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Bio-oil production from pyrolysis of oil palm biomass and the upgrading technologies:A review

Carbon Resources Conversion 2021年第1期4卷 239-250页

作者： Liza Melia Terry Claudia Li Jiuan Jing Chew Aqsha Aqsha Bing Shen How Adrian Chun Minh Loy Bridgid Lai Fui Chin Deni Shidqi Khaerudini Nishar Hameed Guoqing Guan Jaka Sunarso Research Centre for Sustainable Technologies Faculty of EngineeringComputing and ScienceSwinburne University of TechnologyJalan Simpang Tiga93350 KuchingSarawakMalaysia Department of Bioenergy Engineering and Chemurgy Faculty of Industrial TechnologyInstitut Teknologi BandungBandung 40132Jawa BaratIndonesia Department of Chemical Engineering Monash UniversityVictoria 3800Australia Department of Chemical and Energy Engineering Faculty of Engineering and ScienceCurtin University MalaysiaCDT 25098009 Miri SarawakMalaysia Research Centre for Physics National Research and Innovation Agency(BRIN)Gd.440-442 Kawasan Puspiptek SerpongSouth Tangerang15314 BantenIndonesia Faculty of Science Engineering and TechnologySwinburne University of TechnologyHawthornVictoria 3122Australia Energy Conversion Engineering Group Institute of Regional Innovation(IRI)Hirosaki University2-1-3MatsubaraAomori 030-0813Japan

Oil palm biomass(OPB)represents major portion of the lignocellulosic waste in Malaysia that can be converted into *** review aims to provide important insights in OPB-derived bio-oil production by first discussing the chemical compositions of different OPB and their effects to the bio-oil yield and quality obtained from pyrolysis process,followed by discussing the addition of plastics and catalysts into the pyrolysis for bio-oil upgrading,and lastly summarizing the existing technoeconomic and environmental studies and the potential use of process integration and intensification in this ***(PP),low density polyethylene(LDPE),and high density polyethylene(HDPE)have been commonly used in co-pyrolysis of OPB,which can effectively increase the heating value of bio-oil up to 80%that of ***,acidic,basic,and neutral catalysts have been applied to increase the amount of hydrocarbon and phenol in the bio-oil,further improving the heating value to be comparable to *** bio-oil production from OPB is currently still limited to demonstration scale despite the favorable environmental compatibility and technoeconomic feasibility shown by studies focused on empty fruit bunch(EFB).Several promising advanced pyrolysis processes that integrate other processes such as anaerobic digestion,hydrogen production process,and heat and power generation units as well as the advanced reactor designs are also overviewed here as future innovation of the bio-oil production from OPB,which may play more significant role as the technology matures.

关键词： Bio-oil production Co-pyrolysis Oil palm biomass Plastic waste Pyrolysis

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Prediction of Diabetes Using Hidden Naïve Bayes: Comparative Study 1st

Prediction of Diabetes Using Hidden Naïve Bayes: Comparativ...

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1st International Conference of Advanced computing and Informatics, ICACIN 2020

作者： Al-Hameli, Bassam Abdo Alsewari, AbdulRahman A. Alsarem, Mohammed Faculty of Computing IBM Centre of Excellence Universiti Malaysia Pahang Kuantan26300 Malaysia Computer and Information Technology College University of Sheba Sana’a Yemen College of the Computer Science and Engineering Taibah University Medina Saudi Arabia

ISBN: (纸本)9789811560477

Classification techniques performance varies widely with the techniques and the datasets employed. A process performance classifier lies in how accurately it categorizes the item. The technique of classification finds the relationships between the value of the predictor and the values of the goal. This paper is an in-depth analysis study of the classification of algorithms in data mining field for the hidden Naïve Bayes (HNB) classifier compared to state-of-the-art medical classifiers which have demonstrated HNB performance and the ability to increase prediction accuracy. This study examines the overall performance of the four machine learning techniques strategies on the diabetes dataset, including HNB, decision tree (DT) C4.5, Naive Bayes (NB), and support vector machine (SVM), to identify the possibility of creating predictive models with real impact. The classification techniques are studied and analyzed;thus, their effectiveness is tested for the Pima Indian Diabetes dataset in terms of accuracy, precision, F-measure, and recall, besides other performance measures. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Support vector machines

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BIO-OIL PRODUCTION THROUGH CO-PYROLYSIS AND CATALYTIC CO-PYROLYSIS OF OIL PALM TRUNK AND POLYPROPYLENE 30th

BIO-OIL PRODUCTION THROUGH CO-PYROLYSIS AND CATALYTIC CO-PYR...

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30th European Biomass Conference and Exhibition, EUBCE 2022

作者： Terry, Liza Melia Li, Claudia Chew, Jiuan Jing Aqsha, Aqsha Khaerudini, Deni Shidqi Wee, Melvin Xin Jie Saptoro, Agus Sunarso, Jaka Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Jalan Simpang Tiga Sarawak Kuching93350 Malaysia Department of Bioenergy and Chemurgy Faculty of Industrial Technology Institut Teknologi Bandung Jawa Barat Bandung40132 Indonesia Bld. 440 Kawasan Puspiptek Serpong Banten South Tangerang15314 Indonesia Department of Chemical and Energy Engineering Curtin University Malaysia CDT 250 Sarawak Miri98009 Malaysia

Harvesting energy from biomass represents a sustainable approach to meet future energy demand as biomass is one of the largest renewable carbon sources. In Malaysia, aged oil palm trees are typically replanted after reaching 25-30 years old and oil palm trunks (OPT) can be abundantly collected from the replanting activities in palm oil plantations. This work evaluates bio-oil production through the co-pyrolysis of OPT and polypropylene (PP) with and without the use of catalysts. The addition of PP helps to concentrate the carbon content of bio-oil while the catalyst addition is expected to improve the desired composition of bio-oil. The proposed catalyst employed in this study was Ni-Mo/γAl2O3, which is mostly used in hydrotreatment for bio-oil upgrading due to its excellent thermal stability. However, its utilisation in the pyrolysis and co-pyrolysis of biomass has gained less attention. Thus, the feasibility of Ni-Mo/γAl2O3 to upgrade the bio-oil obtained from the co-pyrolysis of OPT and PP was investigated in this work. The maximum bio-oil yield was obtained at 600 °C and 700 °C from co-pyrolysis and catalytic co-pyrolysis, respectively. From the experiments, it is evidence that the addition of Ni-Mo/γAl2O3 resulted in improvement of hydrocarbon content in the bio-oil through the deoxygenation of the oxygenates and phenols. © 2022, ETA-Florence Renewable Energies., All rights reserved.

关键词： Catalysts

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Elucidation of Accelerated Weathering of Limestone for Post Combustion Carbon Capture: Process Development, Optimization, Kinetic Modelling and Mass Transfer Analysis

SSRN

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SSRN 2023年

作者： Ngu, Lock Hei Chai, Slyvester Yew Wang How, Bing Shen Adini, Mohd Jamil Bin Anong Kassim, Alzian Mohamad Peter, Catriena Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Campus Kuching Jalan Simpang Tiga 93350 Malaysia Learning and Development Centre Cahya Mata Sarawak Kuching Jalan Kampung Mambong – Sikog – Sarig Siburan 94200 Malaysia

Energy generation and industrial processes emitted 36.3 billion tCO2 in 2021, causing detrimental environmental effects. To curb these emissions, this research develops an absorption tower for a portable water-operated Accelerated Weathering of Limestone (AWL) process for post-combustion carbon capture. The tower has a limestone-packed bed height of 0.876 m and a diameter of 0.114 m. A correlation study was performed on the effect of the liquid-to-gas (L/G) ratio on effluent's CO2 capture efficiency and alkalinity. The findings showed that decreased L/G ratio (1 to 0.003) leads to an increase in effluent alkalinity (0.77 to 3.65 mM) and pH (5.58 to 7.47) but a decrease in CO2 capture efficiency (81.94 to 20.82 %). Next, optimization using Design of Expert (DoE) identifies the L/G to achieve the highest alkalinity at 3.63 mM (L/G: 0.0024) and the highest CO2 capture efficiency at 82.15% (L/G: 1.23). The reported CaCO3 CO2 absorption capacity is 3.90 to 4.72 mol CO2. mol absorbent-1 is superior to amine-based absorbents and ionic liquid but has a low absorption rate of 1.21 x 10-4 to 3.14 x 10-4 mol CO2.s-1. In addition, the kinetic analysis shows that the forward reaction rate constants (k) are more rapid than AWL occurring at ambient air conditions. The calculated mass transfer coefficients indicated that CO2 dissolution (0.25 cm.s-1) is much faster than CaCO3 dissolution (3.35 x 10-4 cm.s-1). Overall, the study provides valuable insights into the AWL process and its potential for commercialization and scale-up. © 2023, The Authors. All rights reserved.

关键词： Dissolution

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Emergency Vehicle Navigation in Connected Autonomous Systems Using Enhanced Traffic Management System

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IEEE Internet of Things Journal 2025年

作者： Raja, Gunasekaran Anbalagan, Sudha Gurumoorthy, Sugeerthi Jegathesan, Darshini Girivel, Niveditha Subramanian Sundaram, Varsha Mani Shanmuga Khowaja, Sunder Ali Dev, Kapal Anna University NGNLab Department of Computer Technology MIT Campus Chennai600044 India Vellore Institute of Technology Chennai Centre for Smart Grid Technologies School of Computer Science and Engineering Chennai600127 India Citicorp Services Private Ltd Software Development Chennai600113 India Dublin City University School of Computing Faculty of Engineering and Computing Glasnevin Campus DublinD09 V209 Ireland Munster Technological University Department of Computer Science Bishopstown CorkT12 P928 Ireland University of Johannesburg Department of Institute of Intelligent Systems Johannesburg2006 South Africa Chitkara University Institute of Engineering and Technology Centre for Research Impact Outcome Chitkara University Punjab Rajpura140401 India

Autonomous Vehicle (AV) usage has become predominant in the rapidly evolving landscape of urban transportation. Integrating AVs and non-AVs in the existing traffic infrastructure has significantly increased the complexity of traffic patterns. This research work primes the enhanced Traffic Management System (e-TMS), a solution implemented to expedite Emergency Vehicle (EV) travel in the context of Connected AVs (CAVs) and ensured secured communication employing Public Key Infrastructure (PKI) among the Internet of Vehicles (IoV) framework. When an EV is detected, the IoV system verifies the EV's signal using PKI, ensuring its authenticity and integrity by encrypting the communication between the EV and Road Side Units (RSUs). Further, the e-TMS activates the platooning process where CAVs in the EV's lane shift to the adjacent lanes and dynamically form platoons to create a dedicated lane for the EV. To further optimize the platooning process, an Adaptive Smart Leader Selection (ASLS) algorithm is employed to select a leader vehicle spontaneously among the AVs based on the proximity to the EV, communication reliability, and lane position. Radio Detection and Ranging devices aid this platooning process by providing distance and target velocity, which are needed to maintain the required distance between the AVs and ensure safe platoon formation. The e-TMS enhances EV response times and overall traffic flow efficiency and resulted in 27.8% increase in mean speed compared to the traditional methods. © 2014 IEEE.

关键词： Emergency vehicles

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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

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Computer Systems science & Engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the ***6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration ***6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial ***,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of *** paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential ***,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack *** results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)*** proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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Internet of Things: Interoperability and Integration Test with the Combined Business Process Technique in the Layered Architecture

Internet of Things: Interoperability and Integration Test wi...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Teik-Boon Tan Yiqi Tew Tong-Ming Lim Wai-Khuen Cheng Yen-Lin Chen Department of Computer Science Universiti Tunku Abdul Rahman Kampar Malaysia Faculty of Computing And Information Technology Tunku Abdul Rahman University of Management and Technology Kuala Lumpur Malaysia Centre For Business Incubation And Entrepreneurial Ventures Tunku Abdul Rahman University of Management and Technology Kuala Lumpur Malaysia Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

This paper provides an overview of the Internet of Things (IoT) components in the layered architecture. Then we give an overview possible of tests that are applicable in the layers and possible challenges of in conducting tests in the layered architecture. We provide explanation on the integration and interoperability tests with a simple evaluation on how the existing architecture works. We present the need for better tests and an improvement using the combination of path-based and business process components presented in the paper.

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In-Context Code-Text Learning for Bimodal Software Engineering

arXiv

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arXiv 2024年

作者： Tang, Xunzhu Wang, Liran Liu, Yonghui Chai, Linzheng Yang, Jian Li, Zhoujun Tian, Haoye Klein, Jacques Bissyandé, Tegawendé F. University of Luxembourg Luxembourg Luxembourg School of Computer Science and Engineering Beihang University Beijing China Faculty of Information Technology Monash University Melbourne Australia School of Computing and Information Systems University of Melbourne Melbourne Australia SnT Centre for Security Reliability and Trust University of Luxembourg Luxembourg Luxembourg

Bimodal software analysis initially appeared to be within reach with the advent of large language models. Unfortunately, the complex interplay of natural language text and code in software engineering, presents unique challenges that prevent pretrained models to generalize to a variety of tasks. We postulate that in-context learning for the code-text bimodality is a promising avenue. This paper thus introduces a comprehensive study of in-context code-text learning, focusing on leveraging pretrained CodeLLAMA models. We consider a diverse dataset encompassing 23 software engineering tasks, which we transform in an in-context learning format. To effectively extract informative features, we propose a configurable prompt template. Our proposed pipeline, INCTRL, then unifies prompt learning across various software engineering tasks. Extensive evaluation on the study datasets demonstrates the superiority of INCTRL-models in few-shot performance, surpassing state-of-the-art models including the support model, CodeLLAMA. Typically, we observe that applied to the CodeLLAMA model, INCTRL brings improvements in terms of precision (at least about 12%) and recall (up to 93.88%) on various tasks. For example, on the task of program repair, INCTRL improves the BLEU score of CodeLLAMA by 85 points, while for clone detection, INCTRL achieves an improvement of 69 percentage points. Moreover, INCTRL-models offer state-of-the-art performance when using retrieval-augmented generation on individual downstream tasks. Finally, we qualitatively analyze the benefits of INCTRL over CodeLLAMA and open-source all models for broader impact. Copyright © 2024, The Authors. All rights reserved.

关键词： Open source software

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Artificial Intelligence-based Service Chains Scheduling for Medical Emergency in Healthcare 7

Artificial Intelligence-based Service Chains Scheduling for ...

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7th International Conference on Contemporary computing and Informatics, IC3I 2024

作者： Soni, Mukesh Rusho, Maher Ali Byeon, Haewon Alghamdi, Azzah Hannan, Shaikh Abdul Dave, Parth Rameshchandra Dr. D. Y. Patil School of Science & Technology Tathawade Dr. D. Y. Patil Vidyapeeth Marashtra Pune India University of Colorado Department of Lockheed Martin Engineering Management BoulderCO80309 United States Inje University Department of Ai and Software & Medical Big Data Research Centre Gimhae50834 Korea Republic of Imam Abdalrhman Bin Faisal University College of Computer Science and Information Technology Computer Information Systems Department Khobar Saudi Arabia AlBaha University Faculty of Computing and Information AlBaha Saudi Arabia L. D. College of Engineering Department of Computer Engineering Gujarat Ahmedabad India

ISBN: (纸本)9798350350067

This study analyses the weekly scheduling challenge of health and medical information network service function chains to meet medical emergency categorization and grading needs. Emergency services are divided into four sorts by urgency and service area, with priorities and weights. The health and medical information network architecture, service model, and operation method are built accordingly. To reduce weighted completion time, a service function chain scheduling model is created. The function chain scheduling scheme is solved by matching game and Q -learning reinforcement learning algorithms for different issue scales. Finally, simulation studies demonstrate that this approach can accomplish graded medical emergency service, build health and medical information networks, and progress smart healthcare. © 2024 IEEE.

关键词： Electronic health record

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Wetting state transition of porous hydrophobic membrane in direct-contact membrane distillation

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Separation and Purification technology 2025年 372卷

作者： Xie, Songchen Hou, Chunguang Chen, Xiaofei Peng, Yuelian Zhang, Xinmiao Zhang, Chenlin Hartanto, Yusak Bilad, Muhammad Roil Sunarso, Jaka Liu, Shaomin State Key Laboratory of Materials Low-Carbon Recycling Beijing University of Technology Beijing100124 China SINOPEC Beijing Research Institute of Chemical Industry Beijing100013 China Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Kuching93350 Malaysia Faculty of Integrated Technologies Universiti Brunei Darussalam GadongBE1410 Brunei Dongguan Key Laboratory of Intelligent Equipment and Smart Industry School of Engineering Great Bay University Dongguan523000 China

Pore wetting is one of the key factors blocking the development of membrane distillation (MD). This study aimed to develop a wetting model and an equilibrium equation of the gas/liquid interface for membranes in direct-contact MD (DCMD). The model was verified by experimental results and correlated with the membrane porous structure, feed flow rate/hydraulic pressure, and feed temperatures. It was found that reducing membrane pore size had a greater impact in maintaining the gas/liquid interfacial stability rather than controlling the surface hydrophobicity. Furthermore, pore wetting caused by membrane fouling from surfactant adsorption and calcium sulfate deposition can be reduced via membrane cleaning to restore its original hydrophobicity. DCMD operation at low feed pressure could inhibit membrane wetting, particularly operation at negative pressure, which greatly improved the flux stability when liquid with a low surface tension was used as a feed. Other factors like feed pressure and membrane configurations were also discussed for their effects in pore wetting. © 2025 Elsevier B.V.

关键词： Wetting

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