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4th International Conference on Electrical engineering and Computer Science, ICECOS 2024

作者： Albar, Nizam Melinda, Melinda Away, Yuwaldi Universitas Syiah Kuala Dept. Electrical Engineering Master of Electrical Engineering Study Program Banda Aceh Indonesia Universitas Syiah Kuala Engineering Faculty Dept. Electrical Engineering and Computer Banda Aceh Indonesia

ISBN: (纸本)9798350368253

Early detection of heart rate conditions in autistic children is crucial for anticipating tantrum reactions and providing prompt medical intervention. Previous research designed a prototype for acquiring Electrocardiogram (ECG) signals using the AD8232 sensor, but it required a long time to identify heart rate conditions. This study aims to develop the previous prototype using Internet of Things (IoT) implementation to acquire and identify the heart rate conditions of autistic children in real time. The ECG signal data is analyzed using Butterworth Filter and Artificial Neural Network (ANN) integrated into Raspberry Pi and results are transmitted to the Blynk App. Testing over 20 minutes showed that in the first 10 minutes, the system identified a normal heart rate at 105.19 BPM with 67% accuracy, while in the second 10 minutes, the heart rate rose to 117.19 BPM with tantrum symptoms and 75% accuracy. This system helps medical personnel provide immediate intervention during tantrums. © 2024 IEEE.

关键词： Butterworth filters

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Advancements in Geopolymer Concrete for Marine Infrastructure: An Optimization of Performance Considering Workability, Compressive Strength, Capillary Water Absorption, Porosity, and Chloride Migration

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Iranian Journal of Science and Technology - Transactions of Civil engineering 2024年 1-14页

作者： Shahedan, Noor Fifinatasha Hadibarata, Tony Jusoh, Muhammad Noor Hazwan Isia, Ismallianto Bouaissi, Aissa Juwono, Filbert Hilman Nawawi, Natasha Ahmad Kusumaningrum, Hermin Pancasakti Muslim, Abrar Hidayat, Topik Environment Engineering Program Curtin University Malaysia Miri CDT 250 Malaysia School of Engineering University of Plymouth Plymouth PL4 8AA United Kingdom Department of Electrical and Electronic Engineering Xi’an Jiaotong – Liverpool University Suzhou China School of Mechanical Engineering College of Engineering Universiti Teknologi MARA Shah Alam 40450 Malaysia Biotechnology Study Program Department of Biology Faculty of Science and Mathematics Universitas Diponegoro Semarang Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Syiah Kuala Banda Aceh Indonesia Biology Study Program Faculty of Mathematics and Science Education Universitas Pendidikan Indonesia Bandung Indonesia

This research investigates the effectiveness of geopolymer concrete incorporating fly ash in environments rich in chlorides;in contrast to conventional Portland cement concrete (OPC). The study emphasizes essential characteristics such as workability, mechanical strength, capillary water absorption, open porosity, and chloride migration. The experiments demonstrated that geopolymer concrete exhibits a 30% enhancement in slump values, reflecting improved workability, and its compressive strength rose by 14.90–23.94% when compared with OPC. A significant reduction in binder content led to a notable decrease in capillary water absorption, highlighting a positive impact on long-term durability. With time, geopolymer concrete showed a reduction in open porosity and chloride migration coefficient, indicating better resistance to chloride penetration in marine settings. Although these outcomes underscore the potential of geopolymer concrete to improve structural durability, especially in marine infrastructure, additional optimization is required to tackle its relatively higher capillary water absorption and chloride migration during the initial stages. These results contribute to the ongoing investigation of sustainable building materials, offering valuable insights into geopolymer concrete’s ability to endure severe chloride exposure and serve as a durable solution for corrosion management in marine infrastructure. © The Author(s), under exclusive licence to Shiraz University 2024.

关键词： Durability Geopolymer concrete Marine environments Mix design Sustainable construction

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Performance of GNSS positioning in PPP mode using MADOCA precise products

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Geodesy and Geodynamics 2024年第6期15卷 642-651页

作者： Brian Bramanto Rachel Theresia Irwan Gumilar Sidik T.Wibowo Geodetic Science Engineeringand Innovation Research GroupFaculty of Earth Sciences and TechnologyInstitut Teknologi BandungBandung 40135Indonesia Geodesy and Geomatics Engineering Study Program Faculty of Earth Sciences and TechnologyInstitut Teknologi BandungBandung 40135Indonesia Geodetic and Geodynamic Control Network Center Geospatial Information Agency of Indonesia(BIG)Cibinong 16911Indonesia

The Global Navigation Satellite System (GNSS) is widely utilized for accurate *** commonly applied method to obtain precise coordinate estimates is by implementing the relative positioning in network ***,this approach can be complex and ***,The Japan Aerospace Exploration Agency (JAXA) offers freely available satellite orbit and clock correction products called Multi-GNSS Advanced Demonstration Tool for Orbit and Clock Analysis (MADOCA),which can enhance positioning accuracy through the precise point positioning (PPP) *** study focuses on evaluating PPP static mode positioning using MADOCA products and comparing the results with the highly precise relative positioning *** analyzing a network of 20 GNSS stations in Indonesia,we found that the PPP method using MADOCA products provided favorable positioning *** median discrepancies and the corresponding median absolute deviation (MAD) for easting,northing,and up components were estimated as 9±18 mm,10±9 mm,and 3±40 mm,*** results indicate that PPP with MADOCA products can be a reliable alternative for establishing Indonesia's horizontal control networks,particularly for orders 0,1,2,and 3,and for a broad spectrum of geoscience monitoring ***,considerations such as epoch transformations and seismic activities should be taken into account for accurate positioning applications that comply with the definition of the national reference framework.

关键词： Global Navigation Satellite System(GNSS) Precise point positioning(PPP) MADOCA Positioning evaluation

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Evaluation Electrical System of Mini Plant Waste Energy on Institut Teknologi PLN 2

Evaluation Electrical System of Mini Plant Waste Energy on I...

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2nd International Conference on Converging Technology in Electrical and Information engineering, ICCTEIE 2023

作者： Pawenary Listiawati, Dwi Hendri Insitut Teknologi PLN Electrical Engineering Study Program Faculty of Electricity and Renewable Energy Jakarta Indonesia

ISBN: (纸本)9798350370645

Waste is a problem in almost every region, especially related to how the processing of waste can be converted into other forms as a form of energy that can be utilized, one of which is waste processing by pyrolysis is one of the technologies to convert waste into useful energy or fuel. At this time waste processing requires waste processing machines ranging from organic and un-organic waste shredding machines, briquette processing machines, pellets, using star-delta 3-phase motors, generally still conventional/manually. Current research, the author began to develop a waste and flue gas particle handling machine, a non-incinerator pyrolysis machine with the wet method, a high efficiency cyclone system which originally used a machine manually/ conventionally, replaced with a Delta series Star - Delta series with interlock and interface) automatically. Garbage processing The machine in addition to aiming to reduce waste waste, the machine must be made automatically and friendly to the operator who runs it. © 2023 IEEE.

关键词： Pyrolysis

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LoRa Network Design for Monitoring Landslides on 150 KV Delivery Tower 10

LoRa Network Design for Monitoring Landslides on 150 KV Deli...

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10th International Conference on Smart Computing and Communication, ICSCC 2024

作者： Pancane, I Wayan Dikse Putra, I Putu Gelgel Astika Gede Suarjana, I Wayan Supranartha, Agus Universitas Pendidikan Nasional Electrical Engineering Study Program Denpasar Indonesia Universitas Negeri Manado Faculty of Sport Science and Public Health Department of Public Health Sulawesi Indonesia Electro Enginering Elektrical Engineering Program Study Politechnic Negeri Bali Badung Indonesia

ISBN: (纸本)9798350363104

The objective of this research is to design and develop an integrated landslide early detection system at Tower Number Eight, 150 kV Gianyar. The research is expected to result in the construction of a communication system based on LoRa technology that will serve to reduce the potential damage from landslides. In order to achieve this, several parameters must be considered as benchmarks. These include RSSI, SNR, BER and PDR. The device operates by monitoring changes in position, soil moisture and rainfall, and then transmitting the data via LoRa technology. At the sink, the data is recorded and monitored for RSSI, SNR, PDR and BER values. In the test, the source 1 node, situated 300 metres away, exhibited an RSSI value of -100 to -109 dBm and an SNR value of 6.75 to -6.7 in both sunny and rainy weather, with a PDR value of 100%. The source 2 node, situated 600 metres away, exhibited an RSSI value of -97 to -109 dBm and an SNR value of 8.5 to -11.75 dB, with a PDR value of 70 to 100%. It should be noted that the number of bits in the sensor data sent is always complete. This is evidenced by the bit error ratio (BER) value, which is always 0 on both source nodes. © 2024 IEEE.

关键词： Soil moisture

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The Darknet Framework YOLOV7 is Used for Pineapple Fruit Ripeness Classification

The Darknet Framework YOLOV7 is Used for Pineapple Fruit Rip...

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Advanced engineering and Technologies (ICONNIC), International Conference on

作者： Nurliana Nasution Feldiansyah Bin Bakri Nasution Mariza Devega Mhd Arief Hasan Informatic Engineering Study Program Universitas Lancang Kuning Pekanbaru Indonesia

In this study, we developed and implemented an object detection method to distinguish between ripe and unripe pineapples. We used a pre-trained object detection model using YOLOv7 and BlendMask techniques and finetuned it on the MS COCO instance segmentation dataset for 30 epochs. Through the preprocessing process, we resized the images to the specified target size and normalized the pixel intensities. We also created bounding boxes to mark objects in the images based on computed coordinates using object scores and attributes. During the prediction stage on two sample images, we accurately predicted that one image contained a ripe pineapple with a confidence level of 56%, while the other image contained an unripe pineapple with a confidence level of 77%. These results demonstrate that our developed object detection method is effective in differentiating the ripeness of pineapples. This research contributes to the development of fruit classification applications based on ripeness levels. The implemented object detection method can serve as a foundation for the development of more advanced systems in automatically identifying and segregating ripe and unripe fruits. As a result, this study has the potential to enhance efficiency and accuracy in the agricultural and fruit processing industries.

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Combustion Profile of Bio-pellet Produced from Sawdust Using Wet Torrefaction Method with Various Concentrations of Acetic Acid 4

Combustion Profile of Bio-pellet Produced from Sawdust Using...

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4th International Symposium on Advances and Innovation in Mechanical engineering, ISAIME 2023

作者： Pertiwi, Indah Ayu Muhammad Abubakar Setiawan, Adi Iskandar, Rizky Magister Program in Renewable Energy Engineering Faculty of Engineering Universitas Malikusssaleh Jalan Batam Bukit Indah Lhokseumawe24352 Indonesia Chemical Engineering Department Faculty of Engineering Universitas Malikussaleh Kampus Bukit Indah Muara Satu Lhokseumawe24352 Indonesia Mechanical Engineering Vocational Education Study Program Faculty of Teaching and Educational Science Universitas Malikussaleh Cot Teungku Nie Reuleut Muara Batu Aceh Utara24355 Indonesia Mechanical Engineering Department Faculty of Engineering Universitas Malikusssaleh Jalan Batam Bukit Indah Lhokseumawe24352 Indonesia

Sawdust is one of the industrial wastes which naturally contains low energy density. An effective method is needed to utilize this biomass as a solid fuel product. This work aimed to investigate the physical and combustion properties of bio-pellets produced from sawdust under the wet torrefaction method. To prepare sawdust bio-pellet a number of steps were carried out including the wet torrefaction process, dough preparation, pelletizing, and drying. Wet torrefaction was performed by hydrothermally treating the sample in an autoclave at a temperature of 130°C and pressure of 2 atm (g) for 80 minutes. For the hydrothermal process, the used acetic acid solution was varied with variations of 1.3 M, 1.8 M, and 2.3 M. Properties of the product were analyzed under proximate and bomb calorimetry analyses. To evaluate the combustion properties a purposely built test apparatus was developed equipped with a data logger system. Based on the results it can be observed that increases in torrefaction temperature and acetic acid concentration resulted in an increase in the calorific value as well as decreases in the ash content. The highest calorific value was 4745 kcal/kg obtained from sawdust torrefied in acetic acid with a concentration of 2.3 M at a temperature of 130?. This sample also exhibits the lowest ash content which is only 1.97%. The combustion test disclosed a maximum combustion temperature of 589? with a burning rate of 0.711 g/min. Overall, the wet torrefaction applied in this investigation was beneficially enhanced the properties of bio-pellet products. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Sawdust

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Effect of High-Flow Nasal Cannula on Capnogram Waveform for studying Non-Invasive Human Ventilation 2

Effect of High-Flow Nasal Cannula on Capnogram Waveform for ...

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2nd IEEE National Biomedical engineering Conference, NBEC 2023

作者： Tirta Nindhia, Tjokorda Gde Aqila Mohammed, Nursyasa Jamaludin, Julia Jais Devandran, Pagupathi Angel Bhaswara, Nabiel Rafa Hutajulu, Thalitakum Malarvili, M.B. Udayana University Jimbaran Study Program of Mechanical Engineering Engineering Faculty Bali Indonesia Universiti Teknologi Malaysia School of Biomedical and Health Science Engineering Johor Malaysia

ISBN: (纸本)9798350338546

This study is conducted to compare three different cannulas;all purpose nasal cannula with 2 prongs, nasal pressure cannula with 2 prongs and single port nasal cannula which are commonly used for capnography device. These cannulas or sometimes called as nasal prong is connected to the device via nose of subjects studied. This procedure is a part of respiratory study to monitor lungs condition and breathing pattern. This study involves 47 subject where the exhaled breath was recorded to make comparison and choose the most suitable and effective for capnography waveform analysis. Utilizing Statistical Package for the Social Sciences (SPSS) to find the normality of all the nasal cannula data based on capnogram waveform. The result from the analysis shows that the frequency distribution for type 1 nasal cannula which is also known as all-purpose nasal cannula had the feature values closer to the standard value. Our study proofs that all purpose nasal cannula sampling is the most suitable to capture exhaled breath for monitoring respiratory conditions. © 2023 IEEE.

关键词： capnography CO2 monitoring, feature extraction nasal cannula

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Classification of Orange Fruit Using Convolutional Neural Network, Support Vector Machine, K-Nearest Neighbor and Naive Bayes Methods Based on Color Analysis

Classification of Orange Fruit Using Convolutional Neural Ne...

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Computer Science, Information Technology and engineering (ICCoSITE), International Conference on

作者： Widhi Ersa Pratiwi Mhd Arief Hasan Gusyella Mustika Siti Sarah Dwi Suci Ramadhani Fadli Julizar Ferry Informatic Engineering Study Program Universitas Lancang Kuning Pekanbaru Indonesia

Citrus fruit is a fruit that has good vitamins and is popular with the public. This fruit also has various types with different benefits. Each type of orange also has a variety of colors. Types of oranges can be checked manually by looking directly at the color and texture of the fruit. This manual method is very simple but also very subjective because of the different understanding of each person about the types of oranges. Therefore, this research discusses and explains how to determine the type of fruit by comparing several methods, namely using the SVM method (Support Vector Machine), the CNN method (Convolutional Neural Network), the K-NN method (K-Nearest Neighbor), and the Naïve Bayes method by taking several samples of citrus fruit images consisting of sweet oranges, lemons and limes using a mobile phone camera. The total dataset used in this study is 90 datasets consisting of 30 sweet orange images, 30 lime images and 30 lemon images. Of the 90 datasets are divided into training data and test data. From the results of the study, it was obtained that the accuracy of compatibility with a percentage of 100% using the CNN method (Convolutional Neural Network).

关键词： Support vector machines Image color analysis Training data Manuals Nearest neighbor methods Cameras Mobile handsets

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Developing Organizational Resilience Model to Sustain Business Performance

Developing Organizational Resilience Model to Sustain Busine...

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2022 IEEE International Conference on Industrial engineering and engineering Management, IEEM 2022

作者： Jonny Mangindaan, Dave Faculty of Engineering Bina Nusantara University Professional Engineer Study Program Industrial Engineering Department Jakarta Indonesia Bina Nusantara University Professional Engineer Study Program Faculty of Engineering Jakarta Indonesia

ISBN: (数字)9781665486873

ISBN: (纸本)9781665486873

Organizational resilience is about combination of operational and strategic resilience to sustain company's performance. In the time of turbulence like COVID-19 pandemic era, this resilience is extremely needed for any organizations not only to bounce back from its disruption but also ensures its sustained performance. However, knowledge related to this ability is still lacking and developing to cover especially factors needed to develop resilience for organization. Thus, this paper is proposing an organizational resilience model that covers what factors known so far. For this research, 100 organizations were invited for the research using questionnaires as its instrument. Among these invited organizations, only 47 organizations have given their responses at rate of 47%. Partial Least Square Structural Equation Modeling (PLS-SEM) method using SmartPLS 3.0 was utilized for data processing. This confirms that organization should promote its resilience through operational dan strategic resilience to sustain its performance especially in times of turbulence especially during COVID-19 pandemic era. © 2022 IEEE.

关键词： COVID-19

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