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arXiv 2019年

作者： Srivastava, Siddhant Tiwari, Ritu Soft Computing Laboratory ABV-IIITM Gwalior

Machine Translation (MT) is a zone of concentrate in Natural Language processing which manages the programmed interpretation of human language, starting with one language then onto the next by the PC. Having a rich research history spreading over about three decades, Machine interpretation is a standout amongst the most looked for after region of research in the computational linguistics network. As a piece of this current ace’s proposal, the fundamental center is examine the Deep-learning based strategies that have gained critical ground as of late and turning into the de facto strategy in MT. We would like to point out the recent advances that have been put forward in the field of Neural Translation models, different domains under which NMT has replaced conventional SMT models and would also like to mention future avenues in the field. Consequently, we propose an end-to-end self-attention transformer network for Neural Machine Translation, trained on Hindi-English parallel corpus and compare the model’s efficiency with other state of art models like encoder-decoder and attention based encoder-decoder neural models on the basis of BLEU. We conclude this paper with a comparitive analysis of the three proposed models. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural machine translation

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Sliding Mode Control of the PUMA 560 Robot

Sliding Mode Control of the PUMA 560 Robot

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Arezki Fekik Ahmad Taher Azar Mohamed Lamine Hamida Hakim Denoun Dyhia Kais Sabrina Mohand Saidi Amar Bousbaine Nashwa Ahmad Kamal Ammar K. Al Mhdawi Chakib Ben Njima Department of Electrical Engineering University Akli Mohand Oulhadj-Bouria Bouira Algeria Electrical Engineering Advanced Technology Laboratory (LATAGE) Algeria Automated Systems & Soft Computing Lab (ASSCL) Prince Sultan University Riyadh Saudi Arabia College of Computer & Information Sciences Prince Sultan University Riyadh Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University Egypt Department of Electrical Engineering L2CSP Laboratory Mouloud Mammeri University Algeria University of Derby College of Science and Engineering UK Faculty of Engineering Cairo University Giza Egypt Edge Hill University U.K University of Sousse Tunisia

The purpose of this article is to present the application of the sliding mode control and investigate its effectiveness when applied to a three-dimensional robotic manipulator model. The analysis is based on the application of the sliding mode control law for the PUMA 560 model, three degrees of freedom, through the development of a dynamic simulation model. The simulation results show the effectiveness of this proposed method for the automation of industrial applications, such as assembly, machining (deburring, trimming), and surface tracking (polishing). This technique provides a useful insight into the advantages of using sliding mode control laws in robotics applications.

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Vertically constructed wetlands for greywater reuse: Performance analysis of plants

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Environmental Nanotechnology, Monitoring and Management 2023年 20卷

作者： Siriwardhana, Kushan D. Miguntanna, Nandika Jayaneththi, Dimantha I. Kantamaneni, Komali Rathnayake, Upaka Water Resources Management and Soft Computing Research Laboratory Millennium City Athurugiriya 10150 Sri Lanka Department of Civil Engineering Faculty of Engineering Sri Lanka Institute of Information Technology Malabe 10150 Sri Lanka School of Engineering University of Central Lancashire Preston PR1 2HE United Kingdom Department of Civil Engineering and Construction Faculty of Engineering and Design Atlantic Technological University Sligo F91 YW50 Ireland

Vertical Flow constructed wetlands (VFCWs) are environmentally feasible engineered systems that mimic the functions of natural wetlands. They are alternative engineering systems that are economical, and simple in structure with reduced land area compared to Horizontal Flow Constructed Wetlands (HFCW). Thus provides a sustainable solution for greywater treatment to a considerable extent. However, VFCWs feasibility and plant performance were not tested in the context of Sri Lanka for the greywater treatment. Therefore, the purpose of this study is to evaluate the potential of household greywater treatment using a pilot-scale VFCW and examine the performance characteristics of different types of plants. Three types of plants, the Canna plant (Canna indica), Ferns plant (Matteuccia struthiopteris), and Cattail plant (Typha latifolia) were used as emergent plants and a retention tank was constructed to retain solid particles in the greywater as primary treatment. The experiments were carried out for two months using a Completely Randomized Design (CRD) for three replicates. The quality of the influent and effluent was tested fortnight for a number of water quality parameters. Results revealed that the removal efficiency of contaminants was increased. Cattail plants showed higher removal efficiency for dissolved oxygen (DO), chemical oxygen demand (COD), nitrates (NO₃^1-), turbidity, and electrical conductivity. In addition, Canna plants had higher efficiencies for the removal of total dissolved solids (TDS) and phosphates (PO₄^3-). Furthermore, Ferns plants presented higher efficiency only for removing sulphate (SO₄^3-). Conclusively, Cattail plants presented the overall best performance in treating greywater. This can be attributed to the ability of the Cattail's dense fibrous root system to absorb more contaminants from greywater. This research also discussed the importance of microplastic analysis in greyw

关键词： Canna plant Cattail plant Constructed wetlands Ferns plants Greywater treatment Vertical flow Construction Wetlands (VFCWs)

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Biopolymers-based microencapsulation technology for sustainable textiles development: A short review

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Case Studies in Chemical and Environmental Engineering 2023年 7卷

作者： Peng, Xiongyi Umer, Muhammad Pervez, Md. Nahid Hasan, K.M. Faridul Habib, Md Ahsan Islam, Md. Shahinoor Lin, Lina Xiong, Xiaorong Naddeo, Vincenzo Cai, Yingjie Hubei Provincial Engineering Laboratory for Clean Production and High Value Utilisation of Bio-based Textile Materials Wuhan Textile University Hubei Wuhan 430200 China School of Computing Huanggang Normal University Huanggang 438000 China Sanitary Environmental Engineering Division (SEED) Department of Civil Engineering University of Salerno via Giovanni Paolo II 132 SA Fisciano 84084 Italy Fiber and Nanotechnology Program University of Sopron Sopron 9400 Hungary South China Advanced Institute for Soft Matter Science and Technology School of Emergent Soft Matter South China University of Technology Guangzhou 510640 China Department of Chemical Engineering Bangladesh University of Engineering and Technology Dhaka 1000 Bangladesh

Microencapsulation methods in product development may result in innovative products with improved stability, functionality, and active chemical release (s). Microcapsules may be made out of biopolymers instead of synthetic polymers because of their biodegradability, lower production costs, and greater accessibility. The potential of biopolymers-based microencapsulation technology in sustainable textiles is substantial despite this field only getting started. This short review explores the role of biopolymers such as chitosan, gelatin, alginate, and cellulose in microencapsulation-mediated sustainable textile technology. The long-term effects of using microencapsulation made from biopolymers are also discussed, with an eye toward sustainability. © 2023 The Authors

关键词： Cellulose Chitosan Functional textiles Microencapsulation Sustainable textiles

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Robust Internal Model Control Boosts PMSM Performance with Fractional Order Vector Control

Robust Internal Model Control Boosts PMSM Performance with F...

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Tassadit Chekari Arezki Fekik Ahmad Taher Azar Saim Ahmed Abdelghani Djeddi Nashwa Ahmad Kamal Chakib Ben Njima L2CSP Laboratory Mouloud MAMMERI University of Tizi-Ouzou Algeria Mhamed Bougara University of Boumerdes Algeria Department of Electrical Engineering University Akli Mohand Oulhadj-Bouria Algeria Nantes Université École Centrale Nantes CNRS LS2N Nantes France College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia Automated Systems and Soft Computing Lab (ASSCL) Prince Sultan University Riyadh Saudi Arabia Faculty of Computers and Artificial Intelligence Benha University Benha Egypt Faculty of Sciences and Technology Echahid Cheikh Larbi Tebessi University Tebessa Algeria Faculty of Engineering Cairo University Giza Egypt University of Sousse Tunisia

ISBN: (数字)9798350361025

ISBN: (纸本)9798350361032

In this paper, a combination of fractional order control and a classical vector control scheme is proposed to drive the PMSM speed. The new proposed control scheme with fractional order property is based on IMC structure which is known for its robustness to modelling error and Bode’s ideal transfer function chosen as the reference model which exhibits iso-damping property. Simulation results show that the proposed control scheme tracks the PMSM speed at specified values and compensates the effect of load torque. Moreover, the time constant and fractional order of the Bode’s ideal transfer function can be used as tuning parameters to improve the PMSM speed and current responses.

关键词： Resistance Torque Simulation Transfer functions Stators Robustness Inverters

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Measuring structural parameters of crosslinked and entangled semiflexible polymer networks with single-filament tracing

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Physical Review E 2021年第6期103卷 062501-062501页

作者： Tina Händler Cary Tutmarc Martin Glaser Jessica S. Freitag David M. Smith Jörg Schnauß Peter Debye Institute for Soft Matter Physics University of Leipzig Linnéstraße 5 04103 Leipzig Germany Fraunhofer Institute for Cell Therapy and Immunology Perlickstraße 1 04103 Leipzig Germany Institute of Clinical Immunology University of Leipzig Medical Faculty 04103 Leipzig Germany Dhirubhai Ambani Institute of Information and Communication Technology Gandhinagar 382 007 India Unconventional Computing Laboratory Department of Computer Science University of the West of England Bristol United Kingdom

Single-filament tracing has been a valuable tool to directly determine geometrical and mechanical properties of entangled polymer networks. However, systematically verifying how the stiffness of the tracer filament or its molecular interactions with the surrounding network impacts the measurement of these parameters has not been possible with the established experimental systems. Here we use mechanically programmable DNA nanotubes embedded in crosslinked and entangled F-actin networks, as well as in synthetic DNA networks, in order to measure fundamental, structural network properties like tube width and mesh size with respect to the stiffness of the tracers. While we confirm some predictions derived from models based purely on steric interactions, our results indicate that these models should be expanded to account for additional interfilament interactions, thereby describing the behavior of real polymer networks.

关键词： Persistence length Polymer behavior Polymer entanglement Reptation Polymer solutions Polymer scaling theory Polymer theory Tube theories

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Feature engineering combined with 1 D convolutional neural network for improved mortality prediction

arXiv

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arXiv 2019年

作者： Maheshwari, Saumil Verma, Rohit Shukla, Anupam Tiwari, Ritu Garg, Rishu Soft Computing and Expert System Laboratory National Institute of Technology Raipur India Soft Computing and Expert System Laboratory Atal Vihari Vajpayee- Indian Institute of Information Technology and Management GwaliorM.P. India

The intensive care units (ICUs) are responsible for generating a wealth of useful data in the form of Electronic Health Record (EHR). This data allows for the development of a prediction tool with perfect knowledge backing. We aimed to build a mortality prediction model on 2012 Physionet Challenge mortality prediction database of 4000 patients admitted in ICU. The challenges in the dataset, such as high dimensionality, imbalanced distribution, and missing values were tackled with analytical methods and tools via feature engineering and new variable construction. The objective of the research is to utilize the relations among the clinical variables and construct new variables which would establish the effectiveness of 1-Dimensional Convolutional Neural Network (1-D CNN) with constructed features. Its performance with the traditional machine learning algorithms like XGBoost classifier, Support Vector Machine (SVM), K-Neighbours Classifier (K-NN), and Random Forest Classifier (RF) is compared for Area Under Curve (AUC). The investigation reveals the best AUC of 0.848 using 1-D CNN model. Copyright © 2019, The Authors. All rights reserved.

关键词： Forecasting

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Spatial mapping and analysis of forest fire risk areas in Sri Lanka – Understanding environmental significance

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Case Studies in Chemical and Environmental Engineering 2024年 9卷

作者： Makumbura, Randika K. Dissanayake, Prasad Gunathilake, Miyuru B. Rathnayake, Namal Kantamaneni, Komali Rathnayake, Upaka Water Resources Management and Soft Computing Research Laboratory Millennium City Athurugiriya 10150 Sri Lanka Faculty of Engineering and Information Sciences University of Wollongong Northfields Ave Wollongong 2522 NSW Australia Hydrology and Aquatic Environment Division of Environmental and Natural Resources Norwegian Institute of Bioeconomy and Research Ås 1431 Norway Water Energy and Environmental Engineering Research Unit Faculty of Technology University of Oulu Oulu 90014 Finland Department of Civil Engineering Faculty of Engineering The University of Tokyo 1 Chome-1-1 Yayoi Bunkyo City Tokyo 113-8656 Japan School of Engineering University of Central Lancashire Preston PR1 2HE United Kingdom Department of Civil Engineering and Construction Faculty of Engineering and Design Atlantic Technological University Sligo F91 YW50 Ireland

This study presents the first attempt in Sri Lanka to generate a forest fire risk map covering the entire country using a GIS-based forest fire index (FFI) model. The model utilized seven parameters: land use, temperature, slope, proximity to roads and settlements, elevation, and aspect. All these parameters were derived using GIS techniques with ArcGIS10.4 and QGIS3.16. Data from Remote Sensing sources, particularly the MODIS hotspot real-world dataset, were employed to gather fire count information for the year 2020. Validation was conducted through the merging hotspot technique and kernel density estimation (KDE). The research findings highlight the districts in the Central and Uva provinces, such as NuwaraEliya (10.3 km²), Kandy (2.74 km²), and Badulla (10.41 km²), as having a “very low risk" of forest fire potential. Conversely, districts like Hambanthota (0.1 km²), Kaluthara (0.04 km²), and Kurunegala (0.2 km²) exhibit a “very high risk" of forest fire potential, although it is negligible compared country's total area. Overall, the study suggests that Sri Lanka is not currently facing a significant threat of forest fires and is a “medium risk" of forest fires as 49.49% of land falls under this category. These results are of immense value to relevant authorities, including the Ministry of Wildlife and Forest Resources Conservation, in formulating effective strategies to manage and mitigate forest fire risks in the country. © 2024 The Authors

关键词： Forest fire index (FFI) Geographic information system (GIS) Kernel density estimation (KDE) MODIS hotspot Remote sensing top of form

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Dual-responsive nanogels with high drug loading for enhanced tumor targeting and treatment

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Chinese Chemical Letters 2024年

作者： Haotian Shi Yuchao Luo Song Zhang Meijun Zhao Chaoyong Liu Qing Pei Helei Wang Qiong Dai Zhigang Xie Bin Xu Wenjing Tian State Key Laboratory of Supramolecular Structure and Materials College of Chemistry Jilin University Changchun 130012 China Beijing Advanced Innovation Center for Soft Matter Science and Engineering College of Life Science and Technology Beijing University of Chemical Technology Beijing 100029 China School of Mechanical Science and Aerospace Engineering Jilin University Changchun 130022 China Research Center for Life Science Computing Zhejiang Lab Hangzhou 311100 China State Key Laboratory of Polymer Physics and Chemistry Changchun Institute of Applied Chemistry Chinese Academy of Sciences Changchun 130022 China Gastric and Intestinal Department General Surgery Center First Hospital of Jilin University Changchun 130021 China

Nanomedicine holds considerable promise for advancing cancer therapy, however, effective delivery of drugs to solid tumors remains a challenge due to rapid systemic clearance and inefficient cellular uptake. Herein, we have developed a novel charge-reversible nanogel to deliver paclitaxel (PTX) dimers (DPP) with enhanced stability and targeting precision. The nanogels exhibit a dynamic charge-reversal mechanism responsive to the acidic tumor microenvironment (TME), optimizing the cellular uptake of prodrugs. In the high glutathione (GSH) conditions within cancer cells, the disulfide bonds in the DPP are cleaved, resulting in the intracellular release of active PTX and reduced drug toxicity to normal cells. In vivo pharmacokinetic studies revealed an extended plasma elimination half-life for the charge-reversible nanocarriers, and antitumor efficacy studies demonstrated superior tumor suppression with minimal systemic toxicity. This research underscores the potential of integrating charge-reversal and responsive release mechanisms into one nanocarrier system, balancing the long circulation and high tumor cell internalization capacity of the nanocarrier, and providing a promising strategy for targeted delivery of nanomedicine.

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Crosslink-net: Double-branch encoder segmentation network via fusing vertical and horizontal convolutions

arXiv

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arXiv 2021年

作者： Yu, Qian Qi, Lei Zhou, Luping Wang, Lei Yin, Yilong Shi, Yinghuan Wang, Wuzhang Gao, Yang School of Data and Computer Science Shandong Women's University Jinan250300 China The State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China School of Computer Science and Engineering Southeast University Nanjing211189 China The School of Electrical and Information Engineering University of Sydney NSW2006 Australia The School of Computing and Information Technology University of Wollongong WollongongNSW2522 Australia The School of Soft Shandong University Jinan250100 China Department of Respiratory and Critical Care Medicine Shandong Chest Hospital Jinan250013 China

Accurate image segmentation plays a crucial role in medical image analysis, yet it faces great challenges of various shapes, diverse sizes, and blurry boundaries. To address these difficulties, square kernel-based encoder-decoder architecture has been proposed and widely used, but its performance remains still unsatisfactory. To further cope with these challenges, we present a novel double-branch encoder architecture. Our architecture is inspired by two observations: 1) Since the discrimination of features learned via square convolutional kernels needs to be further improved, we propose to utilize non-square vertical and horizontal convolutional kernels in the double-branch encoder, so features learned by the two branches can be expected to complement each other. 2) Considering that spatial attention can help models to better focus on the target region in a large-sized image, we develop an attention loss to further emphasize the segmentation on small-sized targets. Together, the above two schemes give rise to a novel double-branch encoder segmentation framework for medical image segmentation, namely Crosslink-Net. The experiments validate the effectiveness of our model on four datasets. The code is released at https://***/Qianyu1226/*** Codes 68T07 Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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