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Valorization of cannabis waste via hydrothermal carbonization: solid fuel production and characterization

Environmental science and Pollution Research 2023年第39期30卷 90318-90327页

作者： Kanchanatip, Ekkachai Prasertsung, Nattakarn Thasnas, Natakorn Grisdanurak, Nurak Wantala, Kitirote Faculty of Science and Engineering Department of Civil and Environmental Engineering Kasetsart University Chalermprakiat Sakon Nakhon Province Campus Sakon Nakhon47000 Thailand Faculty of Science and Engineering Department of Electrical and Computer Engineering Kasetsart University Chalermprakiat Sakon Nakhon Province Campus Sakon Nakhon47000 Thailand Faculty of Engineering Department of Chemical Engineering Thammasat University Pathum Thani12120 Thailand Faculty of Engineering Center of Excellence in Environmental Catalysis and Adsorption Thammasat University Pathum Thani12120 Thailand Faculty of Engineering Department of Chemical Engineering Khon Kaen University Khon Kaen40002 Thailand Khon Kaen University Khon Kaen40002 Thailand

Hydrothermal carbonization (HTC) was employed to convert cannabis waste into valuable solid fuel (hydrochar) under different operating conditions, including reaction temperature (170–230 °C), biomass-water ratio (1:10–1:20), and residence time of 60 min. The produced hydrochar was examined for their fuel properties including calorific value (HHV), proximate and ultimate analysis, thermal stability and combustion behavior, etc. The results revealed higher HTC temperature led to a higher degree of carbonization, which is beneficial for increasing carbon content and HHV of the hydrochar. The HHV of the hydrochar improved significantly up to 24.65 MJ/kg after the HTC compared to 17.50 MJ/kg for cannabis waste. The energy yield of hydrochar from the HTC process was in a range of 70.41–82.23%. The optimal HTC condition was observed at 230 °C and a biomass-water ratio of 1:10, producing high-quality hydrochar with 24.24 MJ/kg HHV and 72.28% energy yield. The hydrochar had similar fuel characteristics to lignite coal with significantly lower ash content. Additionally, recirculation of liquid effluent showed a positive influence on the HHV of hydrochar besides minimizing the release of wastewater from the HTC process. The study revealed that HTC is a promising technique for valorization of cannabis waste into high-value solid fuel, which can be potentially an alternative to coal. Graphical Abstract: [Figure not available: see fulltext.]. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Biomass

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Hybrid Dynamic Optimization for Multilevel Security System in Disseminating Confidential Information

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computer Systems science & engineering 2023年第12期47卷 3145-3163页

作者： Shahina Anwarul Sunil Kumar Ashok Bhansali Hammam Alshazly Hany S.Hussein School of Computer Science University of Petroleum and Energy StudiesDehradun248007India Department of Computer Science Graphic Era Hill UniversityDehradunUttarakhand248001India Department of Computer Engineering and Applications GLA UniversityMathuraIndia Faculty of Computers and Information South Valley UniversityQena83523Egypt Electrical Engineering Department College of EngineeringKing Khalid UniversityAbha62529Saudi Arabia Electrical Engineering Department Faculty of EngineeringAswan UniversityAswan81528Egypt

Security systems are the need of the hour to protect data from unauthorized *** dissemination of confidential information over the public network requires a high level of *** security approach such as steganography ensures confidentiality,authentication,integrity,and *** helps in hiding the secret data inside the cover media so that the attacker can be confused during the transmission process of secret data between sender and ***,we present an efficient hybrid security model that provides multifold security *** this end,a rectified Advanced Encryption Standard(AES)algorithm is proposed to overcome the problems existing in AES such as pattern appearance and high *** modified AES is used for the encryption of the stego image that contains the digitally signed encrypted secret *** enciphering and deciphering of the secret data are done using the Rivest–Shamir–Adleman(RSA)*** experiments are conducted on the images of the USC-SIPI standard image *** experimental results prove that the proposed hybrid system outperforms other SOTA(state-of-the-art)approaches.

关键词： Cryptography steganography digital signature rectified AES encryption

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Identification and Visualization of Spatial and Temporal Trends in Textile Industry

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computers, Materials & Continua 2023年第2期74卷 4165-4181页

作者： Umair Yousaf Muhammad Asif Shahbaz Ahmed Noman Tahir Azeem Irshad Akber Abid Gardezi Muhammad Shafiq Jin-Ghoo Choi Habib Hamam Department of Computer Science National Textile UniversityFaisalabad38000Pakistan Department of Computer Science and Software Engineering International Islamic UniversityIslamabad44000Pakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea Faculty of Engineering Uni de MonctonMonctonNB E1A3E9Canada International Institute of Technology and Management Commune d’AkandaBPLibreville1989Gabon School of Electrical Engineering Department of Electrical and Electronic Eng.ScienceUniversity of JohannesburgJohannesburg2006South Africa Spectrum of Knowledge Production&Skills Development Sfax3027Tunisia

The research volume increases at the study rate,causing massive text *** to these enormous text corpora,we are drowning in data and starving for ***,recent research employed different text mining approaches to extract information from this text *** proposed approaches extract meaningful and precise phrases that effectively describe the text’s *** extracted phrases are commonly termed ***,these key phrases are employed to determine the different fields of study ***,these key phrases can also be used to determine the spatiotemporal trends in the various research *** this research,the progress of a research field can be better revealed through spatiotemporal bibliographic trend ***,an effective spatiotemporal trend extraction mechanism is required to disclose textile research trends of particular regions during a specific *** study collected a diversified dataset of textile research from 2011–2019 and different countries to determine the research *** data was collected from various open access ***,this research determined the spatiotemporal trends using quality *** research also focused on finding the research collaboration of different countries in a particular research *** research collaborations of other countries’researchers show the impact on import and export of those *** visualization approach is also incorporated to understand the results better.

关键词： Text mining spatiotemporal trend research collaboration

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An Integrated Fusion Framework for Ensemble Learning Leveraging Gradient-Boosting and Fuzzy Rule-Based Models

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5771-5785页

作者： Li, Jinbo Liu, Peng Chen, Long Pedrycz, Witold Ding, Weiping Nantong University School of Artificial Intelligence and Computer Science Nantong226019 China China Unicom Research Institute Beijing100048 China Henan University International Business School Zhengzhou47500 China University of Macau Department of Computer and Information Science 999078 China University of Alberta Department of Electrical and Computer Engineering EdmontonAB T6R 2V4 Canada City University of Macau Faculty of Data Science 999078 China

The integration of different learning paradigms has long been a focus of machine learning research, aimed at overcoming the inherent limitations of individual methods. Fuzzy rule-based models excel in interpretability and have seen widespread application across diverse fields. However, they face challenges such as complex design specifications and scalability issues with large datasets. The fusion of different techniques and strategies, particularly gradient boosting, with fuzzy rule-based models offers a robust solution to these challenges. This article proposes an integrated fusion framework that merges the strengths of both paradigms to enhance model performance and interpretability. At each iteration, a fuzzy rule-based model is constructed and controlled by a dynamic factor to optimize its contribution to the overall ensemble. This control factor serves multiple purposes: it prevents model dominance, encourages diversity, acts as a regularization parameter, and provides a mechanism for dynamic tuning based on model performance, thus mitigating the risk of overfitting. Additionally, the framework incorporates a sample-based correction mechanism that allows for adaptive adjustments based on feedback from a validation set. Experimental results substantiate the efficacy of the presented gradient-boosting framework for fuzzy rule-based models, demonstrating performance enhancement, especially in terms of mitigating overfitting and complexity typically associated with many rules. By leveraging an optimal factor to govern the contribution of each model, the framework improves performance, maintains interpretability, and simplifies the maintenance and update of the models. © 2024 IEEE.

关键词： Optimization

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Air Quality Monitoring in Ulaanbaatar Using Fog Computing and IoT, Looking for the Correlation Between Air Pollution and Public Health 28

Air Quality Monitoring in Ulaanbaatar Using Fog Computing an...

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28th International Scientific Conference on Transport Means 2024

作者： Patlins, A. Nyamkhuu, B. Kunicina, N. Riga Technical University Faculty of Computer Science Information Technology and Energy Institute of Industrial Electronics Electrical Engineering and Energy 10 Zunda Embankment RigaLV-1048 Latvia

In the research under discussion, the authors put forth a novel approach to air quality monitoring in Ulaanbaatar, Mongolia’s capital, by leveraging the power of fog computing. This innovative method involves the collection of air pollution data in a manner that is both cost-effective and efficient, thereby making it a viable solution for a city where air pollution is a significant concern. The primary objective of this approach is to estimate the impact of air pollution on public health. This is achieved through the application of statistical methods to the collected data, which allows for the understanding of the health risks associated with poor air quality. By doing so, it is hoped that this research will contribute to raising awareness about the dangers posed by air pollution, a problem that is often overlooked but has far-reaching implications for public health. One of the key features of the proposed approach is its focus on expanding the coverage of air quality monitoring. This is particularly relevant in the Ger areas of Ulaanbaatar, where pollution levels tend to spike during the winter months. The inhabitants of these areas, who often rely on coal for heating, are among the most affected by the adverse effects of air pollution. Therefore, by extending the reach of monitoring efforts to these areas, the research aims to provide a more accurate and comprehensive picture of the city’s air quality. In addition to the above, the research also takes into account the role of transportation in contributing to air pollution. In Ulaanbaatar, as in many other urban centers around the world, transportation is a one of major sources of air pollution. This includes not only public transport but also private vehicles, which collectively contribute a significant amount of pollutants to the city’s air. By considering the impact of transportation on air quality, the proposed approach acknowledges the multifaceted nature of the air pollution problem and underscores the need

关键词： Air quality

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Cyber Security Analysis and Evaluation for Intrusion Detection Systems

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computers, Materials & Continua 2022年第7期72卷 1765-1783页

作者： Yoosef B.Abushark Asif Irshad Khan Fawaz Alsolami Abdulmohsen Almalawi Md Mottahir Alam Alka Agrawal Rajeev Kumar Raees Ahmad Khan Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Electrical and Computer Engineering Faculty of EngineeringKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow226028India

Machine learning is a technique that is widely employed in both the academic and industrial sectors all over the *** learning algorithms that are intuitive can analyse risks and respond swiftly to breaches and security *** is crucial in offering a proactive security system in the field of *** real time,cybersecurity protects information,information systems,and networks from *** the recent decade,several assessments on security and privacy estimates have noted a rapid growth in both the incidence and quantity of cybersecurity *** an increasing rate,intruders are breaching information *** detection,software vulnerability diagnosis,phishing page identification,denial of service assaults,and malware identification are the foremost cyber-security concerns that require efficient *** have tried a variety of approaches to address the present cybersecurity obstacles and *** a similar vein,the goal of this research is to assess the idealness of machine learning-based intrusion detection systems under fuzzy conditions using a Multi-Criteria Decision Making(MCDM)-based Analytical Hierarchy Process(AHP)and a Technique for Order of Preference by Similarity to Ideal-Solutions(TOPSIS).Fuzzy sets are ideal for dealing with decision-making scenarios in which experts are unsure of the best course of *** projected work would support practitioners in identifying,prioritising,and selecting cybersecurityrelated attributes for intrusion detection systems,allowing them to design more optimal and effective intrusion detection systems.

关键词： Cybersecurity machine learning AHP-TOPSIS fuzzy logic intrusion detection systems

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Implementation of ML Algorithms for the Purpose of Quality Improvement of Power

Implementation of ML Algorithms for the Purpose of Quality I...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Raghu, N. Meena, Mansingh Saxena, Kumud Faculty of Engineering and Technology Department of Electrical and Elceltronics Engineering Bangalore India Vivekananda Global University Department of Electrical Engineering Jaipur India Noida Institute of Engineering & Technology Department of Computer Science and Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350357769

In our fast industrializing world, the need for more reliable and high-quality power production is highlighted by the growing need for electrical energy and the drive toward automation. In an effort to fulfill the growing need for electrical power, sources of renewable electricity (RE) have surfaced as an eco-friendly substitute for traditional energy sources. However, because of their intrinsically erratic and fluctuating production patterns, integrating these sources of renewable energy into the utility grid poses difficulties for sustaining the quality of electricity (PQ) and system stability. Mitigating PQ difficulties related to the adoption of renewable energy has been made possible by the integration of a distributed flexibly AC transfer system gadgets such as distribute static compensator (DSTATCOM) as dynamic voltage restorer (DVR). The control algorithms that dictate the functioning of those DFACTS devices are substantially responsible for their effectiveness. This exploration leads an extensive examination of the ordinary and adjust control methods utilized in DFACTS frameworks to address power quality issues in utility organizations where sustainable power is being incorporated. The exhaustive assessment incorporates an assessment of in excess of 170 examination papers and offers a cautious classification and outline of the different control techniques. The survey investigates these calculations' plan, trying equipment, signs of execution, and reasonability as archived in the group of surviving exploration. This collection is an invaluable tool that provides engineers and scholars working in the dynamic subject of improving power quality in utility networks amid the increasing impact of renewable energy sources with a rapid reference. © 2023 IEEE.

关键词： Adaptive Control Algorithm Conventional Control Algorithm DFACTS Device Modern Utility Grid Power Quality and Renewable Energy Source

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GENERALIZED BAYES SURE FOR MULTIVARIATE NORMAL DISTRIBUTION UNDER BALANCED-QUADRATIC LOSS

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Journal of Mathematical sciences (United States) 2024年第2期280卷 262-274页

作者： Karamikabir, Hamid Afshari, Mahmoud Karamikabir, Nasrin Kiaei, Seyed Faridoddin Department of Statistics Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran Department of Mathematics Hamedan Branch Islamic Azad University Hamedan Iran School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran

One of the most important subjects in statistics is the theory of estimation. In this paper, we consider the generalized Bayes shrinkage estimator of the mean vector for multivariate normal distribution with the unknown covariance matrix under balanced quadratic loss. Also, we find the minimax and admissible estimator of the mean vector based on the generalized Bayes estimator. We obtain Stein’s unbiased risk estimator (SURE) threshold with a generalized Bayes shrinkage estimator and we find the wavelet shrinkage generalized Bayes SURE. Finally, we present a simulation study to test the validity of the generalized Bayes SURE and the concrete compressive strength dataset is given to test the efficiency of this estimator in denoising. © 2024, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Balanced-quadratic loss Generalized bayes estimator Shrinkage estimaton Shrinkage wavelet SURE threshold

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A Bagging MLP-based Autoencoder for Detection of False Data Injection Attack in Smart Grid

A Bagging MLP-based Autoencoder for Detection of False Data ...

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2022 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2022

作者： Paul, Shuva Kundu, Ripan Kumar Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA United States University of Rostock Faculty of Computer Science & Electrical Engineering Rostock Germany

ISBN: (纸本)9781665437752

The accelerated move toward adopting the Smart Grid paradigm has resulted in numerous drawbacks as far as security is concerned. Traditional power grids are becoming more vulnerable to cyberattacks as all the control decisions are generated based on the data the Smart Grid generates during its operation. This data can be tampered with or attacked in communication lines to mislead the control room in decision-making. The false data injection attack (FDIA) is one of the most severe cyberattacks on today's cyber-physical power system, as it has the potential to cause significant physical and financial damage. However, detecting cyberattacks are incredibly challenging since they have no known patterns. In this paper, we launch a random FDIA on IEEE-39 bus system. Later, we propose a Bagging MLP-based autoencoder to detect the FDIAs in the power system and compare the result with a single ML model. The Bagging MLP-based autoencoder outperforms the Isolation forest while detecting FDIAs. © 2022 IEEE.

关键词： Smart power grids

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Towards Using MultiModal LLMs as Graders in a GUI Design Course 66

Towards Using MultiModal LLMs as Graders in a GUI Design Cou...

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66th International Symposium ELMAR, ELMAR 2024

作者： Busic, Bruno Leventic, Hrvoje Romic, Kresimir Habijan, Marija Bamboo Lab d.o.o. OsijekHR-31000 Croatia Computer Science and Information Technology Osijek Faculty of Electrical Engineering OsijekHR-31000 Croatia

ISBN: (纸本)9798350375411

This paper explores the potential of MultiModal Large Language Models (MM-LLMs) in automating grading processes in GUI design courses. We introduce a novel approach in using MM-LLMs to conduct pairwise comparisons rather than assigning direct numerical grades, aiming to enhance grading objectivity and efficiency. Preliminary results indicate that multimodal LLMs (such as OpenAI GPT-4o) can successfully identify superior designs when presented in pairs, suggesting a potential for a scalable and less biased grading system that could benefit both the educators and the students by providing timely and consistent feedback. © 2024 IEEE.

关键词： Curricula

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