Browse Items (2150 total)
Sort by:
-
Sustainability Indicators and Ten Smart Cities Review
The motivation of smart cities is to improve the standard of living of citizens and enhance the use of technology in sustainable city services. A city's sustainability can be measured using various sets of smart indicators. This study will analyse urban sustainability indicators as a research problem for ten smart cities. The review of smart cities will focus on the Internet of things (IoT), Mobile devices, and Artificial intelligence technologies (Sensors in street lights, smart homes) that help our citizens transform from rural to urban areas towards sustainability. This research uses a qualitative framework for the taxonomy of the literature for the terms 'smart city' and 'sustainability' Further, the characteristics, critical technology, and IOT application for mobility are elaborated upon. Finally, we discuss ten smart city review proposals reports, based on their sustainability indicators around the world. Concluding and Future studies could focus on using sustainable indicators for developing smart cities in India. 2023 IEEE. -
Sustainable Assessment of Advanced Machine Intelligence in Clinical Safety
There is growing acknowledgment that artificial intelligence (AI) is being used to evaluate complex and vast volumes of data, producing findings without human input, in a variety of healthcare contexts, including image analysis, bioinformatics and genomics. Although this technology can offer opportunities in the diagnostic and therapeutic process, various safety-related difficulties and traps can still exist. To shed light on these opportunities and challenges, this article addresses the use of AI in healthcare and its security consequences. To deliver safer technology through AI, this research explores the cost implications of all potential technological systems, while design safety, failure safety, procedural security, and safety margins are the primary methods for identifying risks & uncertainties. Additionally, the suggestion involves the identification and distribution of explicit instructions and procedures to all relevant parties, aiming to facilitate the creation and implementation of safer Al applications within healthcare settings. 2023 IEEE. -
Sustainable Climatic Metrics Determination with Ensemble Predictive Analytics
Sustainable features are dependent on vital climatic elements that has a prominent impact on the retention of sustainability provided its metrics are in desired domain. Regression analysis and ensemble learning models are some of the predictive analytics methods which were used to detect the association of every feature on sustainable criteria. Weather samples from Delhi during 1970-2020 is used in the research which considers features like humidity, pollutant level, temperature etc which are gathered from several authenticated sites like pollution management unit of India. After analyzing several elements affecting weather endurability, it is noticed that pollutant level and temperature exhibit the highest significance recording 30% and 44% respectively. Also the R-square metric of 86% and 82% was observed with implementation of analytics models. The major conclusion recorded that random forest outperformed regression model and it established the importance of predictive analytics in predicting sustainability results. The research validated the relevance of climatic tracking for regulating sustainability. 2023 IEEE. -
Sustainable Development- Adopting a Balanced Approach between Development and Development Induced Changes
The emergence of globalization has raised serious concerns and promoted ever increasing dichotomy between development and climate change issues that are borne out of such trade development plans and strategies. The sustainable development goals embark on 17 broad categories that calls upon the nations to achieve them by 2030. In order to achieve these goals the need of the hour is to make a paradigm shift from traditional trade agreements and policies to such agreements that aim to prioritize the attainment of these goals. There has to be uniform environment laws to promote intergeneration and intra-generational equity among the nations and leaving no lacuna for geographical disparity. The Artificial Intelligence can play a pivotal role in achieving sustainability by cross fertilization of technology and sustainable development leading to smart states, effective utilization of resources, green investment policies, use of eff icacious renewable energy resources, analyzing agricultural needs and prior analyses of prospective disasters. The Electrochemical Society -
Sustainable driven Predictive Approaches to Address Climatic Crisis: Issues and Challenges
The issue of climate crisis is currently one of the critical challenges humanity faces in the present era and it holds significant implications, for the future of our planet. To gain an understanding and mitigate the impacts of climate change several methods have been developed to model and forecast future climate trends. This paper critically analyzes sustainable techniques utilized in studying the climate crisis, such as statistical models, machine learning algorithms and climate simulations. The strengths and limitations of each method is analyzed while also considering the factors that can affect their accuracy and reliability. By consolidating existing research on this subject our aim is to provide insights into the effective sustainable approaches for predicting our climates future trajectory while offering suggestions for further research, in this crucial field. 2023 IEEE. -
Sustainable Interior Designing in the 21st Century - A Review
The concept of Sustainable interior designing has gained recognition in recent times. The study focuses on the history, growth and the future of sustainable interior designing. The main aim of the research was to review 102 select journal articles from various Sustainability, Interior designing and combined fields from 2001 all through to 2020, to provide an apprehension on the frequency, study methods, data collection and analysis procedures of the reviewed articles; Alongside providing the readers with an insight on the functionality, aesthetic appeal, client satisfaction and benefits to both environment and the clients. The study also sheds light on the important concepts of Biomimicry, Biophilia and Natural Luxury. The Electrochemical Society -
Sustainable Supply Chain Analytics for Anomalously Potential Fraudulent Logistics
The primary focus of this research is to detect potential anomalous and fraudulent cotton ginning transactions. The analysis of monitoring systems utilizing substantial analytics is often time-consuming and requires painstaking analysis afterward. In addition, the paper discusses how Third-Party Logistics affects the warehousing process and its antidromic role in distribution channels. Data for this study came from an established cotton gin operation in Tanganyika/Tanzania-East Africa. Ultimately, the results should allow cotton ginning to be improved by understanding anomalous activities. Cotton ginning fraud will be explained for the first time in scholarly journals using supply chain analytics. 2022 IEEE. -
Sustainable Technologies for Recycling Process of Batteries in Electric Vehicles
The effective management of batteries has always been a key concern for people because of the imposing challenges posed by battery waste on the environment. This paper explores strategic perspectives on the sustainable management of batteries incorporating modern techniques and scientific methodologies giving batteries a second-life application. A paradigm shift towards the legitimate use of the batteries by the introduction of round economy for battery materials and simultaneously checking the biological impression of this fundamental innovation area. 2023 IEEE. -
SVM Based AutoEncoder for Detecting Dementia in Young Adults
Dementia's impact on cognitive function necessitates timely diagnosis for effective intervention. Understanding the need for timely detection, the proposed work integrates SVM's decision boundary determination and autoencoder's noise reduction capabilities. The proposed work advances in dementia detection in young adult. Results indicate promising performance, with the model achieving high accuracy around 85.33%. The ROC curve illustrates a balanced trade-off between sensitivity and specificity, while the precision-recall curve highlights effective classification. Importantly, the model surpasses existing literature, underscoring its practical utility. While acknowledging limitations, such as parameter fine-tuning, this study lays the groundwork for refining and expanding this innovative methodology. In summary, this research contributes to the urgent field of early dementia detection, potentially transforming patient care and intervention strategies. 2023 IEEE. -
Svsl on combination of star with path
Super Vertex Sum Graph is a graph which admits super vertex sum labeling. In this paper, we combine stars and paths under different combinations which results in formation of new graphs and construct algorithm to obtain optimal super vertex sum labeling for the new graphs formed and their super subdivided graphs. 2020 Author(s). -
Swarm Intelligence Decentralized Decision Making In Multi-Agent System
This research aims to understand how groups of agents can make decisions collectively without relying on a central authority. The research could focus on developing algorithms and models for distributed problem solving, such as consensus-reaching and voting methods, or for coordinating actions among agents in a decentralized manner. The research could also look into the application of these methods in various fields like distributed robotics, swarm intelligence, and multi-agent systems in smart cities and transportation networks. Swarm intelligence in decentralization is an emerging field that combines the principles of swarm intelligence and decentralized systems to design highly adaptive and scalable systems. These systems consist of a large number of autonomous agents that interact with each other and the environment through local communication and adapt their behaviors based on environmental cues. The decentralized nature of these systems makes them highly resilient and efficient, with potential applications in areas such as robotics, optimization, and block chain technology. However, designing algorithms and communication protocols that enable effective interaction among agents without relying on a centralized controller remains a key challenge. This article proposes a model for swarm intelligence in decentralization, including agents, communication, environment, learning, decision-making, and coordination, and presents a block diagram to visualize the key components of the system. The paper concludes by highlighting the potential benefits of swarm intelligence in decentralization and the need for further research in this area. 2023 IEEE. -
Synergizing Insights for Precise Rice Leaf Disease Diagnosis Via Multi-Modal Fusion
Rice holds a significant position in India, especially in the southern part of the country, where people tend to eat some rice at least once a day. Farmers are facing a huge loss due to diseases in leaf, which is the main problem of agriculture. By using techniques like machine learning, main problems detection can be done. This review, discusses common plant diseases that affect the leaf. Some include Leaf Spots, Rusts, Fusarium Wilt, Early Blight, Powdery Mildew and Downey Mildew. Our research found that machine learning techniques on rice plants make finding diseases on leaves easier. Finally, we concluded that the most accurate method is the Enhanced VGG16, with an accuracy of 99.60% because it is really good at spotting diseases on rice leaves because it's great at recognizing the small details and patterns in leaf pictures. This helps it to tell the diseases apart more accurately and make fewer mistakes in identifying them. 2024 IEEE. -
Synergizing Senses: Advancing Multimodal Emotion Recognition in Human-Computer Interaction with MFF-CNN
Optimizing the authenticity and efficacy of interactions between humans and computers is largely dependent on emotion detection. The MFF-CNN framework is used in this work to present a unique method for multidimensional emotion identification. The MFF-CNN model is a combination of approaches that combines convolutional neural networks and multimodal fusion. It is intended to efficiently collect and integrate data from several modalities, including spoken words and human facial expressions. The first step in the suggested system's implementation is gathering a multimodal dataset with emotional labels added to it. The MFF-CNN receives input features in the form of retrieved facial landmarks and voice signal spectroscopy reconstructions. Convolutional layers are used by the model to understand hierarchies spatial and temporal structures, which improves its capacity to recognize complex emotional signals. Our experimental assessment shows that the MFF-CNN outperforms conventional unimodal emotion recognition algorithms. Improved preciseness, reliability, and adaptability across a range of emotional states are the outcomes of fusing the linguistic and face senses. Additionally, visualization methods improve the interpretability of the model and offer insights into the learnt representations. By providing a practical and understandable method for multimodal emotion identification, this study advances the field of human-computer interaction. The MFF-CNN architecture opens the door to more organic and psychologically understanding human-computer interactions by showcasing its possibilities for practical applications. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Synergy Unleashed: Smart Governance, Sustainable Tourism, and the Bioeconomy
This study investigates the transformational potential of smart Governance in the tourism sector to enhance the operational effectiveness, transparency, and efficacy of governmental actions. This research synthesises the body of knowledge regarding the use of technology and data-driven methods in Governance using a literature review methodology. A conceptual framework is suggested to highlight the complex effects of smart Governance on many stakeholders in the travel industry. The study uses a multidimensional paradigm that includes agile leadership, stakeholder alliances, network management, and adaptive Governance. It explains how these complementary components construct a revolutionary ecology that encourages creativity, adaptability, and inclusive growth. Organisations can acquire insights into visitor behaviours, preferences, and traffic patterns by utilising data analytics and digital platforms, which can improve resource allocation, infrastructure construction, and policy formation. Applications that use real-time data enable dynamic crowd control, traffic optimisation, and safety improvements. The report also highlights how local communities may be involved in smart Governance to promote inclusive decision-making. This framework helps promote deeper study into the actual application and outcomes of smart Governance, which has the potential to change the travel sector. This multidisciplinary approach fosters resilience, innovation, and responsible, inclusive development. This study promotes real-world applications that fully utilise this synergy to further the interconnected objectives of sustainable tourism, bioeconomic growth, and efficient Governance. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Synthesis and Characterization of Carbon Nanomaterial Derived from Anthracite
Among various storage devices, carbon based supercapacitors grabs the recent trends in the electronic devices. The present research work describes the synthesis of carbon nanomaterials derived from anthracite by using staudenmaier method. Anthracite was used as a precursor because of its high carbon content. The structural and chemical complex formation carried out by using XRD and FTIR confirms the formation of CNT's. The calculated value obtained from the XRD peaks confirms the formation of multilayer carbon nano-materials. The electrode was prepared by coating synthesized CNT on copper rod. The electrochemical performance of prepared working electrode was carried out by using cyclic voltammetric performance. Electrode characterization was performed for different scan rates 10, 20, 30 and 50 mV/sec in a potential window from-0.08 to 0.2V. The CV curves represents symmetric nature which imply that electrode material have stable capacitive process. 2019 Elsevier Ltd. -
Synthesis and characterization of Chitosan-CuO-MgO polymer nanocomposites
In the present work, we have synthesized Chitosan-CuO-MgO nanocomposites by incorporating CuO and MgO nanoparticles in chitosan matrix. Copper oxide and magnesium oxide nanoparticles synthesized by precipitation method were characterized by X-ray diffraction and the diffraction patterns confirmed the monoclinic and cubic crystalline structures of CuO and MgO nanoparticles respectively. Chitosan-CuO-MgO composite films were prepared using solution- cast method with different concentrations of CuO and MgO nanoparticles (15 - 50 wt % with respect to chitosan) and characterized by XRD, FTIR and UV-Vis spectroscopy. The X-ray diffraction pattern shows that the crystallinity of the chitosan composite increases with increase in nanoparticle concentration. FTIR spectra confirm the chemical interaction between chitosan and metal oxide nanoparticles (CuO and MgO). UV absorbance of chitosan nanocomposites were up to 17% better than pure chitosan, thus confirming its UV shielding properties. The mechanical and electrical properties of the prepared composites are in progress. 2018 Author(s). -
Synthesis and characterization of graphene filled PC-ABS filament for FDM applications
Present investigation focuses on development of graphene filled PC-ABS filament for Fused Deposition Modeling applications. Compounding and twin screw extrusion was employed to synthesis graphene filled FDM filament of 1.75mm diameter. Percentage of graphene was varied from 0.1 vol% to 0.25 vol% in steps of 0.05. Developed filaments were subjected to SEM studies, dimensional accuracy and density measurements. In order to achieve filament of 1.75mm diameter, filament extrusion temperature was optimized using Taguchi's L25 orthogonal array, microstructure shows homogeneous dispersion of graphene particles in PC-ABS matrix, density decreases with increased content of graphene particles. 2018 Author(s). -
Synthesis and characterization of Poly-Vinyl Alcohol-Alumina composite film: An efficient adsorbent for the removal of Chromium (VI) from water
Composite poly vinyl alcohol-alumina films were synthesized by a novel eco-friendly route in the absence of template. The physico-chemical nature of the synthesized film was studied using different characterization techniques. The poly vinyl alcohol-alumina composite film was found to be an efficient adsorbent for the removal of Chromium (VI) at higher concentrations from water. The preparation conditions were optimized to synthesize an efficient adsorbent film for the removal of chromium. The surface properties, chemical composition and amorphous nature of the film confirmed by different characterisation techniques attributes to the chromium removal efficiency of the film. Poly vinyl alcohol-alumina films are economically cheap, easy to prepare, efficient adsorbent for removal of chromium (VI) eco-friendly in nature and reusable with effortless regeneration methods. 2022 -
Synthesis and Studies on Partially Stabilized Zirconia and Rare-Earth Zirconate Pyrochlore Structured Multilayered Coatings
This work is focused on the thermal fatigue behaviour studies of ceramic coatings, as TBC (Thermal Barrier Coating) system, its importance in determining the thermo-mechanical properties and service-life estimation of the coatings when exposed to elevated operating temperatures. Commercial 6-8%Yttria stabilized zirconia (YSZ) top coat (TC) and NiCrAlY bond coat (BC) in (a) conventional YSZ (BC and TC), (b) multi-layered functionally graded materials (FGM) i.e., BC-blend (50BC+50TC)-(TC) configuration and (c) lab synthesized Zirconia based pyrochlore (Lanthanum Zirconate-LZ) were the coating materials involved. Nickel based super alloy Inconel 718 substrates were coated by using Atmosphere Plasma Spray (APS) system with three different (varying power) plasma spray parameters. All the sides of the 25mm x 10mm x 5mm thick substrates were completely covered with the bond coat and ceramic coating. FGM configuration was spray coated only on one side of the Inconel flat plates. Thermal shock cycle tests were performed on the coated specimen by following the ASTM B214-07 guidelines which comprised of introducing the coated specimen in a muffle furnace at 1150C, held in it for 2 minutes before removing from furnace followed by forced fan air cooling (one shock cycle). The specimen were periodically subjected to visual inspection for faults, before continuing the shock cycles, until the coating flaked off or cracked or detached from substrate. Cross section metallographic samples were prepared and analysed under SEM (Scanning Electron Microscope) and Energy Dispersive spectroscope (EDS) to study the as-sprayed coating morphology and interface quality, measure coating thickness, study defects characteristics and the chemical composition. Crystal structural phases were analysed using X-Ray Diffraction (XRD). 2019 Elsevier Ltd. -
Synthesis of 1, 8-Naphthyridine-3-Carbonitriles under solvent-free conditions using ceric ammonium nitrate
1,8-naphthyridines are synthesized using a four-component, one-pot approach. This method includes the reaction of aromatic aldehyde, malononitrile, 1,6-dimethylpyridin-2(1H)-one, substituted aniline in a solvent-free condition catalyzed by Ceric Ammonium Nitrate (CAN). Contrary to the reported literature, this distinct method houses several promising factors to the same degree as solvent-free reaction conditions, shorter reaction duration, excellent yields, and a straightforward extraction process. 2023 Elsevier Ltd. All rights reserved.