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3rd International Conference on Sustainable Mobility Applications, Renewables and technology, SMART 2024

作者： Al-Naemi, Salem Al-Otoom, Awni Benlamri, Rachid Koshy, Biju University of Doha for Science & Technology Doha Qatar College of Engineering & Technology University of Deoha for Science & Technology Doha Qatar University of Deoha for Science & Technology Doha Qatar

ISBN: (纸本)9798331532925

Higher Education Institutions (HEIs) play a pivotal role in driving sustainable development through a multifaceted approach encompassing sustainable curriculum development, impactful research endeavors, adoption of environmentally conscious campus practices, and active community engagement. This mandates HEIs to not only cultivate a cadre of future leaders equipped with sustainable development acumen but also to actively contribute, both directly and indirectly, to local and global sustainable development efforts while fostering technological advancements conducive to sustainability. The university of Sustainable Development in technology (UDST) stands as an exemplar among young universities, demonstrating a concerted commitment to aligning its educational offerings, research pursuits, and campus infrastructure with the principles and objectives outlined in the United Nations Sustainable Development Goals (SDGs). Since its inception, UDST has undertaken a series of proactive measures and initiatives that resonate closely with the aspirations encapsulated within the UN SDGs. These efforts not only underscore UDST's dedication to sustainable development but also underscore its alignment with national strategic imperatives, notably the Qatar National Vision 2030 (QNV2030). This paper presents UDST's initiatives as a compelling case study within the context of Qatar, highlighting its deliberate efforts to synchronize its vision, mission, and strategic objectives with the overarching frameworks of the UN SDGs and QNV2030. Through a comprehensive examination of UDST's approach, this study aims to elucidate the intricate interplay between higher education institutions, sustainable development agendas, and national development aspirations, thereby offering valuable insights for policymakers, educators, and stakeholders alike. © 2024 IEEE

关键词： Sustainable development

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All-weather artificial photosynthesis for CO_(2) conversion

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science China Chemistry 2025年第4期68卷 1212-1214页

作者： Ailin Gao Changchao Jia College of Materials Science and Engineering Qingdao University of Science and TechnologyQingdao 266042China College of Polymer Science and Engineering Qingdao University of Science and TechnologyQingdao 266042China

The global ecological crisis encompasses a variety of effects on the environment caused by *** encompasses severe climatic conditions,escalating sea levels,permanent biodiversity decline,and a heightened disease risk due to greenhouse gas emissions elevating global average temperatures in water and air from industrial and consumer waste,along with soil *** primary cause of greenhouse gas emissions is the overreliance on fossil fuels to satisfy escalating energy needs.

关键词： soil pollution escalating sea levels permanent biodiversity decline greenhouse gas emissions heightened disease risk severe climatic conditions global ecological crisis severe climatic conditionsescalating sea levelspermanent

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In situ growth of nano-hydroxyapatite on multilayered Ti_(3)C_(2)T_(x) MXene as a drug carrier with superior-performance

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Journal of Materials science & technology 2024年第13期180卷 91-101页

作者： Xiaowei Liu Ruixue Sun Zeao Zhou Yuanzheng Tang College of Materials Science and Engineering Qingdao University of Science and TechnologyQingdao 266042China College of Electromechanical Engineering Qingdao University of Science and TechnologyQingdao 266061China

Bone defects caused by tumor resection typically require bone repair materials to fill the defect *** development of multifunctional bone filling materials with integrated chemotherapy,photohermal therapy,and guided bone regeneration is very necessary and urgently ***,for the first time,the construction of novel multilayered Ti_(3)C_(2)T_(x) MXene(m-MXene)/nano-hydroxyaptite(nHAp)composites(m-MXene/nHAp)for bone repair is *** in situ growth of nHAp on multilayered Ti_(3)C_(2)T_(x) MXene is achieved through a facile hydrothermal method without using any organic *** to the syner-gistic effects of nHAp and m-MXene,the m-MXene/nHAp composites show superior drug carrier perfor-mance with ultra-high drug loading capacity and ultra-long drug sustained release *** molecular dynamics simulation results indicate that both Ti_(3)C_(2)T_(x) MXene and HAp show many adsorption sites and high binding energy with ***,the m-MXene/nHAp composites possess high photothermal conversion efficiency and excellent photothermal *** in situ growth of nano-HAp can signifi-cantly improve the biocompatibility of the *** as-prepared multifunctional m-MXene/nHAp composites in this work can be used as bone filling powder and have great potential in bone defect reconstruction caused by bone tumor.

关键词： Multilayered Ti_(3)C_(2)T_(x)MXene Nano-hydroxyapatite In situ growth Drug carrier Photothermal property

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Enhancing waste sorting and recycling efficiency: robust deep learning-based approach for classification and detection

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Neural Computing and Applications 2025年第6期37卷 4567-4583页

作者： Sayem, Faizul Rakib Islam, Md. Sakib Bin Naznine, Mansura Nashbat, Mohammad Hasan-Zia, Mazhar Kunju, Ali K Ansaruddin Khandakar, Amith Ashraf, Azad Majid, Molla Ehsanul Kashem, Saad Bin Abul Chowdhury, Muhammad E. H. Department of Electrical and Electronic Engineering University of Dhaka Dhaka Bangladesh Department of Biomedical Engineering Military Institute of Science and Technology Dhaka Bangladesh Department of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi6204 Bangladesh Chemical Engineering Department University of Doha for Science and Technology Doha Qatar Department of Electrical Engineering Qatar University Doha2713 Qatar Computer Applications Department Academic Bridge Program Qatar Foundation Doha Qatar Department of Computing Science AFG College With the University of Aberdeen Doha Qatar

Given the severity of waste pollution as a major environmental concern, intelligent and sustainable waste management is becoming increasingly crucial in both developed and developing countries. The material composition and volume of urban solid waste are key considerations in processing, managing, and utilizing city waste. Deep learning technologies have emerged as viable solutions to address waste management issues by reducing labor costs and automating complex tasks. However, the limited number of trash image categories and the inadequacy of existing datasets have constrained the proper evaluation of machine learning model performance across a large number of waste classes. In this paper, we present robust waste image classification and object detection studies using deep learning models, utilizing 28 distinct recyclable categories of waste images comprising a total of 10,406 images. For the waste classification task, we proposed a novel dual-stream network that outperformed several state-of-the-art models, achieving an overall classification accuracy of 83.11%. Additionally, we introduced the GELAN-E (generalized efficient layer aggregation network) model for waste object detection tasks, obtaining a mean average precision (mAP50) of 63%, surpassing other state-of-the-art detection models. These advancements demonstrate significant progress in the field of intelligent waste management, paving the way for more efficient and effective solutions. © The Author(s) 2024.

关键词： Deep learning for waste management Intelligent waste management Object detection in waste management Sustainable waste processing Urban solid waste Waste image classification

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Ecofriendly conversion of marble waste into value-added tiles for green building

Ecofriendly conversion of marble waste into value-added tile...

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International Conference on Innovation and Technological Advances for Sustainability, ITAS 2023

作者： Kurdi, Mo Hamed Al Ghafri, Khalifa Al Hamad, Fahad Hassan, Khalifa Kurdi, Jamal Michaud, Michel Department of Chemical Engineering Technology University of Doha for Science and Technology Doha Qatar Department of Mechanical Engineering University of Doha for Science and Technology Doha Qatar

ISBN: (纸本)9781032803722

Sustainable manufacturing is urgently required nowadays, more than ever before, to overcome current challenges in climate changes, depleting natural resources and polluting environment. Based on the Qatar National Vision 2030 (QNV 2030) and the third Qatari National Development Strategy (2023–2027), converting industrial solid waste in Qatar into value-added products is an important target which should be implemented to ensure sustainable consumption and production patterns as set by the United Nations, in the global goal: SDG 12. Away from dumping in landfills, preserving value of waste and byproduct in Qatari industries is an ideal approach to maximize economic gain, keep clean environment, optimize sustainability and reduce carbon footprint. Upgrading existing industrial procedures and increasing recycling rate should be considered for the production of new or improved quality products. Marble mining and processing generate around 200 million tons of waste per year worldwide. Quarrying, cutting, sawing, sizing, carving and polishing marbles produce aqueous slurry, sludge, powder or dust wastes from marble materials. These wastes lead to destructive irreversible impacts on ecological systems, the environment, and public health, particularly when they are discharged arbitrarily to the environment or even dumped into the landfills. Converting waste marble powder into alternative marketable products at a lower cost or better performance compared to that for the current existing products will promote sustainable economic growth and development. Marble waste can be used in different applications such as asphalt, road construction, gypsum plaster, cement, aggregates, concrete, mortar, brick making and other building materials. Also, marble waste can be used for replacing the traditional clay, fillers and other conventional materials to manufacture of high-performance hybrid composites. The socioeconomic benefits of producing hybrid polymer composites are not only recycl

关键词： Carbon footprint

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A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 965-981页

作者： Yong-Chao Li Rui-Sheng Jia Ying-Xiang Hu Hong-Mei Sun the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590 the Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266000China the College of Computer Science and Engineering Shandong University of Science and TechnologyQingdao 266590China the College of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210000China

In a crowd density estimation dataset,the annotation of crowd locations is an extremely laborious task,and they are not taken into the evaluation *** this paper,we aim to reduce the annotation cost of crowd datasets,and propose a crowd density estimation method based on weakly-supervised learning,in the absence of crowd position supervision information,which directly reduces the number of crowds by using the number of pedestrians in the image as the supervised *** this purpose,we design a new training method,which exploits the correlation between global and local image features by incremental learning to train the ***,we design a parent-child network(PC-Net)focusing on the global and local image respectively,and propose a linear feature calibration structure to train the PC-Net simultaneously,and the child network learns feature transfer factors and feature bias weights,and uses the transfer factors and bias weights to linearly feature calibrate the features extracted from the Parent network,to improve the convergence of the network by using local features hidden in the crowd *** addition,we use the pyramid vision transformer as the backbone of the PC-Net to extract crowd features at different levels,and design a global-local feature loss function(L2).We combine it with a crowd counting loss(LC)to enhance the sensitivity of the network to crowd features during the training process,which effectively improves the accuracy of crowd density *** experimental results show that the PC-Net significantly reduces the gap between fullysupervised and weakly-supervised crowd density estimation,and outperforms the comparison methods on five datasets of Shanghai Tech Part A,ShanghaiTech Part B,UCF_CC_50,UCF_QNRF and JHU-CROWD++.

关键词： Crowd density estimation linear feature calibration vision transformer weakly-supervision learning

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Interfacial Ru nanoclusters in tandem with single atoms on oxygen-vacancy regulated CeO_(2)for anion exchange membrane seawater-splitting

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Journal of Energy Chemistry 2025年第3期102卷 618-627页

作者： Yue Wang Jing Li Pengfei Yang Hongdong Li Guangrui Xu Yunmei Du Caixia Li Wei Jin Tianyi Ma Zexing Wu Lei Wang Key Laboratory of Eco-chemical Engineering Ministry of EducationInternational Science and Technology Cooperation Base of Eco-chemical Engineering and Green ManufacturingCollege of Chemistry and Molecular EngineeringCollege of Chemical EngineeringQingdao University of Science&TechnologyQingdao 266042ShandongChina College of Chemical Engineering Qingdao University of Science and TechnologyQingdao 266042ShandongChina College of Materials Science and Engineering Qingdao University of Science&TechnologyQingdao 266042ShandongChina College of Environment and Safety Engineering Qingdao University of Science and TechnologyQingdao 266042ShandongChina School of Environmental Science and Engineering Suzhou University of Science and TechnologySuzhou 215009JiangsuChina School of Science STEM CollegeRMIT University 3083VictoriaAustralia

A hydrogen spillover-bridged water dissociation/hydrogen formation could concurrently promote Volmer/Tafel process and improve the efficiency of hydrogen evolution reaction(HER)under alkaline ***,it is still challenging to promote occurrence of hydrogen spillover for the large interfacial transport barriers of H_(2)O and hydrogen on active ***,the strategy of energy barrier gradient to induce hydrogen spillover was proposed by constructing Ru nanoclusters coupled with single atom onto oxygen vacancy cerium dioxide(Ru/CeO_(2)-Ov-2).Density functional theory(DFT)calculations uncover that the adsorption/desorption of H2O occurs at the Ru clusters sites and then the dissociated H*spontaneously overflows from Ru clusters with high binding energy into the adjacent Ru single atom sites with low binding energy,which facilitate the hydrogen ***,the synthesized Ru/CeO_(2)-Ov-2 exhibits a small overpotential of 41 mV at 10 mA cm^(-2)and good stability at 500 mA cm^(-2)for 100 h in alkaline seawater,which could be ascribed to the rapid hydrogen spillover and strong coupling interaction between Ru and CeO_(2)-O_(v).This work provides a novel insight that synthesizing cooperative sites with energy barrier gradient helps to promote hydrogen spillover and accelerate the Volmer/Tafel process of HER.

关键词： Electrocatalyst CeO_(2) Ru Oxygen vacancy Hydrogen evolution reaction

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Federated Learning with Kalman Filter for Intrusion Detection in IoT Environment 8

Federated Learning with Kalman Filter for Intrusion Detectio...

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8th IEEE International Energy Conference, ENERGYCON 2024

作者： Almesleh, Ziad Gouissem, Ala Hamila, Ridha College of Engineering Qatar University Qatar College of Engineering and Technology University of Doha for Science & Technology Qatar

ISBN: (纸本)9798350382150

Enhancing the IoT (Internet of Things) network for reliability prompted a heightened focus on device security, given their diverse characteristics and sensitive data exchange. Federated Learning (FL) gained attention for its collaborative approach, sharing only local models, not data, among devices in IoT networks. Additionally, the non-i.i.d. data distribution complexity adds another layer to the network’s challenges. In this article, we propose FedKF as a model approach for a federated learning algorithm with KF (Kalman Filter). This approach improves the performance of the IDS (Intrusion Detection System), especially for IoT data. In this model, each edge client trains the data locally to form a local model, which is then aggregated on a central server to create a global model. The FedKF aggregation algorithm employs a KF to predict and estimate the aggregation weight, where the prediction is based on the current measured weight of aggregated global models and the previous model weight. Furthermore, by selecting clients and allowing only selected devices to participate in the training process, the overall energy consumption can be reduced. Therefore, it’s essential to balance energy savings with the performance of the federated learning model, ensuring that the model remains accurate and effective despite reduced participation. The experimental results demonstrate the model’s performance across different IoT datasets, compare the results with the average FL model, and verify the noticeable improvement in accuracy and communication loss. The model also shows the effect of client selection on the model’s performance. ©2024 IEEE.

关键词： Learning systems

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Technical review of atmospheric water harvesting in a harsh environment (in Qatar)

Technical review of atmospheric water harvesting in a harsh ...

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International Conference on Innovation and Technological Advances for Sustainability, ITAS 2023

作者： Gannan, Aiyad Aljarrah, Mohannad Department of Mechanical Engineering University of Doha for Science and Technology Doha Qatar Department of Chemical Engineering University of Doha for Science and Technology Doha Qatar

ISBN: (纸本)9781032803722

This study is being carried out to review and investigate several sustainable water harvesting techniques from atmospheric humidity, fogs, and dew. This investigation will show how well different fog/dew collectors’ function in collecting water. Furthermore, a feasibility study will be carried out to obtain the technical details of the fog collector and efficiency enhancements. Of course, the prevalence of fog globally places a restriction on fog harvesting technologies. Dew water harvesters, on the other hand, are universally accessible but call for a cooled condensing surface. The dew water collection systems will also be investigated in this study. The main goal of all these strategies is the creation of an atmospheric water collector that can produce water regardless of the humidity level, location, and cost, or materials available. This project aims to adapt Atmospheric Water Harvesting (AWH) system design and material to ensure excellent performance and reliability of AWH in harsh conditions such as in Qatar. It will be particularly focused on the development of passive system. High efficiency solar cell technologies are proposed here as selected candidates for desert AWH development. © 2025 The Author(s).

关键词： Atmospheric humidity

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Balanced Fracturing and Cold-welding of Magnesium during Ball Milling Assisted by Carbon Coating:Experimental and Molecular Dynamic Simulation

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Journal of Wuhan university of technology(Materials science) 2024年第4期39卷 895-903页

作者：韩宗盈 DONG Hui DING Guoyang ZHANG Jiale SONG Xiufang College of Energy Storage Technology Shandong University of Science and TechnologyQingdao 266590China College of Chemical and Biological Engineering Shandong University of Science and TechnologyQingdao 266590China

The lignite-derived carbon from self-protection pyrolysis was employed to balance the fracturing and cold-welding of magnesium during ball *** size analysis indicates that the introduction of lignite-derived carbon can effectively reduce the particle size of Mg while the introduction of graphite does no ***,the effect of lignite-derived carbon on crystallite size reduction of Mg is also better than graphite.A moderate cold-welding phenomenon was observed after ball-milling Mg with the lignite-derived carbon,suggesting less Mg is wasted on the milling vials and *** dynamic simulations reveal that the balanced fracturing and cold-welding of magnesium during ball milling is mainly attributed to the special structure of the lignite-derived carbon:graphitized short-range ordered stacking function as dry lubricant and irregular shape/sharp edge function as milling *** preliminary findings in current study are expected to offer implications for designing efficient Mg-based hydrogen storage materials.

关键词： magnesium lignite-derived carbon cold-welding ball milling molecular dynamic

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