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Optimization of microwave-assisted extraction in the purification of triglycerides from non-edible crude Calophyllum inophyllum oil as biodiesel feedstock using artificial intelligence

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South African Journal of Chemical engineering 2024年 47卷 312-321页

作者： Azhar, Badril Gunawan, Setiyo Muharja, Maktum Avian, Cries Satrio, Dendy Aparamarta, Hakun W. Department of Chemical Engineering Institut Teknologi Sepuluh Nopember (ITS) Surabaya 60111 Indonesia Department of Chemical Engineering Faculty of Engineering University of Jember Kalimantan 37 Jember 68121 Indonesia Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei 10607 Taiwan Department of Ocean Engineering Institut Teknologi Sepuluh Nopember (ITS) Surabaya 60111 Indonesia

Crude nyamplung Calophyllum inophyllum is a potential non-edible feedstock for biodiesel production. Calophyllum Inophyllum oil (CCIO) is a non-edible oil that has a high content of triglyceride (TG) and free fatty acid (FFA). This study aims to optimize microwave-assisted power and extraction time of triglyceride purification from C. inophyllum crude oil for biodiesel. This work deployed Artificial Intelligence (AI) algorithms consisting of eight Machine Learning (ML) algorithms and found the most accurate model, then optimized using the Particle Swarm Optimization (PSO) *** result of machine learning modelling Random Forest achieved higher accuracy in R-Square and lower Mean Square Error (MSE) than any other models. Overall, in R-Square average across all variables was 0.949 ± 0.026 and the MSE average of 0.097 ± 0.068. This result can be interpreted as a mean deviation between the predicted value and an accurate value of less than 0.1 for all variables. The optimum of the TG compound resulted in the power of 462.3 W and time of 39.12 min that equalled at 84.02% and FFA equalled at 6.92%. The TG have increased by 11% from the reference range, which states conventional methods from crude oil. Comparison with the MAE method has a minimum fitness value difference of 0.0006 but has a smaller accuracy of less than 1%. Implementing this prediction and optimization method can shorten the extraction time by 5.8 min and reduce energy consumption or system work by 130 kJ. This method can be used for input parameter model prediction and parameter optimization in purification for biodiesel feedstock. Further research can be carried out using other artificial intelligence methods to optimize biodiesel production. © 2023 The Author(s)

关键词： Biodiesel Calophyllum inophyllum Machine learning Microwave-assisted extraction PSO

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A 7nm-Based Decodable Self-Resetting Regfile Circuit 15

A 7nm-Based Decodable Self-Resetting Regfile Circuit

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15th IEEE International Conference on ASIC, ASICON 2023

作者： Zhao, Wanlong Zhang, Yuejun Ren, Mingze Wen, Liang Wang, Pengjun Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo China Ningbo University Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China China Coast Guard Academy Department of Electronic Technology Ningbo China Wenzhou University College of Electrical and Electronic Engineering Wenzhou325035 China

ISBN: (纸本)9798350312980

This paper presents a novel design scheme for a decodable self-resetting Regfile circuit that aims to reduce the power consumption caused by massive data and high computing power. The scheme consists of three steps: first, it analyzes the working principle and the energy consumption process of the decoding circuit;second, it proposes a self-resetting decoding circuit structure that uses the clock to control the decoding state and automatically resets when the clock is low, thus avoiding the extra power consumption due to the inversion of the memory cell state during the non-working period of the decoding circuit;third, it implements a two-read, two-write, decodable self-resetting Regfile circuit using a full-custom design method under the TSMC 7nm FinFET process. The experimental results demonstrate that the circuit has an area of 5593μm2 and an energy-delay product of 0.41pJ•nS, and it can operate stably at 4GHz under various temperatures and process corner conditions. © 2023 IEEE.

关键词： 7nm process high speed low power consumption Regfile circuit

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A Portable 3D-Printed Dielectric Lens Antennas for Liquid-Mixture Characterization

A Portable 3D-Printed Dielectric Lens Antennas for Liquid-Mi...

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2023 IEEE International Symposium on Antennas and Propagation, ISAP 2023

作者： Sangpet, Patchadaporn Thaiwirot, Wanwisa Chudpooti, Sukanya Akkaraekthalin, Prayoot Somjit, Nutapong Chudpooti, Nonchanutt Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut’s University of Technology North Bangkok Bangkok Thailand Department of Industrial Physics and Medical Instrumentation Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand School of Electronic and Electrical Engineering University of Leeds Leeds United Kingdom

ISBN: (纸本)9798350341140

The Fused Deposition Modeling (FDM) method is utilized in this research to present dielectric lens antennas that were 3D printed. The ultra-wideband (UWB) stub antenna's antenna characteristic is intended to be improved by the 3D-printed dielectric lens antennas. The proportion of ethanol in the liquid mixture sample is categorized using the transmission-line measuring technique. The device-under-test (DUT) is placed between two 3D-printed dielectric lens antennas. The glass bottle is filled with a 100-ml liquid sample and covered with a plastic cap. The 3D EM Simulation CST Studio is used to optimize the 10 mm gap between the dielectric lens antennas and the DUT. Six concentrations of the ethanol/water mixture, such as empty, 60%, 65%, 70%, and 80%, are measured to examine the measurement system. The measurement outcomes indicate the various S21 (transmission coefficient) levels between 9 GHz and 11 GHz. According to the trend of the suggested system, the level of the transmission coefficient, S21, will change downward when the proportion of ethanol is increased. Several better advantages, such as a nondestructive method, non-contact measurement, and support with a real-time monitoring system, are provided by the transmission-line measuring methodology using 3D-printed dielectric lens antennas. © 2023 IEEE.

关键词： 3D-printed dielectric lens antennas Fused Deposition Modeling technique non-destructive measurement real-time monitoring system

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Development and analysis of whispering gallery mode model for refractive index sensing 6

Development and analysis of whispering gallery mode model fo...

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6th Photonics Meeting 2023, PM 2023

作者： Batumalay, M. Zain, H.A. Rahim, H.R.A. Harun, S.W. Department of Electrical Engineering University of Malaya Kuala Lumpur50603 Malaysia Faculty of Data Science and Information Technology INTI International University Nilai Negeri Sembilan71800 Malaysia Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia

A refractive index sensor based on a whispering gallery mode resonator is numerically investigated in this paper. Whispering gallery mode resonators confine light and can be used in sensing applications, and this work presents the model built using COMSOL software to analyze their sensing performance. This work has investigated the WGM resonators' response to refractive index changes numerically using 2D models in the refractive index ranges 1.000 and 1.333. The resonator showed a sensitivity of 167 nm/RIU in the refractive index range of 1.3331.4 and a sensitivity of 95 nm/RIU in the refractive index range of 1.000-1.010. The sensing resonator has potential applications for biological and chemical analytes. © Published under licence by IOP Publishing Ltd.

关键词： Refractive index

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Performance evaluation of the non-local cost aggregation in stereo matching algorithm

Performance evaluation of the non-local cost aggregation in ...

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2022 engineering technology International Conference, ETIC 2022

作者： Zahari, Madiha Hamzah, Rostam A. Manap, Nurulfajar A. Herman, Adi Irwan Faculty of Electronic and Computer Engineering Universiti Teknikal Malaysia Melaka Melaka Malaysia Faculty of Electrical and Electronic Engineering Technology Universiti Teknikal Malaysia Melaka Melaka Malaysia Product & Test Engineering Texas Instruments Melaka Batu Berendam Malaysia

ISBN: (纸本)9781839537820

This paper presents the evaluation of the efficiency and accuracy of the stereo matching algorithm using a census transform with the non-local aggregation technique. This technique is proposed to reduce the average error of the overall matching process in order to produce an accurate disparity map and to access the efficiency of the matching algorithm. Fundamentally, the stereo matching process highly depends on the quality of the image pair. The properties different between left and right images such as image brightness, exposure, occlusion and less texture area have a significant influence on the matching algorithm's accuracy. Thus, this paper analysed the performance of the stereo matching algorithm using Census Transform at matching cost computation, the non-local technique of cost aggregation and winner-take-all strategy at cost optimization. The initial disparity value obtained in cost optimization is used as the final disparity map. The disparity maps obtained from three different aggregation methods are evaluated in terms of accuracy and processing time. The experimental results using the Middlebury dataset show that the non-local method is more accurate compared with other aggregation methods and while maintaining the efficiency of the algorithm. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Efficiency

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Mitigating Crop Losses: AI-enabled Disease Detection in Tomato Plants 20

Mitigating Crop Losses: AI-enabled Disease Detection in Toma...

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20th International Conference on Frontiers of Information technology, FIT 2023

作者： Ashfaq, Hassan Arshad, Usama Ali, Raja Hashim Ul Abideen, Zain Shah, Muhammad Huzaifa Ali Khan, Talha Ijaz, Ali Zeeshan Ali, Nisar Siddique, Abu Bakar Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany BCMaterials Basque Center for Materials Applications & Nanostructure Basque Country Leioa Spain University of Regina Faculty of Electronic Systems Engineering Regina Canada

ISBN: (纸本)9798350395785

Fostering crop health is vital for global food security, underscoring the need for effective disease detection. This research introduces an innovative artificial intelligence (AI) model designed to enhance the detection and diagnosis of diseases in tomato plants, particularly focusing on Early Blight and Late Blight. Significantly, our model leverages cutting-edge image processing techniques to improve disease detection efficiency, outperforming traditional methods in terms of speed and accuracy. Our results demonstrate an impressive model accuracy of 92.58% on training data and 86.83% on validation data, showing the effectiveness of AI in diagnosing plant diseases. These high accuracy rates underline the potential of our model for timely disease classification, allowing for immediate and appropriate interventions. However, our research also identified a potential overfitting problem in the model's performance. To address this, we propose using regularization and data augmentation techniques to enhance the model's generalizability on unseen data. Additionally, we delve into inherent challenges that plague AI-based plant disease detection, such as the scarcity of diverse datasets and the difficulty of achieving broad generalizability across different plant species. In identifying potential solutions for these issues, our research lays the groundwork for the wider and more practical implementation of AI technologies in agriculture. © 2023 IEEE.

关键词： Crops

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Quantum-Coherent X-rays from Crystals

Quantum-Coherent X-rays from Crystals

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Shi, Xihang Wong, Lee Wei Wesley Wong, Liang Jie Kaminer, Ido Solid State Institute Faculty of Electrical and Computer Engineering Technion - Israel Institute of Technology Haifa32000 Israel School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

We present a quantum analysis of X-ray radiation generated from free electrons interacting with crystalline materials, revealing the role of the electron's quantum-wave nature and of the radiation's quantum-pa... 详细信息

ISBN: (纸本)9781957171258

关键词： Crystals

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Blockchain-Based Crowdsourcing in UAV-Assisted Vehicular Edge Computing

Blockchain-Based Crowdsourcing in UAV-Assisted Vehicular Edg...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Yu, Ziqing Chang, Zheng Li, Jian Li, Yuan Zhang, Yulu School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China University of Jyväskylä Faculty of Information Technology JyväskyläFIN-40014 Finland School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China China Mobile Research Institute Department of IoT Technology Research Beijing China

ISBN: (纸本)9798350370218

Utilizing the flexibility advantages of the unmanned aerial vehicle (UAV), the emerging vehicular edge computing (VEC) is able to expand service and computing capability to the vehicular network. In this paper, we consider a crowdsourcing problem and propose a joint blockchain-based framework that enables end users to request services from UAV-assisted VEC system in emergency scenarios. Our framework leverages the global data relevant to the task by uploading it to the public blockchain for storage and tracing, where UAV and vehicles play important roles. Meanwhile, data specific to private networks is stored in the consortium blockchain to relieve data pressure on the public blockchain and improve the efficiency of the lookup process of public blockchain. During the task processing phase, we create a two-layer contract for the crowdsourcing network to incentivize the UAV network and vehicles to participate in task processing phase. We validate the feasibility of our two-layer contract through extensive simulations, which demonstrate the potential of our proposed framework to improve the efficiency of crowdsourcing in an UAV-assisted VEC. © 2023 IEEE.

关键词： Consortium Blockchain Contract Theory Crowdsourcing Incentive Mechanism Unmanned Aerial Vehicles Vehicular Edge Computing

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Performance Evaluation of Popular Deep Neural Networks for Neural Machine Translation 20

Performance Evaluation of Popular Deep Neural Networks for N...

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20th International Conference on Frontiers of Information technology, FIT 2023

作者： Naeem, Muhammad Siddique, Abu Bakar Ali, Raja Hashim Arshad, Usama Abideen, Zain Ul Ali Khan, Talha Shah, Muhammad Huzaifa Zeeshan Ijaz, Ali Ali, Nisar Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany BCMaterials Basque Center for Materials Applications & Nanostructure Basque Country Leioa Spain University of Regina Faculty of Electronic Systems Engineering Regina Canada

ISBN: (纸本)9798350395785

The field of Neural Machine Translation (NMT) has shown impressive performance for quick and easy communication in various languages spoken all over the world. NMT helps us by improving communication between different languages. For this purpose, different sequential models are used such as Recurrent Neural Network (RNN), Long Short Term Memory (LSTM), and Gated Recurrent Units (GRU). Analysis among these different models are important for making language translation better and choose the best model for the right job. This research investigates the performance of these models on two distinct language datasets, English-to-German and English-to-Urdu. Based on accuracy metrics, the findings reveal that GRU having test accuracy (88.22% ) outperforms RNN (87.21% ), and LSTM (85.70% )demonstrating the highest translation accuracy, followed by RNN and LSTM exhibiting comparatively lower accuracy levels. © 2023 IEEE.

关键词： Long short-term memory

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Leveraging AI and NLP in Chatbot Development: An Experimental Study 20

Leveraging AI and NLP in Chatbot Development: An Experimenta...

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20th International Conference on Frontiers of Information technology, FIT 2023

作者： Paracha, Abdul Wahab Arshad, Usama Ali, Raja Hashim Ul Abideen, Zain Shah, Muhammad Huzaifa Ali Khan, Talha Ijaz, Ali Zeeshan Ali, Nisar Siddique, Abu Bakar Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan BCMaterials Basque Center for Materials Applications & Nanostructure Basque Country Leioa Spain University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany University of Regina Faculty of Electronic Systems Engineering Regina Canada

ISBN: (纸本)9798350395785

In the current era of chatbots, this research delves into the advancements in AI chatbots, drawing on artificial intelligence (AI) and natural language processing (NLP) techniques to mimic human-like conversations. A particular focus is given to the potential of chatbots in facilitating multitasking dialogues, offering emotional support, and addressing complex subject matter, all the while respecting user privacy and trust. The implemented chatbot model is trained on a neural network, using Keras and TensorFlow libraries. This model's performance indicates a considerable dependence on the dataset's size, with larger datasets leading to better outcomes by providing more extensive language usage and context examples. Additionally, we also analyze the effect of varying architectures and hyperparameters on chatbot performance. The significance of localizing chatbots to adapt to different languages and cultures is also highlighted. While promising, the study identifies areas of improvement, suggesting future research directions in enhancing language capture techniques, expanding training datasets, and integrating emotional intelligence within chatbot systems. © 2023 IEEE.

关键词： Natural language processing systems

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