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Effect of physical and biological pretreatment on sugarcane bagasse waste-based biogas production

Materials Today: Proceedings 2023年 87卷 41-44页

作者： Sumardiono S. Matin H.H.A. Sulistianingtias I. Nugroho T.Y. Budiyono B. Department of Chemical Engineering Faculty of Engineering Universitas Diponegoro Semarang 50239 Indonesia Study Program of Environmental Science Faculty of Mathematic and Natural Science Universitas Sebelas Maret Surakarta 57126 Indonesia Vocational School Universitas Diponegoro Semarang 50239 Indonesia

Sugarcane bagasse is a biomass with very potential, especially in agricultural countries. In this research, a study related to pretreatment and the ratio of C/N to biogas production from sugarcane bagasse was conducted. The study was carried out on a laboratory scale with physical pretreatment by grinding with a size of 6 mesh, then biological pretreatment with the microbial consortium 5 % g/V, and variations in the C/N ratio at 25 and 30. Cow rumen fluid was used in this study as a source of anaerobic bacteria and technical urea is used to adjust the C/N ratio. The solid total is set at 7 %. Based on research that has been carried out for 60 days, it was found that physical pretreatment by grinding with a size of 6 mesh can increase biogas production. Biogas production increased both at C/N ratio conditions of 25 and 30. Furthermore, biological pretreatment with the microbial consortium 5 % g/V was proven to increase biogas production at both C/N ratios of 25 and 30. Further studies on the C/N ratio, it was found that the C/N ratio of 25 was better than the C/N ratio of 30. This is evident in several variables, including raw and fine substrate conditions, as well as on variables with or without a microbial consortium, with the amount of biogas productivity at a C/N 25 ratio of 53-90.5 % higher than the C/N 30 ratio. © 2023 The Authors. All rights reserved.

关键词： Biogas Biological pretreatment Physical pretreatment Sugarcane bagasse

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Batik Industrial Waste Monitoring and Control System Based on the Internet of Things 5

Batik Industrial Waste Monitoring and Control System Based o...

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5th International Conference on electrical, Electronics, Informatics, and Vocational Education, ICEELINVO 2022

作者： Ali, M. Firdaus, M.F. Electrical Engineering Education Department Faculty of Engineering Universitas Negeri Yogyakarta Indonesia Electrical Study Program Vocational School Universitas Negeri Yogyakarta Indonesia

The aims of this research are to (1) Design and build a Batik Industrial Waste Monitoring and Control System Based on the Internet of Things (BIWMCS -IoT);(2) Test the performance of the BIWMCS-IoT system. The design and implementation of the BIWMCS-IoT system consist of five stages, namely: (1) Needs analysis, (2) Design, consisting of electronic planning, hardware, and software;(3) Development, including hardware and software development;(4) Testing, and (5) implementation. The BIWMCS-IoT system consists of a sensor unit to measure the parameters of water turbidity, temperature, Power of Hydrogen (pH), and the flow velocity of the wastewater then obtained by the microcontroller and the results are sent to the Wi-Fi module to adjust the solenoid valve opening and closing. Based on the testing of the system, has been shown that the BIWMCS-IoT system can work well according to the standards in the Minister of Indonesian Environment Regulation Number 05 of 2014. The reading accuracy of the batik waste monitoring system reaches 96.6% with the delivery time to the smartphone less than 30 seconds. This shows that this system can work well to monitor and control the liquid waste produced by the batik industry. © Published under licence by IOP Publishing Ltd.

关键词： Internet of things

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Arduino and LabVIEW Based Ping-Pong Ball Position Control using PID Controller 17

Arduino and LabVIEW Based Ping-Pong Ball Position Control us...

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17th International Conference on Telecommunication Systems, Services, and Applications, TSSA 2023

作者： Ramelan, Agus Rohman, Febri Abdul Sulistyo, Meiyanto Eko Adriyanto, Feri Sartika, Nike Zakaria, Diky Faculty of Engineering Universitas Sebelas Maret Dept. of Electrical Engineering Surakarta Indonesia UIN Sunan Gunung Djati Bandung Dept. of Electrical Engineering Bandung Indonesia Mechatronics and Artificial Intelligence Study Program Universitas Pendidikan Indonesia Bandung Indonesia

ISBN: (纸本)9798350309164

Industrial development requires accurate and reliable control technology. One of the popular control systems is PID control. This paper discusses the implementation of the PID method for ping-pong ball position control by utilizing the theory of the Coanda effect. The control system was designed using Arduino as the controller and LabVIEW as the control interface. Tests were carried out by combining set point values to determine whether the position control system worked properly or not. The test results show that the PID method combined with LabVIEW can work well with the results of the PID control test at successive heights of 15 cm, 20 cm, 25 cm, 30 cm, and 35 cm obtained rise time (tr) 3.49 seconds, 4.58 seconds, 9.08 sec, 9.92 sec, and 8.84 sec. The average tolerance is 1.5 cm for the upper limit and 1 cm for the lower limit. © 2023 IEEE.

关键词： Position control

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study Case on Implementation Elevator 2 Floor System on PLC OMRON CP1E N30 9

Study Case on Implementation Elevator 2 Floor System on PLC ...

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9th International Conference on Education and Technology, ICET 2023

作者： Habibi, Muhammad Afnan Wibawa, Arif Fadlika, Irham Irfani, Mochamad Farhan Ali Firmansyah, Mohamad Farel Baskoro, Angger Study Program of Power Plant Engineering Technology Malang Indonesia Universitas Negeri Malang Dept. of Electrical Engineering Malang Indonesia National Yang Ming Chiao Tung University Dept. of Electrical Engineering and Computer Science Hsinchu Taiwan

ISBN: (纸本)9798350358292

The swift progression of industrial technology underscores the need for adept professionals capable of skillfully implementing and managing intricate systems. Vocational education assumes a pivotal role in cultivating competent intermediaries proficient in translating theoretical knowledge into practical applications. At the core of industrial automation lies the programmable Logic Controller (PLC), a specialized digital computer that interfaces with sensors, switches, and actuators to execute real-time control programs, thus facilitating meticulous industrial processes. This study concentrates on the practical deployment of a two-floor elevator system utilizing the OMRON CP1E N30 PLC. Elevators, integral to contemporary structures, mandate precision for secure vertical conveyance. Leveraging input signals from elevator buttons, sensors, and switches, the PLC orchestrates efficient motor control and dependable door operations. This hands-on application underscores the PLC's significance within real-time control contexts. Nonetheless, Vocational Higher Education graduates frequently grapple with the challenge of transitioning to industry settings due to limited practical exposure. This partnership harmonizes with the center's objective of enriching vocational education by integrating sophisticated technologies like PLCs, equipping the workforce with the acumen to bridge the gap between theoretical foundations and the pragmatic demands of industry. © 2023 IEEE.

关键词： Elevators

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Tin electronucleation and growth from Sn(II) in nonaqueous solutions based on ethylene glycol: Electrochemical behavior and temperature effect

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Transactions of Nonferrous Metals Society of China 2023年

作者： Kiem Do Van Nguyen Van Hieu Tu Le Manh Faculty of Electrical and Electronic Engineering， Phenikaa University Phenikaa Research and Technology Institute (PRATI)， A&A Green Phoenix Group Faculty of Materials Science and Engineering， Phenikaa Institute for Advanced Study (PIAS)， Phenikaa University

Thermodynamic and kinetic aspects of tin electronucleation and growth processes onto a glassy carbon electrode from SnCl2·2H2O dissolved in ethylene glycol solutions were studied. Typical reduction and oxidation peaks observed in voltammograms have demonstrated the capability of ethylene glycol solutions to electrodeposit Sn. The temperature-dependence of diffusion coefficient values derived from potentiodynamic and potentiostatic studies helped to determine and validate estimations of the activation energy for Sn(II) bulk diffusion. Chronoamperometric results have identified that， the suitable model to describe the early stage of Sn electrodeposition could be composed of Sn three-dimensional nucleation and diffusion-controlled growth and water reduction contributions， which was duly validated by theoretical and experimental approaches. From the model， typical kinetic parameters such as nucleation frequency， A， number density of tin nuclei， N0， and D， were determined. The presence of tin nuclei with excellent quality and their structure were verified using SEM， EDX， and XRD techniques.

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Multi-criteria decision making for nuclear power plant selection using fuzzy AHP:Evidence from Indonesia

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Energy and AI 2023年第4期14卷 99-111页

作者： Ade Gafar Abdullah Mohammad Ali Shafii Syeilendra Pramuditya Topan Setiadipura Kurnia Anzhar Electrical Engineering Study Program Universitas Pendidikan IndonesiaBandungIndonesia Physics Department Andalas UniversityPadangIndonesia Nuclear Science and Engineering Study Program Bandung Institute of TechnologyIndonesia Research Center for Nuclear Reactor Technology National Research and Innovation AgencyIndonesia Pusat Unggulan Ipteks Perguruan Tinggi Technical and Vocational Education and Training Research Center(TVET RC)Universitas Pendidikan IndonesiaIndonesia

In terms of planning aspect,nuclear power plant(NPP)development needs analyses,consideration,and right decision making due to multi criteria *** study prioritizes the best site development of Indonesian NPPs in terms of 21 social,economic,and technical perspectives which comprise transmission network,oper-ating cost,economic impact,geology,geotechnic,seismology,population density,environment,cooling water,meteorology,hydrology,proximity to hazardous facilities,topography,land use,proximity to wetland,evacu-ation route,security,transportation network,legal consideration,impact of tourism,land ownership,historical places,and public acceptance,all identified to be considerations for the best *** Fuzzy algorithms(Chang’s Extent Analysis and Buckley’s Fuzzy AHP)were used to determine the criteria priorities as well as NPP site feasibility of two locations in *** results found that geology,geotechnic,and seismology(SA1);security(SO1),population density(SA2),environment(SA3),and cooling water(SA4)had the highest priorities among the 21 *** on the 5 top priority criteria,West Kalimantan and East Kalimantan provinces serve as the best candidates for the NPP *** an innovative and novel multi criteria Fuzzy AHP–based decision making(MCDM)approach has been proven to become a useful reference to select NPP sites in Indonesia.

关键词： Analytical hierarchy process Fuzzy AHP Multi-criteria decision making Nuclear power plant

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Java Bali Grid Mean Time To Failure Prediction using Machine Learning 1

Java Bali Grid Mean Time To Failure Prediction using Machine...

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1st International Conference on Technology, engineering, and Computing Applications, ICTECA 2023

作者： Sesotyo, Priyo Adi Pandjaitan, M.M. Lanny W. Lukas Universitas Katolik Indonesia Atma Jaya Professional Engineer Study Program Faculty of Engineering Jakarta12930 Indonesia Universitas Semarang Electrical Engineering Dept. Semarang50196 Indonesia Universitas Katolik Indonesia Atma Jaya Electrical Engineering Master Program Jakarta12930 Indonesia Jakarta12930 Indonesia

ISBN: (纸本)9798350360554

The role of Mean Time To Failure (MTTF) is critical to maintain cost-efficient in smart grids, as the predictive maintenance means for ensuring their reliability. Java Bali grid is the most important power network in Indonesia, because it holds 75% energy sales and the foundation of the Indonesian government, business and industrial sectors. One method for prediction in the machine learning is the Linear Regression, as part of the Supervised Learning technique. The regression model extracts the grid overload variable from MV distribution system, where connected load (MVA) divided by the number of MV customers. The model constructs the Linear Regression function, where the slope and intercept values found from the correlation between predicted response and actual response. After confronting the function f(x) and the coefficient of determination (R2), the test results for the MTTF prediction values for Java-Bali's region shows the higher accuracy when the R2 shows highest value. © 2023 IEEE.

关键词： Forecasting

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Measurement of key performance indicator Green Supply Chain Management (GSCM) in palm industry with green SCOR model

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Materials Today: Proceedings 2022年 63卷 S326-S332页

作者： Rosyidah, Masayu Khoirunnisa, Ninin Rofiatin, Umi Asnah, Asnah Andiyan, Andiyan Sari, Dyana Industrial Engineering Study Program Universitas Muhammadiyah South Sumatra Palembang 30263 Indonesia Agribusiness Study Program Faculty of Agriculture University of Tribhuwana Tunggadewi East Java Malang 65144 Indonesia Master of Agricultural Economics Postgraduate School of University of Tribhuwana Tunggadewi East Java Malang 65144 Indonesia Architecture Study Program Faculty of Science and Engineering Universitas Faletehan West Java Bandung 40266 Indonesia

SCOR (Supply Chain Operations Reference) model is a tool for diagnosing Supply Chain Management (SCM) that allows users to understand all processes in a business organization. This study aimed to analyze activities related to Green Supply Chain Management (GSCM), especially in the palm oil sector, and to determine the performance of Green Supply Chain Management (GSCM) at PT. Sutopo Lestari Jaya using the green score model. The results showed that the highest Green Objectives (GO) weight in environmentally friendly garden management was located on protected forest land used as plantation land by 38.82%, while waste minimization was found in Crude palm oil water content of 48%. Meanwhile, in minimizing and handling greenhouse gas emissions, the highest weight is found in the amount of fuel used in Fresh Fruit Bunch (FFB) shipments of 54.07%. For plantation management and palm oil management mills, the highest weight is in the percentage of water use per ton of FFB in PPKS 60.7%, while in waste management, the highest percentage lies in the standardized wastewater Biological Oxygen Demand (BOD) of 38.8%. In maximizing the use of new and renewable energy, the highest weight lies in renewable energy per tonne of FFB and the use of solid waste (empty shells and shells) as a substitute for fossil fuels of 45.5% each. © 2022

关键词： Palm oil

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Multi Task Classification Using Deep Learning Approaches for Big Five Personality Traits Prediction: A Review 11

Multi Task Classification Using Deep Learning Approaches for...

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11th International Conference on Information Technology, Computer and electrical engineering, ICITACEE 2024

作者： Nudin, Salamun Rohman Gernowo, Rahmat Somantri, Maman Wibowo, Adi Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Physics Semarang Indonesia Diponegoro University Faculty of Engineering Department of Electrical Engineering Semarang Indonesia Diponegoro University Faculty of Science and Mathematics Department of Informatics Semarang Indonesia

ISBN: (纸本)9798350389289

This paper presents a comprehensive review of deep learning methods for the Big Five personality traits prediction using multi-task classification. The purpose of the review is to determine the performance of models developed in previous research to describe research opportunities and challenges in the future. The Big Five model is a framework in psychology that categorizes human personality into five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. The review begins by analyzing 22 articles from the science Direct, IEEE Xplore, and Scopus databases by applying screening using the Big Five Personality keywords. Then study the concepts of deep learning for model development such as: input, architecture, method, dataset, and performance to identify the strengths and limitations of each approach. The review results of the highest average accuracy by modality such as unimodal text with essay dataset (80.98%), unimodal image with ImageNet dataset (95.36%), unimodal audio with SSPNet dataset (79.48%), bimodal image and audio with Chalearn Video First Impression dataset (91.67%), multimodal text, image, and audio with Chalearn Video First Impression dataset (91.88%). The average accuracy of the Big Five Personality traits was highest (95.36%) and lowest (59%). This highlights the need for standard benchmarks, interpretable models and interdisciplinary collaboration to improve the accuracy, reliability and ethical implications of personality prediction. Future research is expected to pave the way for advancements in understanding human personality through deep learning approaches using other modalities such as EEG, GSR, and PPG. © 2024 IEEE.

关键词： Contrastive Learning

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DeepCat: A Deep Learning Approach to Understand Your Cat's Body Language 11

DeepCat: A Deep Learning Approach to Understand Your Cat's B...

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11th International Japan-Africa Conference on Electronics, Communications, and Computations, JAC-ECC 2023

作者： Fawzy, Arwa Hassan, Ahmed Gad, Ahmed Zaky, Ahmed B. El-Hussieny, Haitham Alexandria Egypt program Alexandria Egypt Benha University Faculty of Engineering at Shoubra Electrical Engineering Department Egypt Egypt-Japan University of Science and Technology Department of Mechatronics and Robotics Engineering Alexandria Egypt

ISBN: (纸本)9798350369328

Pet owners experience difficulty in understanding their pets' body language and its implications for animal welfare, given that animals cannot utilize human speech to communicate their emotions and health conditions. However, previous experiments for analyzing cat behavior have demonstrated that cats are precisely expressive. DeepCat, a deep-learning approach developed in this study, translates cats' body language signals, enabling owners to discern their feline companions' intended messages and emotional states. Our DeepCat model was trained on a dataset comprising 10,000 cat images, implementing automatic labeling to track key features, including the tail, eyes, and mouth. Presented as a Flutter application, DeepCat can function everywhere, allowing owners to easily monitor their cats and make informed decisions in situations that require caution. This paper discusses the potential benefits and limitations of DeepCat and provides suggestions for future research in this domain. © 2023 IEEE.

关键词： Emotion Recognition

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