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Optimizing dispersion of torrefied spent coffee grounds for enhanced biochar-EVA composite properties through sodium percarbonate-assisted treatment

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Journal of Industrial and engineering Chemistry 2025年

作者： Lee, Kuan-Ting Gabriela, Situmorang Chen, Wei-Hsin Rajendran, Saravanan Selvarajoo, Anurita Department of Chemical and Materials Engineering Tunghai University Taichung407 Taiwan International Master Degree Program on Energy Engineering National Cheng Kung University Tainan701 Taiwan Department of Aeronautics and Astronautics National Cheng Kung University Tainan701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung411 Taiwan Instituto de Alta Investigación Universidad de Tarapacá Arica1000000 Chile Department of Civil Engineering Faculty of Science and Engineering University of Nottingham Malaysia

This study aims to optimize biochar by combining 10 % sodium percarbonate with 90 % spent coffee grounds and torrefying at 300 °C for 30 min. Biochar enhances black color dispersion in a composite when blending the optimal biochar and ethylene vinyl acetate. The maximum carbon content of the optimal biochar is 59.97 %, exhibiting similar dispersion, packing density, pore size, and contact angle to carbon black. The optimal biochar's specific surface area and total pore volume are 7.12 m2·g−1 and 0.0018 cm3·g−1, respectively, 2.9 times and 1.2 times that of untreated torrefied spent coffee grounds with SP treated. The mechanical properties of the composite, which is blended with 15 wt% of the optimal biochar to ethylene vinyl acetate through trade-off analysis, indicate a tensile strength and Young's modulus of 1.03 MPa and 9.69 MPa, respectively. As the amount of blended optimal biochar increases, the tensile strength decreases while Young's modulus increases. Compared with a composite blended with the same 15 wt% of carbon black, the tensile strength and Young's modulus are 0.77 MPa and 9.55 MPa, respectively. In conclusion, the optimal biochar is a potential alternative material that could replace carbon black. This finding aligns with the developmental direction of achieving negative carbon emissions, promoting a circular economy and valorizing waste. © 2025 The Korean Society of Industrial and engineering Chemistry

关键词： Tensile strength

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The ultimate strength characteristics on double hull oil tanker 2

The ultimate strength characteristics on double hull oil tan...

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2nd International Conference of Interdisciplinary Research on Green Environmental Approach for Sustainable Development, ICROEST 2020

作者： Lukman, Arlinda Verawati Juswan Alie, Muhammad Zubair Muis Wulandari, Amalia Ika Department of Ocean Engineering Engineering Faculty Universitas Hasanuddin Makassar Indonesia Naval Engineering Study Program Institut Teknologi Kalimantan Kalimantan Timur Indonesia

A double hull tanker is one of the specific ships where the payload is liquid. The payload is an internal load and gives pressure inside the cargo hold. Besides, the external load like wave act simultaneously on the ship during the voyage. Therefore, the ultimate strength of the ship caused by the internal and external loads must be investigated. The objective of the present study is to investigate the ultimate strength characteristic of double hull oil tankers under hogging and sagging conditions. The cross-section of the double hull tanker is modeled using the finite element method to analyze the ultimate strength. The master node is applied to both sides of the cross-section to know the characteristic of the hull girder under hogging and sagging conditions. One side of the master node is constrained, and the other one is given by rotational force. The analytical method is performed, and the result obtained by the numerical method is then compared, including their characteristic in terms of moment-curvature relationship and deformation. © Published under licence by IOP Publishing Ltd.

关键词： Numerical methods

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Renewable energy potential of rice straw and paunch manure as bioethanol feedstocks in Central Java, Indonesia

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Case Studies in chemical and Environmental engineering 2024年 9卷

作者： Arianti, Forita Dyah Triastono, Joko Pertiwi, Miranti Dian Prabowo, Agung Prasetyo, Teguh Chanifah Haryanto, Bambang Megawati Astuti, Widi Djarot, Ira Nurhayati Santoso, Arif Dwi Wijayanti, Sri Peni Research Center for Sustainable Production System and Life Cycle Assessment National Research and Innovation Agency Banten 15314 Indonesia Research Center for Behavioral and Circular Economics National Research and Innovation Agency Jakarta 12710 Indonesia Chemical Engineering Study Program Faculty of Engineering E1 Building 2nd floor Semarang Negeri Semarang Semarang 50229 Indonesia

Almost all farmers are unaware that rice straw and paunch manure are potential feedstocks for bioethanol besides organic fertilizer, biochar, and biogas. Farmers' perceptions regarding the multiattributes of bioethanol development are still underestimated, indicating that farmers are still indecisive about the potential use of rice straw and paunch manure as feedstock for bioethanol. They still need extension and training to improve their knowledge. The Location Quotient (LQ) value of rice straw and cattle paunch manure is > 1, indicating that Karanganyar Regency could become a base for bioethanol development from rice straw and cattle paunch manure. © 2024 The Authors

关键词： Bioethanol Farmer's perception Location quotient Paunch manure Renewable energy Rice straw

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Customer Segment Classification Prediction in the Australian Retail Based on Machine Learning Algorithms 23

Customer Segment Classification Prediction in the Australian...

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Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application

作者： Yiming Luo Rui Zhang Fei Wang Tao Wei Business Schoo The University of Sydney Austialia Computer and information sciences program Harrisburg University of Science and Technology United States Faculty of Science and Technology Beijing Normal University-Hong Kong Baptist University United International College China School of Chemical and Environmental Engineering Sichuan University of Science & Engineering China

ISBN: (纸本)9798400709449

Customer segmentation is an essential area of business analytics today. Accurate customer segmentation is access to improves the efficiency of marketing campaigns and customer satisfaction. This study employs multiple machine learning methods to classify Australian Retail company BIGW's customer segments and first to apply multiple model explanation methods to find insights related to customer segmentation identification. After rigorous comparison and hyperparameter fine-tuning, XGBoost is the most adept for this dataset. We derive three key insights through the model results and model interpretive methods. First, BIGW's primary clientele comprises young families in urban areas who prefer cost-effective products, establishing the foundation of their consumer base. Second, the model result indicates a notable gap in BIGW's understanding of its high-end customers, suggesting an area for immediate attention. Third, a specific customer segment emerges from the data: individuals favoring online shopping, demonstrating high total expenditure but low interest in promotions, representing a high-value segment.

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Digital Forensics Investigation and Incident Response in Internet of Things (IoT-DFIR): Challenges and Models

Digital Forensics Investigation and Incident Response in Int...

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International Conference on Wireless and Telematics (ICWT)

作者： Syaiful Ahdan Eki Ahmad Zaki Hamidi Sampurna Dadi Riskiono Ridha Muldina Negara Ratna Mayasari Suci Ramadona Ade Nurhayati Adi Sucipto Jupriyadi Galih Nugraha Nurkahfi Dzata Farahiyah Muchammad Naseer Faculty of Engineering & Computer Science Universitas Teknokrat Indonesia Lampung Indonesia Electrical Engineering Department UIN Sunan Gunung Djati Bandung Bandung Indonesia School of Electrical Engineering Telkom University Bandung Indonesia Elearical Engineering Study Program Politeknik Caltex Riau Riau Indonesia Faculty of Engineering Institut Teknologi Telkom Jakarta Jakarta Indonesia National Research and Innovation Agency (BRIN) Bandung Indonesia Faculty of Industrial Technology Universitas Islam Indonesia Yogyakarta Yogyakarta Indonesia Informatics Department Sekolah Tinggi Teknologi Bandung Bandung Indonesia

Many different industries are currently making substantial use of the Internet of Things (IoT). IoT is the process through which electronic devices communicate with their surrounding virtual environment by continuously exchanging data via sensors. Due to increased IoT security concerns, digital forensic investigators now possess greater knowledge and abilities to investigate IoT devices. IoT-DigFor are required in terms of cybercrime due to the rapid growth in the number of electronic devices and the collection and consumption of enormous amounts of data. IoT systems with billions of devices have produced a significant amount of evidence, which presents a significant challenge to digital investigators and practitioners who must connect with IoT devices to conduct fast and thorough investigations into cybercrimes. This article presents detailed information about forensics in the IoT environment. The IoT forensic paradigm and the challenges that design-based security requirements and IoT system security offer for IoT-DigFor are covered in great detail at the beginning of the article.

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An alternative model of retaining walls on sandy area to prevent landslides 4

An alternative model of retaining walls on sandy area to pre...

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4th International Conference on Earthquake engineering and Disaster Mitigation, ICEEDM 2019

作者： Mazni, Deni Irda Doctoral Program Dept. of Civil Eng. Faculty of Engineering Andalas University Indonesia Civil Engineering Study Program Universitas Dharma Andalas Indonesia

Landslide is one of the potential disasters that can take life and material. A way to reduce disaster risk in slopes is to improve slope stability. A challenge in improving slope stability is how to make soil retaining walls that are simple, quickly built, and workable in the process. This research focuses on laboratory tests of gravity, segmental, and pre-cast retaining walls in sands. The tested models are slopes with different segmental, pre-cast, gravity walls made of un-reinforced concrete for static loads. The slope failure patterns were observed with their load variations. There are two wall models segmental. Each segmental wall observed a collapse pattern that occurred behind the wall. Static loading is carried out step by step until collapse occurs in the segmental wall. Observations and defects are carried out during the load process until the segmental wall collapses. This research shows that segmental pre-cast retaining walls with specific models and sizes can be selected to support certainly given loads to prevent slope failure. © 2020 The Authors, published by EDP Sciences.

关键词： Landslides

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Blue carbon dynamics in mangroves and conservation of their services in the Coral Triangle Ecoregion, Southeast Sulawesi, Indonesia 2

Blue carbon dynamics in mangroves and conservation of their ...

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2nd Workshop on engineering, Education, Applied Sciences and Technology, WEAST 2020

作者： Analuddin, Kangkuso Kadidae, La Ode Muhammad Yasir, La Ode Septiana, Andi Syahrir, La Rahim, Saban Pratama, David Fajar, L.D. Abdul Nadaoka, Kazuo Biotechnology Study Program Halu Oleo University Kendari Indonesia Chemistry Study Program Halu Oleo University Kendari Indonesia Marine Science Study Program Halu Oleo University Kendari Indonesia Fisheries Science Postgraduate Program Halu Oleo University Kendari Indonesia Geography Study Program Halu Oleo University Kendari Indonesia Chemistry Science Postgraduate Program Halu Oleo University Kendari Indonesia Marine and Fisheries Faculty Sebelas November University Kolaka Indonesia Dept. of Trans-disciplinary Science and Engineering Tokyo Institute of Technology Japan

Coral triangle eco-region is hotspot of coastal blue carbon, and contributes to the global carbon cycling. This study aimed to elucidate the blue carbon dynamics in mangroves and their importance services as source of blue carbon in the coastal zone of coral triangle ecoregion. The blue carbon content in mangrove sediment was analyzed, while blue carbon production and its export frommangroves leaf litterfallwasestimated. The results showed that the blue carbon content in mangrove sediment was significantly higher in deep of 40-50 cm than other layers(P © 2021 Published under licence by IOP Publishing Ltd.

关键词： Carbon

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Artificial Intelligence in Cancer Immunotherapy: Navigating Challenges and Unlocking Opportunities

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engineering 2025年第1期44卷 12-16页

作者： Xiang, Wei Yu, Lu Chen, Xiaoyuan Herold, Marco J. Australian Centre for Artificial Intelligence in Medical Innovation La Trobe University MelbourneVIC3086 Australia School of Computing Engineering and Mathematical Sciences La Trobe University MelbourneVIC3086 Australia Department of Diagnostic Radiology Yong Loo Lin School of Medicine National University of Singapore Singapore119074 Singapore Department of Chemical and Biomolecular Engineering College of Design and Engineering National University of Singapore Singapore117575 Singapore Department of Biomedical Engineering College of Design and Engineering National University of Singapore Singapore117575 Singapore Department of Pharmacy and Pharmaceutical Sciences Faculty of Science National University of Singapore Singapore117544 Singapore Clinical Imaging Research Centre Centre for Translational Medicine Yong Loo Lin School of Medicine National University of Singapore Singapore117599 Singapore Nanomedicine Translational Research Program Yong Loo Lin School of Medicine National University of Singapore Singapore117597 Singapore Yong Loo Lin School of Medicine National University of Singapore Singapore138667 Singapore Singapore138673 Singapore Olivia Newton-John Cancer Research Institute HeidelbergVIC3084 Australia School of Cancer Medicine La Trobe University MelbourneVIC3086 Australia The Walter and Eliza Hall Institute of Medical Research ParkvilleVIC3052 Australia Department of Medical Biology University of Melbourne ParkvilleVIC3010 Australia

Cancer continues to be a major cause of global mortality rates, with conventional treatments such as chemotherapy and radiotherapy exhibiting inconsistent efficacy, high costs, and considerable side effects. Over the past decade, a promising alternative has emerged: cancer immunotherapy, which leverages the body’s immune system to identify and eradicate cancer cells. Significant progress has been made in several novel immunotherapies, including immune checkpoint inhibitors (ICIs), chimeric antigen receptor T-cell therapies, and personalized therapeutic cancer vaccines. However, the heterogeneity and complexity of cancer types still pose enormous challenges. The efficient use of large numbers of medical datasets is essential for overcoming these obstacles. Without artificial intelligence (AI), linking translational and clinical data to derive meaningful insights would remain an insurmountable task. Recently, single-cell RNA sequencing cell typing (scGPT), a pretrained generative model utilizing a database of more than 33 million cells, is developed to accurately extract important biological insights concerning cellular biology. A personalized learning workflow is also proposed as a simple and effective pipeline to discover neoantigens for cancer immunotherapy.

关键词： intelligence immunotherapy cancer artificial challenges navigating opportunities unlocking

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Identification of Beef Freshness Using Linear Discriminant Analysis (LDA) Algorithm and Extraction of HSV Values

Identification of Beef Freshness Using Linear Discriminant A...

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Electronic and Electrical engineering and Intelligent System (ICE3IS), International Conference on

作者： Riduwan Napianto Agung Tri Prastowo Agung Deni Wahyudi Wajiran Yohanes Egi Pratama Yudoutomo Arico Ayani Suparto Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandarlampung Indonesia Information Technology Education Study Program STKIP PGRI Situbondo Situbondo Indonesia

ISBN: (纸本)9781665465427

To determine the quality of beef, it is usually seen using a flashlight and matching it with a predetermined color standard. However, this method is time consuming and the results are inconsistent due to human visual limitations. This study aims to identify the freshness of beef based on its color characteristics using feature extraction method with HSV and LDA method for identification. The identification process begins with the transformation process from RGB images to L*a*b, then image segmentation serves to separate one object from another and image identification uses the LDA method with feature extraction using HSV. The use of color feature extraction with the HSV algorithm to assist in obtaining information from the colors contained in the image for easy identification. Furthermore, the LDA algorithm has a function to obtain the maximum projection to obtain a smaller dimensional space so that the desired patterns can be separated through the boundary line of a linear equation so as to form a certain class or group. Based on the test results using the confusion matrix, it produces a precision value of 80%, recall of 84%, and accuracy of 82%.

关键词： Visualization Image segmentation Image color analysis Shape Feature extraction Mathematical models Linear discriminant analysis

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Wind farm sites selection using GIS and multi-criteria analysis: The case of Sumba Island - Indonesia

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AIP Conference Proceedings 2024年第1期2744卷

作者： Zul Afief Akbar Dewi Kania Sari Geodetic Engineering Study Program Faculty of Civil Engineering and Planning Institut Teknologi Nasional Bandung Indonesia

Renewable energy has grown rapidly nowadays. One of them is wind energy which also has been developed in Indonesia. One of the major technical challenges for wind energy development is to locate the areas with high suitability for placing wind farms, so finding suitable locations is critical for the economic success of wind farm operation. In the past few decades, Geographic Information Systems (GIS) have been widely used to assist for locating suitable sites for wind farms. In this study, GIS and multi-criteria decision analysis were used to select the suitable location for the wind farms in Sumba Island, Indonesia. There were five criteria used in the method, including distance to road, population density, wind potential, land use, slope, and added with exclusionary areas. The weighted overlay was used as the method to find the suitability wind farm sites with the concerns of geospatial layers related to the criteria. The resulted suitability map for the wind farm development in the study area gave five categories of suitability levels: unsuitable, very low, low, medium and high. Research results showed that around 21.5% area of Sumba Island fell into medium and high suitability levels. The method used in this study, if used with care, can be applied to other areas with a similar background.

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