning objectives. This study aims to evaluate the practicality of natural science learning devices for junior high school on the concept of environmental pollution using a problem-solving learning model. The research method uses Design Development Research by Tessmer. The data was taken at the small group evaluation and field test. Data were collected through observation of teacher and student activities with a scale of 1-4;selfassessment with a score of 1 (positive) and 0 (negative);and student response questionnaires on a scale of 1-5. The data were categorized and analysed descriptively. The results of the small group evaluation are: teacher activities get a good category;student activities with good categories in the preliminary and closing activities, but main activities are still quite good;selfassessment aspects show eight positive and two negatives, and student responses show nine positive and one negative. The field test results are: teacher and student activities get a "very good" category;self-assessment aspects show eight positive and two negative, and student responses are positive for all aspects. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Students

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