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International Conference on Business Development and Human Resource Management (IC-BDHRM)

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Articles

Utilizing Waste Biomass Resources for Organosolv Lignin Barrier Paper Coatings

Gregor Lavrič, Aleksandra Zamljen, Janja Juhant Grkman, Edita Jasiukaitytė-Grojzdek, Miha Grilc, Blaž Likozar, Diana Gregor-Svetec and Urška Vrabič-Brodnjak

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This abstract investigates the utilization of waste biomass resources to produce organosolv lignin barrier paper coatings. Lignin, a natural polymer found in biomass, has shown promise as a renewable and sustainable alternative to synthetic coatings in paper production. This study explores the organosolv process as a method to extract lignin from waste biomass and develop barrier coatings for paper applications. Through experimental analysis and characterization, the study assesses the performance of organosolv lignin coatings in providing barrier properties such as water resistance, grease resistance, and oxygen permeability. Furthermore, the abstract discusses the environmental benefits of using waste biomass as a feedstock for lignin production, highlighting the potential for reducing reliance on fossil-based materials and mitigating environmental impacts. By showcasing the feasibility and advantages of organosolv lignin barrier coatings, this research contributes to advancing sustainable practices in the paper industry and promoting the utilization of renewable resources for value-added applications.

Analyzing the Driving Forces of Agricultural Economic Growth in Ningxia, Northwest China, through Water Utilization Effects: A Study Using the LMDI Method

Jie Du, Zhaohui Yang, Guiyu Yang, Shuoyang Li and Ziteng Luo

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This abstract investigates the driving forces behind agricultural economic growth in Ningxia, Northwest China, focusing on the impact of water utilization effects. Using the Logarithmic Mean Divisia Index (LMDI) method, this study analyzes the contributions of various factors to agricultural economic growth, with a particular emphasis on water utilization efficiency. Ningxia faces significant challenges related to water scarcity and agricultural sustainability, making it imperative to understand the dynamics between water use and economic development. Through empirical analysis and data modeling, the study identifies key drivers of agricultural economic growth and quantifies the specific contributions of water utilization effects. The findings shed light on the complex interactions between water resources management and economic performance in arid regions. By leveraging the LMDI method, this research provides valuable insights for policymakers and stakeholders seeking to optimize water use efficiency and promote sustainable agricultural development in Northwest China and similar regions globally.

Developing an Evaluation Framework for Intelligent Transport Systems in Public Transportation: A Case Study of Bangkok Metropolitan Region Using Fuzzy AHP

Aoonrot Choosakun and Chunho Yeom

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This abstract outlines the development of an evaluation framework for Intelligent Transport Systems (ITS) in public transportation, focusing on the Bangkok Metropolitan Region. Leveraging the Fuzzy Analytic Hierarchy Process (AHP), this study aims to address the complexities and uncertainties inherent in assessing ITS implementations. Bangkok, like many other rapidly growing urban areas, faces numerous challenges in its public transportation system, including congestion, pollution, and safety concerns. Through the proposed evaluation framework, key performance indicators for ITS are identified, prioritized, and weighted using fuzzy AHP methodology. The abstract discusses the significance of integrating fuzzy logic with AHP to handle the vagueness and ambiguity often encountered in evaluating ITS projects. By providing a structured approach to assess the effectiveness and efficiency of ITS in improving public transportation, this research offers valuable insights for policymakers, urban planners, and transportation authorities in Bangkok and beyond. Ultimately, the abstract underscores the importance of evidence-based decision-making to enhance urban mobility and sustainability in rapidly evolving metropolitan regions.

Addressing Transport Inequalities: Mapping the Research Landscape of Intelligent Transportation Systems Adoption in Africa

Olasupo O. Ajayi, Antoine B. Bagula, Hloniphani C. Maluleke and Isaac A. Odun-Ayo

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This abstract surveys the research landscape concerning transport inequalities and the adoption of Intelligent Transportation Systems (ITS) in Africa. While ITS has the potential to address transportation challenges, including congestion and safety issues, its implementation in Africa has been uneven. This study examines existing research to understand the factors influencing the adoption of ITS in the continent's diverse socio-economic and infrastructural contexts. By mapping the research landscape, this study identifies key themes, trends, and gaps in knowledge regarding transport inequalities and ITS adoption in Africa. The abstract highlights the importance of addressing these disparities to promote equitable and sustainable transportation systems across the continent. Through a comprehensive analysis of the existing literature, this research provides insights to inform policymakers, researchers, and practitioners working towards enhancing transportation accessibility and efficiency in Africa.

Time Delay-Based Multipath Routing Protocol for Intelligent Transport Systems in Vehicular Ad Hoc Networks

Yashar Ghaemi, Hosam El-Ocla, Nitin Ramesh Yadav, Manisha Reddy Madana, Dheeraj Kurugod Raju, Vignesh Dhanabal and Vishal Sheshadri

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This abstract investigates the implementation of a time delay-based multipath routing protocol within Intelligent Transport Systems (ITS) for Vehicular Ad Hoc Networks (VANETs). VANETs play a pivotal role in enhancing road safety, traffic efficiency, and communication among vehicles and infrastructure. However, the dynamic nature of vehicular environments poses challenges for reliable and efficient data transmission. This study proposes a novel multipath routing protocol based on time delay considerations to improve the robustness and performance of ITS in VANETs. Through simulation and performance evaluation, the protocol's effectiveness in mitigating communication disruptions and reducing latency is assessed. The abstract underscores the significance of leveraging multipath routing techniques to enhance the reliability and efficiency of communication in ITS applications. By integrating time delay considerations into the routing protocol, this research contributes to advancing the state-of-the-art in VANET communication protocols, ultimately improving the effectiveness of Intelligent Transport Systems for safer and more efficient vehicular environments.

Predictive Intelligent Transportation: Mitigating Traffic Congestion in the Internet of Vehicles

Le Zhang, Mohamed Khalgui and Zhiwu Li

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

As urbanization continues to surge, traffic congestion has become a pressing issue in many cities worldwide. The advent of the Internet of Vehicles (IoV) offers promising solutions to alleviate this congestion by leveraging predictive intelligent transportation systems. This paper explores the intersection of predictive analytics and intelligent transportation within the IoV framework to address traffic congestion proactively. Through the analysis of real-time data from vehicles, infrastructure, and other sources, predictive algorithms can anticipate traffic patterns and optimize routes, reducing congestion and travel time. Furthermore, integrating intelligent decision-making mechanisms enables dynamic adjustments to traffic flow, enhancing overall efficiency and safety. This paper examines various predictive models and algorithms employed in IoV environments and evaluates their effectiveness in mitigating traffic congestion. Additionally, it discusses the challenges and opportunities associated with implementing predictive intelligent transportation systems in real-world scenarios, including data privacy concerns and infrastructure requirements. Ultimately, this research underscores the transformative potential of predictive intelligent transportation in alleviating traffic congestion and enhancing urban mobility within the Internet of Vehicles ecosystem.

Improving Hourly Origin–Destination Matrix Estimation with Deep Learning using Intelligent Transportation Systems Data

Shahriar Afandizadeh Zargari, Amirmasoud Memarnejad and Hamid Mirzahossein

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Efficient estimation of hourly origin–destination (OD) matrices is crucial for urban transportation planning and management. In this study, we propose a novel approach that harnesses intelligent transportation systems (ITS) data and deep learning techniques to accurately estimate OD matrices at an hourly resolution. By leveraging rich data streams from various ITS sources such as traffic sensors, GPS data, and traffic cameras, our method utilizes deep learning models to learn complex spatial-temporal patterns in urban traffic flow. Specifically, we employ convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to capture both the spatial correlations between different locations and the temporal dynamics of traffic demand throughout the day. Through extensive experiments on real-world datasets, we demonstrate the effectiveness and scalability of our approach in accurately estimating hourly OD matrices. Furthermore, we compare our method with existing approaches and showcase its superior performance in terms of estimation accuracy and computational efficiency. Our research highlights the potential of combining ITS data and deep learning techniques to enhance the estimation of OD matrices, thereby facilitating more informed decision-making in urban transportation management.

Optimizing Zwitterionic Salts for Rapid Discovery of Thermoresponsive Materials in Structural Engineering

Yen-Ho Chu, Chien-Yuan Chen and Jin-Syuan Chen

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This study delves into the structural engineering and optimization of zwitterionic salts to expedite the discovery of thermoresponsive materials. By leveraging advanced computational methods and experimental techniques, we explore the design space of zwitterionic salts to uncover novel materials with thermoresponsive properties. Through a systematic investigation of molecular structures, interactions, and thermodynamic behavior, we identify key design principles for enhancing the thermoresponsive nature of these materials. Our approach combines computational modeling, synthesis, and characterization to efficiently screen and optimize zwitterionic salts for targeted applications in structural engineering. We demonstrate the efficacy of our methodology through the discovery of promising thermoresponsive materials with tunable properties and enhanced performance. This research not only contributes to the advancement of structural engineering but also provides valuable insights into the design and optimization of thermoresponsive materials for a wide range of applications.

Comprehensive Review of Structural Health Monitoring in Composite Structures

Sahar Hassani, Mohsen Mousavi and Amir H. Gandomi

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This paper presents a comprehensive review of structural health monitoring (SHM) techniques specifically tailored for composite structures. Composite materials are increasingly used in various industries due to their high strength-to-weight ratio and corrosion resistance. However, they are susceptible to damage from various sources, such as impact, fatigue, and environmental factors. Effective SHM systems are essential for detecting and assessing damage in composite structures to ensure their safety and reliability. This review provides an overview of the different types of damage that can occur in composite materials and discusses the challenges associated with monitoring these structures. Various SHM techniques, including acoustic emission, ultrasonic testing, thermography, and guided wave-based methods, are evaluated in terms of their capabilities and limitations for detecting damage in composite structures. Additionally, advancements in sensor technologies and data analysis algorithms are discussed, highlighting recent developments and future trends in the field of SHM for composite materials. This comprehensive review serves as a valuable resource for researchers, engineers, and practitioners interested in the development and implementation of SHM systems for composite structures.

Preliminary Characterization of an Electrospun Polycaprolactone-SurgihoneyRO Mesh for Skin Tissue Engineering

Enes Aslan, Cian Vyas, Joel Yupanqui Mieles, Gavin Humphreys, Carl Diver and Paulo Bartolo

Year: 2020 | Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This study presents a preliminary characterization of an electrospun mesh composed of polycaprolactone (PCL) and SurgihoneyRO for potential application in skin tissue engineering. The electrospinning technique was employed to fabricate the mesh, and its morphology, mechanical properties, and biocompatibility were evaluated. Scanning electron microscopy (SEM) revealed the fibrous structure of the mesh, demonstrating uniformity and interconnectedness. Mechanical testing indicated sufficient mechanical strength and elasticity, suitable for supporting tissue growth and withstand physiological forces. Furthermore, in vitro biocompatibility assessments demonstrated cell adhesion and proliferation on the mesh surface, suggesting its potential for promoting tissue regeneration. Overall, this preliminary characterization highlights the promising properties of the PCL-SurgihoneyRO electrospun mesh for skin tissue engineering applications, paving the way for further development and optimization in this field.


International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

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