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Activated Carbon for Supercapacitor Electrodes Produced by the Carbonation and Activation of Glucose with Potassium Nitrate

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ACS Applied Energy Materials 2024年第16期7卷 6873-6886页

作者： Wu, Chih-Yung Chang, Chia-Yu Tsai, Shu-Wei Lin, Shang-Chih Hsu, Tien-Chiu Hsieh, Tzu-Hsien Department of Aeronautics and Astronautics National Cheng Kung University Tainan701401 Taiwan International Degree Program on Energy in Engineering National Cheng Kung University Tainan701401 Taiwan Institute of Space Systems Engineering National Cheng Kung University Tainan701401 Taiwan Green Technology Research Institute CPC Corporation Kaohsiung Taiwan811251 Taiwan

The preparation of activated carbon has long been a subject of interest for researchers aiming to develop a straightforward and environmentally friendly method. This study introduces an approach for carbonizing glucose using potassium nitrate to ignite and carbonize glucose, resulting in the production of fluffy carbon. Activated carbon suitable for supercapacitor production can be obtained through postprocessing involving calcination and pickling. An important feature of this method is that it does not require the use of a strong alkali, such as potassium hydroxide, for the activation reaction following carbonization. Based on experimental results, optimal activated carbon is produced when the proportion of potassium nitrate in the feedstock is 50%. Furthermore, activated carbon with superior physical characteristics can be utilized in the assembly of organic electrolyte supercapacitors, and their electrical properties can be analyzed. The results indicate that the supercapacitor assembled by using activated carbon with 50% potassium nitrate in the raw material demonstrates the best performance. Its cyclic voltammetry (CV) curve approximates a rectangle and exhibits an almost vertical curve at low frequencies in the Nyquist plot. Additionally, for the analysis of the galvanostatic charge-discharge behavior of the supercapacitor, the curve maintains an equilateral triangle pattern even at a current density of 5A/g. The results also show that the best supercapacitor achieves 38.41 and 153.66 F/g for capacitor-specific capacitance and electrode-specific capacitance, respectively. © 2024 The Authors. Published by American Chemical Society.

关键词： Potassium hydroxide

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Mammogram Breast Cancer Classification Based on Deep-Convolutional Neural Network

Mammogram Breast Cancer Classification Based on Deep-Convolu...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Amadea, Avissa Aurellia Sari, Christy Atika Rachmawanto, Eko Hari Sari, Wellia Shinta Noori, Mohammed S. Alkhafaji, Mohamed Ayad University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia University of Dian Nuswantoro Study Program in Information Systems Semarang Indonesia Northern Technical University Department of Computer Engineering Technology Mosul Iraq National University of Science and Technology Department of Computer Science DhiQar Iraq

ISBN: (纸本)9798350339215

Based on WHO's data, breast cancer is one of the most deadly diseases that has claimed many victims, especially women. This disease begins with the presence of an undetected and eventually turns into malignant (cancer). This happens due to ignorance of the importance of having a medical check-up even though in good health. Doctors and researchers can prevent the development of tumor cells through treatment that begins with radiological examinations to identify the possibility of a person being affected by this disease. One of the most frequently used techniques is Mammography. This technique can detect the presence of tumor cells using advanced technology and several methods in displaying the patient's diagnostic results on low-dose X-rays in the form of mammogram images. The technology is inseparable from the methods used to identify the presence of tumor cells. In this study, we have proposed the CNN method based on the deep-CNN model to identify mammogram images in the detection of breast cancer cells with average evaluation results in terms of accuracy, precision, recall, specificity, and f-measure on mammogram image datasets of 99.52%, 99.72%, 99.31%, 99.72%, and 99.5%. These results showed that this method has a good performance in breast cancer detection. © 2023 IEEE.

关键词： Diseases

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Effect of Sn addition on electrochemical activity of ribbons of Mg-Al-Ca anode material for rechargeable magnesium batteries fabricated by rapid solidification

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Keikinzoku/Journal of Japan Institute of Light Metals 2025年第1期75卷 9-13页

作者： Fukuta, Yoshitaka Kikura, Kensei Tsukeda, Tadayoshi Aida, Tetsuo Tabata, Hironobu Kurihara, Hideki Suzuki, Mayumi Program of Materials Science and Engineering Studies in Science and Engineering Graduate School of Science and Engineering University of Toyama 3190 Gofuku Toyama-shi Toyama930-8555 Japan Graduate School of Science and Engineering University of Toyama Toyama-shi Toyama Japan Faculty of Sustainable Design Academic Assembly University of Toyama Toyama-shi Toyama Japan CHUETSU METAL WORKS CO. LTD. Nakaniikawagun Toyama Japan Saitama Industrial technology Center Kawaguchi-shi Saitama Japan Department of Mechanical Systems Engineering Faculty of Engineering Toyama Prefectural University Imizu-shi Toyama Japan

Magnesium-based batteries are potential candidates for next-generation rechargeable batteries due to the divalent nature of magnesium cations and the natural abundance of magnesium resources. In this study, the electrochemical activity of Mg-6mass%Al-3mass%Ca anodes combined with Sn was investigated. Thin ribbons of the anode specimens were prepared by a single-roll rapid solidification method. The results showed that the electrochemical activity increased upon adding 1 mass% Sn, while it decreased for 3 mass% Sn. Based on the results of an X-ray diffraction analysis, the addition of Sn led to the formation of Mg2Sn and Ca2Sn phases, which increased the lattice distortion. Scanning electron microscopy observations indicated that these secondary phases were homogeneously distributed for 1 mass% Sn addition, while they were coarsely distributed for 3 mass% Sn. © 2025 The Japan Institute of Light Metals.

关键词： X ray diffraction analysis

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Aerodynamic Effects Compensation on Multi-Rotor UAVs Based on a Neural Network Control Allocation Approach

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IEEE/CAA Journal of Automatica Sinica 2022年第2期9卷 295-312页

作者： Sarah P.Madruga Augusto H.B.M.Tavares Saulo O.D.Luiz Tiago P.do Nascimento Antonio Marcus N.Lima Graduate Program of Electrical Engineering Universidade Federal de Campina GrandeCampina Grande-PBBrazil Department of Electrical Engineering Universidade Federal de Campina GrandeCampina Grande-PBBrazil IEEE Department of Computer Systems Universidade Federal da ParaibaJoao Pessoa-PBBrazil

This paper shows that the aerodynamic effects can be compensated in a quadrotor system by means of a control allocation approach using neural ***,the system performance can be improved by replacing the classic allocation matrix,without using the aerodynamic inflow equations *** network training is performed offline,which requires low computational *** target system is a Parrot MAMBO drone whose flight control is composed of PD-PID controllers followed by the proposed neural network control allocation *** a quadrotor is particularly susceptible to the aerodynamics effects of interest to this work,because of its small *** compared the mechanical torques commanded by the flight controller,i.e.,the control input,to those actually generated by the actuators and established at the *** was observed that the proposed neural network was able to closely match them,while the classic allocation matrix could not achieve *** allocation error was also determined in both ***,the closed-loop performance also improved with the use of the proposed neural network control allocation,as well as the quality of the thrust and torque signals,in which we perceived a much less noisy behavior.

关键词： Aerodynamics effects control allocation minidrone multi-rotor UAV neural networks

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Optimizing Menu Bundling Strategies Through Apriori Algorithm in Sales Analysis

Optimizing Menu Bundling Strategies Through Apriori Algorith...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Ahmad Sambang Setya Tama Faqih Hamami Taufik Nur Adi Information Systems Study Program Faculty of Industrial Engineering Telkom University Bandung Indonesia

ISBN: (数字)9798331506490

ISBN: (纸本)9798331506506

Indonesia, as one of the largest coffee producers and exporters in the world, has experienced significant growth in the number of coffee shops, driven by increasing consumer demand for ready-to-drink coffee. This study aims to enhance sales performance at Authen Café and Space through the implementation of a menu bundling strategy. By utilizing data mining techniques and the Apriori algorithm, customer purchasing patterns were analyzed to identify optimal menu combinations. The data was collected directly at Authen Cafe during the period from April to August 2028. The analysis revealed that bundling strategies, such as combining Ayam Rica-Rica with Es Kopi Susu Karamel, are effective in increasing sales volume and product popularity among consumers. Furthermore, this study evaluated the impact of offering discounts on bundled packages on the café's profitability, demonstrating that this approach can boost net profit without sacrificing profit margins. This research provides significant insights into the application of data-driven marketing strategies within the café'industry and offers guidance for more effective managerial decision-making.

关键词： Industries Consumer behavior Profitability Computational modeling Decision making Data models Association rule learning

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Optimizing Neural Networks for Academic Performance Classification Using Feature Selection and Resampling Approach

Mendel

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Mendel 2023年第2期29卷 261-272页

作者： Supriyadi, Didi Purwanto, Purwanto Warsito, Budi Doctorate Program of Information Systems School of Postgraduate Studies Universitas Diponegoro Semarang Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Diponegoro Semarang Indonesia Department of Statistics Faculty of Science and Mathematics Universitas Diponegoro Semarang Indonesia Department of Information System Faculty of Informatics Institut Teknologi Telkom Purwokerto Banyumas Indonesia

The features present in large datasets significantly affect the performance of machine learning models. Redundant and irrelevant features will be rejected and cause a decrease in machine learning model performance. This paper proposes HyFeS-ROS-ANN: Hybrid Feature Selection and Resampling combination method for binary classification using artificial neural network multilayer perceptron (MLP). The first stage of this approach is to use a combination of two feature selection methods to select essential features that are highly correlated with model performance. The second stage of this approach is to use a combination of resampling methods to handle unbalanced data classes. Both approaches are applied to the academic performance classification model using the MLP neural network. This research dataset is obtained using three-dimensional (3D) frameworks such as the Big Five Personality to determine the Personality that affects academic performance from the student dimension, the Family Influence Scale (FIS), which measures factors that affect academic performance from the family dimension, and Higher Education Institutions Service Quality (HEISQUAL) to measure service quality and its influence on academic performance from the Education institution dimension. Previous research shows that the CoR-ANN algorithm has a model accuracy rate of 94%. The research results based on the dataset show that our proposed method can improve accuracy by selecting more relevant and essential features in improving model performance. The results show that the features are reduced from 135 to 108, while the HyFS-ROS-ANN model for binary classification accuracy increases to 100%. © 2023, Brno University of Technology. All rights reserved.

关键词： Feature Selection

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Synthesis of Zeolite from Waste Concrete Powder

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Funtai Oyobi Fummatsu Yakin/Journal of the Japan Society of Powder and Powder Metallurgy 2022年第5期69卷 208-212页

作者： Harada, Satori Kanda, Yasuyuki Mechanical Systems Engineering Course Graduate School of University of the Ryukyus 1 Senbaru Nishihara-cho Nakagami-gun Okinawa903-0213 Japan Mechanical Engineering Program School of Engineering Faculty of Engineering University of the Ryukyus 1 Senbaru Nishihara-cho Nakagami-gun Okinawa903-0213 Japan

This study investigated the conditions for zeolite synthesis from waste concrete powder (WCP) using the hydrothermal synthesis method. The WCP was prepared by milling the waste concrete using pot mill equipment. The synthesis conditions, i.e., the heating time, heating temperature, and NaOH solution concentration were varied. Furthermore, hydrochloric acid-treated WCP (WCP-HCl), which is removed the calcium component, was prepared to examine the effectiveness of acid treatment in the zeolite synthesis. The zeolite synthesis was investigated using X ray diffraction (XRD) and scanning electron microscopy (SEM). Analcime-type zeolite was synthesized using WCP and WCP-HCl. The requirements of synthesis conditions for analcime were as follows: heating time above 12 h, heating temperature above 433 K, and NaOH solution concentration above 2 mol/ L. With a progressive increase in the concentration of the NaOH solution from 5 to 7 mol/L, analcime could be synthesized at NaOH concentrations below 4 mol/L, while cancrinite was synthesized at NaOH concentrations exceeding 5 mol/L. The peak intensity of analcime and cancrinite of WCP-HCl showed high value in comparison to the WCP. Thus, the effectiveness of the HCl treatment of WCP was confirmed from the XRD patterns. ©2022 Japan Society of Powder and Powder Metallurgy.

关键词： Hydrothermal synthesis

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RECRUITING AND TRAINING THE FUTURE WORKFORCE IN ADVANCED MANUFACTURING CAPABILITIES: A CASE STUDY FROM THE TAMPA BAY

RECRUITING AND TRAINING THE FUTURE WORKFORCE IN ADVANCED MAN...

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ASME 2024 International Mechanical engineering Congress and Exposition, IMECE 2024

作者： Amjad, Muhammad Saad Singh, Pallavi Zapata, Valerie Barger, Marilyn Diaz-Elsayed, Nancy Smart and Sustainable Systems Laboratory Department of Mechanical Engineering University of South Florida TampaFL33620 United States Department of Electrical Engineering University of South Florida TampaFL33620 United States Florida Advanced Technological Education Center TampaFL33619 United States Introduction to Production Systems Certificate Program College of Engineering University of South Florida TampaFL33620 United States

ISBN: (纸本)9780791888650

The manufacturing sector is of paramount importance to a nation’s economy, as it creates employment opportunities, fosters innovation and enhances the competitive advantage in global markets. With the introduction of smart manufacturing technologies, the manufacturing sector has been able to boost its production performance, however, there is a skill gap that the manufacturing sector is facing when it comes to hiring a trained workforce. The US National Strategy for Advanced Manufacturing has underlined the importance of training an advanced manufacturing workforce with an opportunity to support historically underrepresented and underserved communities. We report the outcomes of a manufacturing training certificate program that is designed to provide equitable opportunities for high-quality, industry-relevant training that can lead to sustainable employment and economic growth. A holistic curriculum was developed to teach manufacturing education including CAD, CAM, 3D printing, AR/VR technologies, robotics and automation, assembly and production lines, and measurement systems. We report the outcomes of two cohorts that graduated in Summer 2023 and Fall 2023, in which a total of 86 training sessions were conducted. Twenty-five students enrolled and 17 students (14 males and 3 females) graduated across the two cohorts - among the graduates 47% identified as Hispanic or Latino, 41% identified as African American, and the rest identified as non-white/Hispanic;16 of the graduates belonged to the low-to-middle income category. In the future, the program can be further expanded to include on the job training opportunities with local employers. We also provide recommendations to improve the learning experience of the students and enhance participation in the program. © 2024 American Society of Mechanical Engineers (ASME). All rights reserved.

关键词： Students

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Impact of Dynamic Slab Insulation on Energy Performance of Residential Buildings

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Journal of engineering for Sustainable Buildings and Cities 2022年第4期3卷 041001页

作者： Rajabi, Roya Dehwah, Ammar H.A. Krarti, Moncef Engineering Center CEAE Department University of Colorado Boulder 80309 CO United States Building Systems Program CEAE Department University of Colorado Boulder 80309 CO United States Building Systems Program University of Colorado Boulder 80309 CO United States

In this paper, the energy efficiency potential of applying novel dynamic insulation systems to slab foundations is investigated for residential buildings. Specifically, dynamic insulation allows the foundation to change its thermal resistance to reduce both heating and cooling thermal loads compared to static insulation systems. The energy benefits of the dynamic insulation are evaluated using a validated numerical model integrated with a state-of-art whole-building simulation tool. Specifically, optimal settings for slab-integrated dynamic insulation are determined monthly to reduce heating and cooling thermal loads while maintaining thermal comfort for a prototypical house located in representative US climates. The analysis results indicate that the deployment of slab-integrated dynamic insulation can reduce heating energy by 10% and cooling energy by 39%, and total heating, ventilating, and air conditioning end-use by up to 12%, especially for houses located in cold climates. Copyright © 2022 by ASME.

关键词： dynamic systems energy efficiency heating and cooling loads optimal controls ranch house slab foundation switchable insulation systems

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Effect of Cu addition on electrochemical activity of ribbons of Mg-Al-Ca anode materials for magnesium rechargeable batteries manufactured by rapid solidification method

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Keikinzoku/Journal of Japan Institute of Light Metals 2024年第1期74卷 14-17页

作者： Fukui, Shunsaku Tsukeda, Tadayoshi Aida, Tetsuo Tabata, Hironobu Kurihara, Hideki Suzuki, Mayumi Program of Materials Science and Engineering Studies in Science and Engineering Graduate School of Science and Engineering University of Toyama 3190 Gofuku Toyama-shi Toyama930-8555 Japan Faculty of Sustainable Design Academic Assembly University of Toyama Toyama-shi Toyama Japan CHUETSU METAL WORKS CO. LTD. Nakaniikawa-gun Toyama Japan Saitama Industrial Technology Center Kawaguchi Kawaguchi-shi Saitama Japan Department of Mechanical Systems Engineering Faculty of Engineering Toyama Prefectural University Imizu-shi Toyama Japan

The potential for magnesium storage batteries to become the next generation of rechargeable batteries is high. This is largely due to the abundance of magnesium metal resources and their high safety and electric capacity per volume. Our research team has been studying magnesium alloys as anode materials for these batteries. Specifically, we have been investigating the electrochemical activity and mechanism of adding copper to Mg-9mass%Al and Mg-9mass%Al-3mass%Ca. Our findings indicate that the electrochemical activity increased with the addition of 1mass%Cu, but decreased with the addition of 3mass%Cu. In addition, changes in lattice constant and basal orientation were also observed. These changes decreased with 1mass%Cu and increased with 3mass%Cu. SEM observations showed that the cell delimitation was indistinct for the 1%Cu addition. © 2024 The Japan Institute of Light Metals.

关键词： Secondary batteries

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