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International Conference on Electrical engineering and Computer Science (ICECOS)

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

ISBN: (数字)9798350368253

ISBN: (纸本)9798350368260

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.

关键词： Heart rate Pediatrics Accuracy Prototypes Artificial neural networks Electrocardiography Real-time systems Internet of Things Servers Testing

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Security Door Lock Using Multi-Sensor System Based on RFID, Fingerprint, and Keypad

Security Door Lock Using Multi-Sensor System Based on RFID, ...

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Green Energy, Computing and Sustainable Technology (GECOST), International Conference on

作者： Joni Welman Simatupang Ramses Wanto Tambunan Electrical Engineering Study Program Faculty of Engineering President University Cikarang Indonesia

ISBN: (纸本)9781665486644

Thefts problem in household needs to be anticipated with home security system. One of simple methods is using automatic solenoid door lock system, so that it is difficult to be duplicated and will reduce the chance of theft action when the house is empty. Therefore, a home security system prototype that can be accessed by utilizing biometric fingerprint, Radio Frequency Identification (RFID), and keypad sensors was designed and tested. Arduino Uno works to turn on the door lock solenoid, so door access will be given when authentication is successful. Experimental results show that fingerprint sensor works well by being able to read fingerprints perfectly and the average time required to scan a fingerprint was 3.7 seconds. Meanwhile, Radio Frequency Identification (RFID) sensor detects Electronic-Kartu Tanda Penduduk (E-KTP) and the average time required for Radio Frequency Identification (RFID) to scan the card is about 2.4 seconds. Keypad functions to store password to unlock the door which produces the average time of 3.7 seconds after 10 trials. Average time to open with multi-sensor is 9.8 seconds. However, its drawback is no notification or SMS which directly be accessed by a cellphone or website with Wi-Fi or Telegram applications allow homeowners to monitor their doors from afar as to minimize the number of house thefts.

关键词： Prototypes Thumb Passwords Fingerprint recognition Sensor systems Sensors Security

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Ensemble Deep Learning NARX for Estimating Time Series of Earthquake Occurrence

Ensemble Deep Learning NARX for Estimating Time Series of Ea...

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Robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： Hapsoro Agung Nugroho Eka Yuni Astuty Aries Subiantoro Benyamin Kusumoputro Department of Electrical Engineering Research Center for Artificial Intelligence and Data Engineering Faculty of Engineering University of Indonesia Depok Indonesia Information Systems Study Program Faculty of Engineering Darma Persada University Jakarta Indonesia

ISBN: (数字)9798350307566

ISBN: (纸本)9798350307573

Predicting earthquake occurrences in time series data remains a challenging task in seismology. NARX (Nonlinear Autoregressive with eXogenous input) neural networks have recently shown promise for accurate predictions. While previous research has demonstrated NARX's effectiveness in estimating earthquake frequencies, the architecture still relies on several pre-determined parameters. These parameters include the number of hidden layers, number of neurons, and delay time. This study aims to investigate the effectiveness of Ensemble Deep Learning NARX neural networks in predicting time series of earthquakes. The proposed ensemble model integrates multiple NARX neural networks, each trained on a distinct subset of earthquake data. This approach aims to enhance prediction accuracy and bolster model robustness. The dataset consists of time series records detailing earthquake occurrence frequencies and magnitudes. The results show performance evaluation metrics in terms of Mean Square Error (MSE) values. For training frequency data, the MSE is 4.10e-26, and for testing, it is 6.05e-22. Regarding training magnitude data, the MSE is 2.86e-21 for training and 3.17e-19 for testing. This study makes a valuable contribution to the advancement of earthquake prediction techniques, underscoring the potential of Ensemble Deep Learning NARX neural networks for precise time series estimation in seismology.

关键词： Deep learning Training Time series analysis Earthquakes Seismology Estimation Predictive models

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Hydrogen production by steam reforming of fusel oil over Ni-based fiber catalyst

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Materials Today: Proceedings 2022年 57卷 1147-1153页

作者： Le-Mai, T.H. Mhadmhan, S. Trieu, T.Q. Prasongthum, N. Suriya, P. Reubroycharoen, P. Department of Chemical Technology Faculty of Science Chulalongkorn University Bangkok10330 Thailand Center of Excellence on Petrochemical and Materials Technology Chulalongkorn University Research Building Bangkok10330 Thailand Program of Petrochemistry Faculty of Chemical Engineering Industrial University of Ho Chi Minh City 70000 Viet Nam Pathum Thani12120 Thailand

This research aimed to evaluate the fusel oil steam reforming over Ni/carbon nanotubes-silica fiber (Ni/CNTs-SF) catalysts prepared by impregnation method with 10 wt% of Ni loading. CNTs-SF was synthesized by chemical vapor deposition (CVD) using ethanol as a source for CNTs over steam reforming. The prepared catalysts were analyzed by BET, XRD, TEM, FESEM-EDS, Raman, and TG/DTG. Ni/CNTs-SF catalyst was tested for fusel oil steam reforming and compared with Ni supported on conventional silica such as a silica fiber (SF) and a silica porous (SP) at the same loading. The results found that Ni/CNTs-SF catalyst showed better catalytic activity and stability than Ni/SF and Ni/SP. TGA profile of the catalysts after fusel oil steam reforming showed that the severe carbon deposited over Ni/SP at 64% (wt%), while at 31% was found over Ni/CNTs-SF catalyst and Ni/SF catalyst. In addition, Ni/CNTs-SF catalyst exhibited the highest hydrogen yield at 15%, and Ni/SF and Ni/SP catalysts gave a lower yield of hydrogen at 11% and 7%, respectively. © 2021

关键词： Carbon nanotubes

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Performance Analysis of YOLO-DeepSORT on Thermal Video-Based Online Multi-Object Tracking

Performance Analysis of YOLO-DeepSORT on Thermal Video-Based...

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Robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： Nur Ibrahim Arsyad Ramadhan Darlis Herianto Benyamin Kusumoputro Department of Electrical Engineering Research Center for Artificial Intelligence and Data Engineering Faculty of Engineering University of Indonesia Depok Indonesia Information Systems Study Program Faculty of Engineering Darma Persada University Jakarta Indonesia

ISBN: (数字)9798350307566

ISBN: (纸本)9798350307573

Recently, thermal cameras have been used in various fields, including surveillance systems and advanced driver assistance systems (ADAS), as they perform better in low light than visible-light cameras. Some challenges in the surveillance system or ADAS field related to thermal cameras are occlusion and thermal crossover between objects with similar appearances during object detection or object tracking tasks, which can lead to misdetection, false positives, and lost tracking. In this paper, performance analysis of you-only-look-once (YOLO) combined with deep online real-time tracking (DeepSORT) on thermal video-based online multi-object tracking (MOT) in occlusion and thermal crossover scene is presented. YOLO, as one of state-of-the-art method for detection task, is used for detection system. Then, the detected object from YOLO is tracked using DeepSORT. The results demonstrate that the online MOT of sequential thermal images using YOLO-DeepSORT achieved a MOTA score of 44.2% and IDF1 of 45.3%. Thus, negative example was added in YOLO training process to reduce false detection, and it gives improvement with MOTA score of 63.8% and IDF1 score of 54.6%.

关键词： YOLO Training Surveillance Cameras Real-time systems Thermal analysis Performance analysis

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LoRa Network Design for Monitoring Landslides on 150 KV Delivery Tower

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

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International Conference on Smart Computing & Communications (ICSCC)

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

ISBN: (数字)9798350363104

ISBN: (纸本)9798350363111

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.

关键词： Rain Electricity Poles and towers Soil moisture LoRa Terrain factors Reliability Monitoring Signal to noise ratio Meteorology

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

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

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Converging Technology in Electrical and Information engineering (ICCTEIE), International Conference on

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

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.

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Ag-decorated 3D flower-like Bi_(2)MoO_(6)/rGO with boosted photocatalytic performance for removal of organic pollutants

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Rare Metals 2021年第5期40卷 1086-1098页

作者： Xin Liu Wei-Ya Huang Qin Zhou Xi-Rong Chen Kai Yang Dan Li Dionysios D.Dionysiou Faculty of Materials Metallurgical and ChemistryJiangxi University of Science and TechnologyGanzhou 341000China Environmental Engineering and Science Program Department of Chemical and Environmental EngineeringUniversity of CincinnatiCincinnatiOH 45221-0012USA College of Science HealthEngineering and EducationMurdoch UniversityMurdoch 6150Australia

A series of unique 3D flower-like Bi_(2)MoO_(6)(BMO)/reduced graphene oxide(rGO)heterostructured composites decorated with varying amounts of Ag nanoparticles(NPs)were *** morphological characteristics,structural features,energy band structures and photoelectrochemical properties were systematically *** the Ag/BMO/rGO ternary composites(AgBGy;y=1%,2%and 3%)demonstrated greater photocatalytic activity towards efficient removal of our selected organic models[methyl orange(MO),rhodamine B(RhB)and phenol],as compared with the BMO/rGO binary composites(BG-x;x=0.25,2,4 and 5).Particularly,AgBG-2%,which was synthesized with the addition of 2 wt% rGO and 2 wt%Ag in BMO,possessed superior photocatalytic *** fitted rate constants(k)for the photocatalytic degradation of RhB,MO and phenol using AgBG-2% were estimated to be 0.0286,0.0301 and 0.0165 min^(-1),respectively,which were over one order of magnitude greater than those obtained using pure *** factors may contribute to the observed enhancement,including greater specific surface area,enhanced light absorption,promoted spatial separation of electronhole(e^(-)-h^(+))pairs and their suppressed recombination,especially benefiting from the synergistic effects among BMO,rGO and Ag *** work suggests that the rational design of BMO/rGO/Ag ternary composite was an effective strategy to boost the photocatalytic activity of the resulting catalyst towards the highly efficient removal of organic pollutants from water.

关键词： Bi_(2)MoO_(6) Reduced graphene oxide Ag nanoparticles 3D flower-like morphology Photocatalytic degradation

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Determination of Planck's Constant Using the Photoelectric Effect Experiment 11

Determination of Planck's Constant Using the Photoelectric E...

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11th National Physics Seminar, SNF 2022

作者： Fitri, U.R. Ziveria, M. Muhara, I. Department of Physics Education Universitas Negeri Jakarta Jl. Rawamangun Muka Jakarta13220 Indonesia Information Systems Study Program Kalbis Institute of Technology and Business Jl. Pulomas Selatan No.22 Jakarta Indonesia Chemical Engineering Study Program Faculty of Industrial Technology Institut Teknologi Bandung West Java Bandung Indonesia

Planck's constant experiment has been carried out to determine the value of Planck's constant using the regression analysis method. The steps are carried out using the scientific process outlined in the practical work steps. The specification of the experimental equipment uses the Planck constant experimental set with 12v/35w tungsten halogen light, 15v output, +-0.2% accuracy, 220V power requirement, 0.5A fuse rating and red, yellow 1, yellow 2, and red color filters, green and blue. Experiments using the concept of the photoelectric effect phenomenon began by irradiating metallic materials with light using a filter. The wavelength (635, 570, 540, 500, 460) nm is the light filter variation. The wavelength that hits the metal material is selected by placing a light filter on the light propagation path toward the metal material. So the light that passes through the filter is only light with a certain wavelength. After the metal material is irradiated by light with a certain wavelength, then the stopping potential voltage measurement is carried out on the metal material irradiated by light. From the variation of the light filter used, it is possible to calculate Planck's constant using the regression method with the value obtained 6.26x1034. This value is very close to the actual Planck's constant value which is 6.62x1034 so an error value is obtained 4.23%. With 95.77% accuracy, Planck's constant value obtained from the calculation using the linear regression method can be said to be very close to the actual Planck's constant value. © Published under licence by IOP Publishing Ltd.

关键词： Photoelectricity

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Bridging the gap in nutrient management: Transitioning from conventional to sustainable slow-release fertilizers in modern agriculture

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Journal of Cleaner Production 2025年 513卷

作者： Said, Nor Sakinah Mohd Kurniawan, Setyo Budi Daud, Nurull Muna Sharuddin, Siti Shilatul Najwa Barakwan, Rizkiy Amaliyah Luthfi, Abdullah Amru Indera Department of Chemical and Process Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia UKM Selangor Bangi43600 Malaysia Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia UKM Selangor Bangi43600 Malaysia Jakarta Pusat10340 Indonesia Environmental Engineering Study Program Department of Biology Faculty of Science and Technology Universitas Airlangga Kampus MERR C Dr. Ir. H. Soekarno Street Mulyorejo East Java Surabaya60115 Indonesia

The world's continuous demographic expansion has driven a growing demand for a stable food supply, making the agriculture sector a key foundation for sustainable food production. However, the widespread use of conventional fertilizers has resulted in significant environmental and economic drawbacks, including inefficient nutrient delivery and nutrient leaching. These challenges highlight the urgent need for innovative agricultural solutions. This article reviews the adverse impacts of conventional fertilizer use on ecosystems and discusses the transition to slow-release fertilizers (SRF) as a promising alternative. SRF offers more controlled nutrient release, reducing nutrient loss and improving efficiency compared to traditional fertilizers. The article examines different types of SRF, their mechanisms, advantages, limitations, and their potential to transform modern agriculture by addressing both environmental concerns and crop nutrient management. Key challenges, including high production costs and the use of non-biodegradable coatings, are addressed. This review highlights the potential of bio-based coatings as replacements for non-renewable petroleum-based materials in SRFs, promoting sustainable practices and reducing potential toxicity in agricultural applications. The evolution of SRFs into multifunctional fertilizers is also discussed, emphasizing their expanding roles beyond controlled nutrient release. © 2025 Elsevier Ltd

关键词： Crops

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