Browse Items (5511 total)
Sort by:
-
Polyamines influence the production of Boeravinone-B from cell suspension cultures of Boerhavia diffusa L.
Boerhavia diffusa L. (Punarnava) is an ayurvedic herb with a wide range of phytochemicals and pharmacological activities that have been utilised since antiquity. Boeravinone-B (an isoflavone rotenoid molecule) is one of the most significant secondary metabolites produced in its plant body. Modern plant biotechnological tools have helped in the overproduction of desired plant secondary metabolites from in vitro cell and organ cultures. Elicitation is one such strategy employed for the production of phytochemicals. In the present study, polyamines like putrescine, spermine and spermidine have been used as elicitors for the production of Boeravinone-B. The cell suspension cultures of punarnava have been treated with polyamines at various concentrations, ranging from 0.5 to 20M, at various day intervals of 2, 4 and 6 before the harvesting. The fresh weights, dry weights of cell suspension cultures, their Boeravinone-B content and yield are evaluated. Among all the various polyamine treatments, 2.5M spermidine (SPD) on the 6th day before harvesting shows the highest Boeravinone-B content of 10.88 0.13mgg?1 DW and yield of 110.34mg L?1 respectively, which is a five-fold increment compared to the control cultures (2.16 0.06mgg?1 DW and 16.35mg L?1) respectively. The highest total phenolic content in the cell suspension cultures is observed with 1?M SPD on the 2nd day prior to harvesting (194.25 0.37mgg?1 DW), while the highest levels of flavonoids are observed with 2.5?M SPD on the 6th day before harvesting (86.85 0.26mgg?1 DW). 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
Production of Boeravinone-B, total phenolic, flavonoid content and antioxidant activity from callus cultures of Punarnava (BoerhaviadiffusaL.)
Boerhavia diffusa L. (Punarnava) is a medicinal herb, rich in diversified plant secondary metabolites used in curing various health ailments. Boeravinone-B is one of the important phytochemicals reported in Punarnava, possessing various pharmacological activities. It belongs to the family of rotenoids, belonging to the isoflavone group. Production of Boeravinone-B from the Punarnava through conventional propagation is comparatively very low, and alternative interventions are of utmost importance to meet the growing demand. In view of this, the present study aims to develop biotechnological approaches like cell/tissue culture as a substitute strategy for the accumulation of biomass and Boeravinone-B biosynthesis. Callus was established from leaf explants of Boerhavia diffusa L. when cultured on MS semi solid medium fortified with varied concentrations and combinations of auxins and cytokinins. The callus induced on Murashige and Skoog medium (MS medium) supplemented with 5.0 ppm 2,4-Dichlorophenoxyacetic acid (2,4-D) favored the highest production of Boeravinone-B analyzed through High-performance Liquid chromatography (HPLC) and it was found to be 673.95 ?g g-1 Dry weight (DW). The total phenolic and flavonoid content were determined for the callus extracts and the results showed that callus induced on 5.0 ppm 2,4-D medium showed the highest phenolic and flavonoid content, which was 63.48 mg g-1 Gallic acid equivalent (GAE) Dry weight (DW), and 30.22 mg g-1 Quercetin equivalent (QE) DW. Similarly, antioxidant activities (radical scavenging, metal chelating, and reducing power) were performed, and it was found that callus induced on 5.0 ppm 2,4-D showed the highest anti-oxidant potential. Radical scavenging activity was found to be 91.1%, and 74% of metal chelating activity was recorded, and a similar trend was observed with respect to reducing power as well. The results of the present study lay foundation for optimization and subsequent large-scale production of Boeravinone-B from callus/cell suspension cultures. The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited (https://creativecommons.org/licenses/ by/4.0/) -
Nano Zinc Oxide Particle Synthesis from Bio-Waste Selaginella willdenowii Leaf Extract: A Multi-Faceted Approach for Environmental and Biomedical Applications
Selaginella willdenowii, a commonly used greenhouse fern, was often used as a biowaste to synthesize zinc oxide nanoparticles (ZnO NPs) in an eco-friendly and cost-effective way. UV-Visible spectra studies were carried out to confirm the synthesis of S. willdenowii-mediated ZnO NPs (SW-ZnO NPs), and a peak at 367nm with a sharp band gap of 3.415eV was observed. The X-ray diffraction analysis indicated that the crystalline size of the synthesized SW-ZnO NPs was 11.971nm. The phytochemicals present in the extracts and the compounds involved in the reduction of metal to nanoparticles were determined by Fourier Transform Infrared analysis. Scanning electron microscopy was utilized to analyze the surface morphology and size of the obtained SW-ZnO NPs. The examination revealed that they exhibited a hexagonal shape, with an average size falling within the range of 17-23nm. Under ultra-violet light, reactive blue 220 and reactive yellow 145 dyes showed 78.06% and 60.14% degradation, showing potential photocatalytic degradation activity. The synthesized SW-ZnO NPs also exhibited antimicrobial activity against bacterial strains (Escherichia coli and Bacillus subtilis) and fungal cultures (Candida tropicalis and Candida albicans) showed cytotoxic activity against Hep-G2 cell lines. Our results suggest the green synthesized SW-ZnO NPs have potential photocatalytic, antimicrobial and cytotoxic potential. 2024 World Scientific Publishing Company. -
Knowledge transfer: An information theory perspective
Personalization and codification are two dominant knowledge transfer (KT) mechanisms found in organizations and organizational networks. This paper proposes a theoretical model of KT that explains organizations' choice of KT mechanisms in terms of the tacitness of knowledge being shared and the corresponding information content. Shannon's entropy, an information theoretical concept, has been used to define the constructs of tacitness and information content and explain their influence on the choice of the corresponding KT mechanisms. Contributions of the paper include (a) use of information content as a predictor of the choice of KT mechanisms, (b) development of an expression for tacitness, and an intuitive explanation of the tacit-explicit continuum, (c) characterization of product variety in terms of information content, and (d) development of a KT theoretical model that can be operationalized for predicting the choice of KT mechanisms in real-life situations. 2017 The OR Society. -
Classification of supply chain knowledge: A morphological approach
Purpose The purpose of the article is to create a knowledge classification model that can be used by knowledge management (KM) practitioners for establishing a knowledge management framework (KMF) in a supply chain (SC) network. Epistemological and ontological aspects of knowledge have been examined. SC networks provide a more generic setting for managing knowledge due to the additional issues concerning flow of knowledge across the boundaries of organizations. Design/methodology/approach Morphological analysis has been used to build the knowledge classification model. Morphological approach is particularly useful in exploratory research on concepts/ entities having multiple dimensions. Knowledge itself has been shown in literature to have many characteristics, and the methodology used has enabled a comprehensive classification scheme based on such characteristics. Findings A single comprehensive classification model for knowledge that exists in SC networks has been proposed. Nine characteristics, each possessing two or more value options, have been finally included in the model. Research limitations/implications Knowledge characteristics have been mostly derived from past research with the exception of three which have been introduced without empirical evidence. Although the article is primarily about SC knowledge, the results are fairly generic. Practical implications The proposed model would be of use in developing KM policies, procedures and establishing knowledge management systems in SC networks. The model will cater to both system and people aspects of a KMF. Originality/value The proposed knowledge classification model based on morphological analysis fills a gap in a vital area of research in KM as well as SC management. No similar classification model of knowledge with all its dimensions has been found in literature. Emerald Group Publishing Limited. -
Work life balance among women anganwadi workers in Bengaluru
Over the past few years, worklife balance has evolved into a matter of significant concern. Both men and women strive to achieve a steady professional and personal life. In reality, women are more prone to experiencing such challenges. The paper attempted to understand worklife balance among Anganwadi workers (women-dominant centres). The research focused on the impact of job satisfaction, work overburden, workplace support, family support, and dependent care on the worklife balance of Anganwadi workers. For the purpose of the study, a structured questionnaire was administered to 467 participants. Statistical technique used for the study was regression model. The results indicated that workplace support and family support had a positive impact on the worklife balance among Anganwadi workers. The findings also suggested that work overburden and dependent care had a negative impact on worklife balance. The results also contradicted the hypotheses by portraying that job satisfaction was not a significant factor that impacted the worklife balance among Anganwadi workers. However, many other variables such as emotional intelligence, job autonomy, turnover intention, absenteeism, and work engagement that could potentially impact worklife balance were not taken into consideration. 2020, Associated Management Consultants Pvt. Ltd.. All rights reserved. -
Experimental Investigation of Uniaxial Compressive Behavior of Composite Columns without and with Full and Partial CFRP Wraps
Concrete columns are the backbone of any major structure, and their strengthening, repair, and retrofit have always drawn special research attention. One of the techniques for strengthening and improving the ductility of concrete columns has been the application of carbon fiber-reinforced polymer (CFRP) materials. A total of 43 columns of different configurations were experimentally investigated to evaluate the uniaxial compressive behavior of composite columns. Experimental and international code-recommended load-carrying capacities, stress-strain relations, axial stiffness, ductility factor, and failure modes were examined in the study. When fully wrapped, the strength of both plain cement concrete and reinforced cement concrete columns improved by 21% each with reference to the unwrapped columns. In addition to providing the advantages of external confinement to the columns, full wrapping contributed to a strength increment of 21%, which compared well with the steel reinforcement contribution to a strength increment of 28% to 39%. The partial wrapping technique was found to be an economical alternative to the full wrapping technique, with strength enhancements of 6% to 12% in the case of both plain cement concrete and reinforced cement concrete partially wrapped columns. Two regression models for the load-carrying capacity for columns with and without wraps were developed with four key performance parameters: percentage steel reinforcement, percentage concrete, percentage carbon fiber-reinforced polymer wrap, and the weight of the specimen. The formulated models were validated and found to be robust and consistent with the results. 2024 American Society of Civil Engineers. -
Mathematical Modeling of Concrete Fracture Energy of Notched Specimens Using Experimental Evidence
The tensile stiffness of concrete is an important parameter for crack initiation. The microcrack initiation and propagation regulate the stressstrain behavior and the failure mode of concrete. Therefore, fundamental awareness of the fracture mechanism in terms of fracture energy is a requisite to comprehend concrete behavior. There is research consensus that fracture energy alone does not suffice to characterize the ductility/brittleness and also the size dependency of concrete. Therefore, it is necessary to evaluate the fracture energy and the characteristic length for a realistic assessment of the fracture behavior of concrete. Towards this objective, this study examined the fracture energy of concrete by experimentation, and the fracture energy proposed by various models in the literature. Further, the characteristic length proposed by Hillerborg which depicted both the material influence and the size effect, has been computed. Based on the RILEM50 FM recommendations, 18 specimens with varying grades of concrete and notch depths have been tested and the fracture energy parameters have been evaluated. Also, two regression models with key fracture parameters as variables for two-notch ratios, have been formulated for the concrete fracture energy. The arguments have been supported by experimental evidence. The Author(s), under exclusive licence to Shiraz University 2024. -
Multigene Genetic Programming Based Prediction of Concrete Fracture Parameters of Unnotched Specimens
This study explores the fracture energy of notched and unnotched concrete specimens subjected to the classical three-point bend test, instantiating a gradational step in the continued development of concrete fracture mechanics. An experimental campaign involving 18 notched test specimens and nine unnotched specimens of three different grades of concrete, an examination of the existing literature models for unnotched specimens, and a novel Multigene Genetic programming (MGGP) based concrete fracture energy model for unnotched specimens are integral to this study. As a salient result, the multiple approaches to quasi-brittle materials adopted in the study, highlighted the criticality of the determination of fracture energy, tensile strength and characteristic length for the crack width study. The failure modes of notched and unnotched specimens were found to be similar. The reported literature has mainly focused on a limited number of fracture energy influencing parameters. Therefore, six impact parameters have been chosen and incorporated into the present study to provide a more acceptable explanation of concrete fracture behaviour. A sensitivity analysis of the parameters and an error analysis of the model undertaken have established the accuracy and robustness of the developed MGGP model. 2023 by the authors. Licensee C.E.J, Tehran, Iran. -
Machine Learning Classifiers for Credit Risk Analysis
The modern world is a place of global commerce. Since globalization became popular, entrepreneurs of small and medium enterprises to large ones have looked up to banks, which have existed in various forms since antiquity, as their pillars of support. The risk of granting loans in various forms has significantly increased as a consequence of this, the businesses face financing difficulties. Credit Risk Analysis is a major aspect of approving the loan application that is done by analyzing different types of data. The goal is to minimize the risk of approving the loan for the Individuals or businesses who might not pay back on time. This research paper addresses this challenge by applying various machine learning classifiers to the German credit risk dataset. By evaluating and comparing the accuracy of these models to identify the most effective classifier for credit risk analysis. Furthermore, it proposes a contributory approach that combines the strengths of multiple classifiers to enhance the decision-making process for loan approvals. By leveraging ensemble learning techniques, such as the Voting Ensemble model, the aim is to improve the accuracy and reliability of credit risk analysis. Additionally, it explores tailored feature engineering techniques that focus on selecting and engineering informative features specific to credit risk analysis. 2024 Sudiksha et al., licensed to EAI. -
Encountering risk with resilience for experiences: a case study on tourism in a conflicted tourist destination
Purpose: This paper aims to unravel how tourists balance their novel experiences with risk perceptions, psychological resilience and behavioral intentions. Additionally, it explores how tourists' personalities moderate the relationship between experiences and travel intentions. Design/methodology/approach: A total of 234 self-administered questionnaires were distributed to a diverse group of tourists who recently explored the Srinagar region to capture their perspectives. The data obtained was analyzed using Smart PLS-SEM. Findings: This study revealed that the impact of perceived terror risk on behavioral intentions is not statistically significant. Instead, tourists' experiences significantly influence psychological resilience and behavioral intentions. Tourists with higher resilience are inclined to perceive these experiences as aiding in managing negative feelings. Research limitations/implications: The study's focus is confined to one conflict zone within the country due to research constraints, excluding other areas. Practical implications: This research provides practical insights for destination management authorities and highlights areas for improvement for tourism service providers and the government in the Srinagar region, as well as other conflict regions. Emphasizing mutual respect between locals and tourists can foster community-based tourism, enhancing the region's appeal and promoting positive intentions for all involved parties. Social implications: This study examines how local communities in conflict-affected areas adjust to and manage the presence of tourists, with an emphasis on building resilience and support systems. Additionally, it explores how travel decisions and behaviors are influenced by tourists' perceptions of safety and how these perceptions can influence broader societal attitudes toward areas affected by conflict. Evaluating the local population's economic reliance on tourism may result in changed social dynamics, as well as possible exploitation or over-reliance on industry. Promoting mutual understanding and cultural interchange between locals and visitors may have a positive impact on efforts to promote social cohesion and peacebuilding. Originality/value: This study broadens the scope of the existing literature on destination attributes in conflict zones, offering a unique perspective on the intrinsic features of this issue. The solutions proposed in this study contribute a novel dimension to the current literature. 2024, International Tourism Studies Association. -
An overlap-based human gait cycle detection
Identification of a person by his/her style of walking is referred as gait recognition. Gait is one among the biometric used for human identification. In gait recognition, an inevitable step for accurate feature extraction is gait cycle detection. In this paper, a novel gait cycle detection algorithm based on the concept of overlap between legs during locomotion is proposed. To identify overlap, zero-crossing counts of silhouette frames as well as bottom halves of silhouette frames are considered. The efficiency of this algorithm is tested using normal walking sequence of subjects with 90 viewing angle from CASIA B as well as TUM-IITKGP human gait databases. The results obtained shows that gait cycle can be easily and efficiently detected with zero-crossing count of silhouette frames. Further zero-crossing counts taken from bottom halves of silhouette frames gives better performance. Copyright 2019 Inderscience Enterprises Ltd. -
Blockchain-Based Service Oriented Privacy-Preserving Data Sharing over Distributed Data Streams in Asynchronous Environment
Innovative city applications use information and communication technologies to function various operations efficiently. The widespread use of the Internet of Things (IoT) can be viewed in several applications like smart cars, smart cities, e-commerce, and cyber-physical systems. The huge amount of data produced and transmitted by these systems is handled by cloud-based storage services, which are vulnerable to multiple threats risking the privacy and security features of the application. Cloud storage services employ encryption algorithms to ensure data confidentiality, but it fails to address the privacy issues. Apart from the privacy risks, in these systems, the identity of a user who shares and accesses the data is traceable, as it is required to verify user eligibility before providing access. Also, a vast amount of daily data is stored on a centralized system that processes service requests from multiple users, posing considerable risks to the system's stability during peak periods. To address these challenges faced during the data sharing process in a centralized system, Service Oriented Privacy-Preserving Data Sharing (SOPPDS) platform based on a blockchain framework is proposed. The modified Key Policy-Attribute-based Encryption (MKP-ABE) technique is applied to securely share the data between the service owners and the service consumers. It was evident from the performance evaluation of the proposed SOPPDS platform that the encryption process takes lesser time than the decryption process. Also, the cryptographic operations performed on the prime order sets exhibited increased latency and computational cost. It was observed that comparatively, cryptographic operations performed on composite order sets could overcome the issues in prime order sets. SOPPDS platform works well in preserving the users' privacy, ensuring anonymity in the data sharing process, and maintaining the confidentiality of the data shared in the system. 2023, Ismail Saritas. All rights reserved. -
Integration of 0.1 GHz to 40 GHz RF and microwave anechoic chamber and the intricacies
The aim of this paper is to highlight and elaborate the construction and establishment of a rectangular anechoic chamber (AC) of dimensions 7 m 4 m 3 m working from 0.1 GHz to 40 GHz. It is an informative checklist giving an insight on the reckoning of chamber dimensions and selection of appropriate absorbers as per the required specifications. It briefs the key features of validation of an anechoic chamber, namely, shielding effectiveness and reflectivity (quiet zone). It describes the intricacies of the integration of systems such as vector network analyzer (VNA), antenna mounting stands, three-axes motorized antenna rotation control circuitry, and customized software. The validation of the established chamber is accomplished for overall shielding effectiveness of ?80 dB and reflectivity of ?40 dB in one cubic meter area at the receiving antenna or the antenna under test (AUT) region far away from transmitter say, at 5.5 m separation. This paper covers the measurement results of three broadband horn antennas which can be used as reference antennas for characterization of other antennas in the chosen frequency range. The entire report will certainly be a guideline for any reader or aspirant who is interested in the development of a similar anechoic chamber and looking for complete intricacies. 2020, Electromagnetics Academy. All rights reserved. -
Experimental Verification of Gain and Bandwidth Enhancement of Fractal Contoured Metamaterial Inspired Antenna
The performance of any antenna cannot be completely assessed purely on the basis of simulation results. All simulations are made by assuming an ideal environment where the fabrication tolerances and practical losses are not accounted for. Therefore, evidencing the performance experimentally becomes a crucial step. In this work, the experimental validation of a fractal contoured square microstrip antenna with four ring metamaterial structure, hereon referred to as optimized metamaterial inspired square fractal antenna has been presented. It is an extension to previously designed antenna and aims to experimentally verify the enhanced gain and bandwidth of this antenna. The design and simulation of the proposed antenna was accomplished by using Ansys HFSS v18.2. The end-to-end antenna spread area is 23 mm x 23 mm on a 46 mm x 28 mm x 1.6 mm FR4 substrate with ?r of 4.4. The simulated design was fabricated using Nvis 72 Prototyping Machine and measured in an anechoic chamber facility using vector network analyzer. The antenna resonates with the deepest S11 of-39.5 dB in a broad bandwidth of 2.53 GHz from 2.265 GHz to 4.79 GHz with experimental verification. The proposed antenna provides an enhanced gain of 8.81 dB at the most popularly used frequency of 2.5 GHz. The simulation and experimental results of resonance, gain and radiation pattern are found to agree maximally. The fractional bandwidth offered by this proposed antenna is 72.28%. The experimental validation confirms enhanced gain-bandwidth performance in a wide resonance band. Hence, this antenna is well recommended for wireless, energy harvesting rectenna and sub-6 GHz (2.5 GHz to 4.20 GHz) 5G applications. 2022, Advanced Electromagnetics. All rights reserved. -
Enablers and Outcomes of Supply Chain Collaboration for Sustainable Growth
This study explores the intricate dynamics, challenges, and potential benefits of supply chain collaboration, emphasizing its pivotal role in achieving sustainability goals. Modern Supply Chain Collaboration (SCC) projects focus on sustainability-related activities, fostering interdependence between partners and driving sustained competitive advantage. The study introduces a comprehensive framework encompassing specific enablers (e.g., Joint Decision Making, Technology Integration) and outcomes (e.g., Social, Economic, and Environmental Sustainability) of supply chain collaboration. It contributes to practical guidelines for businesses seeking to enhance collaboration strategies and delves into theoretical paradigms such as the Cooperative Advantage concept, Triple Bottom Line Theory, Resource-Based View Theory, and Network Theory. The Triple Bottom Line Theory serves as an integrated theory of sustainability, emphasizing economic advantages, environmental impact minimization, and societal benefits. The Resource-Based View Theory underscores the role of internal resources in gaining competitive advantages, aligning with sustainability goals. Network Theory explores collaborative dynamics among competing entities, emphasizing resource sharing. The study's findings offer practical implications, enabling companies to assess and improve the sustainability of their supply chain management. It advocates for the integration of supply chain collaboration into organizational missions, emphasizing the importance of trust-building through standardized guidelines. The insights gained from this study are applicable across sectors, aiding legislators in developing flexible regulations and refining collaboration processes. Additionally, the study highlights the potential cultural variations in supply chain collaboration, paving the way for future research. 2024, Iquz Galaxy Publisher. All rights reserved. -
Enhancing the job scheduling procedure to develop an efficient cloud environment using near optimal clustering algorithm
In this internet era, cloud computing and there are various problems in the cloud computing, where the consumers as well as the service providers facing in their day to day cloud activities. Job scheduling problem plays a vital role in the cloud environment. To provide an efficient job scheduling environment, it is necessary to perform efficient resource clustering. In this regard, the proposed system, concentrated on the resource clustering methodology by proposing an efficient resource clustering algorithm named identicalness split up periodic node size (ISPNS) in the cloud environment. The algorithm proposed helps in forming resource clusters with the help of cloud environment. The proposed system is compared with the existing systems to justify the performance of the proposed resource clustering algorithm and it produces near optimal solution for the resource clustering problem which helps to provide an efficient job scheduling in cloud environment. Copyright 2023 Inderscience Enterprises Ltd. -
Millets Industry Dynamics: Leveraging Sales Projection and Customer Segmentation
Millets delves into the dynamics of the millets industry, with a particular focus on sales projection and customer segmentation as strategic levers for growth. The research commences with an in-depth analysis of the millets market, encompassing production patterns, consumption trends, and emerging market opportunities. It explores the diverse range of millets varieties, their nutritional profiles, and the factors driving consumer preference. By understanding the market landscape, the study identifies key trends and challenges shaping the industry. A core component of this research is the development of a robust sales projection model. Employing advanced statistical and data-driven techniques, the model forecasts future sales based on historical data, market trends, and relevant economic indicators. The model incorporates factors such as consumer demographics, purchasing behavior, and competitive landscape to provide accurate and actionable insights. Customer segmentation is another critical aspect of the study. By applying clustering and profiling methodologies, the research identifies distinct customer segments based on factors such as age, income, dietary preferences, and purchasing habits. This segmentation enables a deeper understanding of customer needs and preferences, facilitating targeted marketing strategies and product development. The integration of sales projection and customer segmentation empowers businesses to make informed decisions, optimize resource allocation, and enhance overall market performance. By aligning product offerings and marketing efforts with customer segments, companies can achieve higher customer satisfaction, increased market share, and improved profitability. This research contributes to the growing body of knowledge on the millets industry by providing valuable insights into market dynamics, sales forecasting, and customer segmentation. The findings offer practical guidance for industry stakeholders, including farmers, processors, retailers, and policymakers, in navigating the evolving millets landscape. By leveraging the potential of sales projection and customer segmentation, the millets industry can unlock new opportunities and achieve sustainable growth. The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024. -
Implementation of OpenId connect and O Auth 2.0 to create SSO for educational institutes
Increase in the number of users is directly proportional to the need of verifying them. This means that any user using any website or application has to be authenticated first; this leads to the creation of multiple credentials of one user. Now if these different websites or applications are connected or belong to one single organization like a college or school, a lot of redundancy of data is there. Alo ng with this, each user has to remember a wide range of credentials for different applications/websites. So in this paper, we addre ss the issue of redundancy and user related problems by introducing SSO using OpenId Connect in educational institutes. We aim to mark the di fference between the traditional system and proposed login by testing it on a group of users. 2018 Authors. -
Smart city initiatives and disaster resilience of cities through spatial planning in Pune city, India
Cities are attracting populations at alarming rate. Cities provide the need of populations in every way from livelihoods to livability. In doing so it is exhausting its resources resulting in increasing threats of risk. An initiative like Smart City Mission is aiming to enhance the capacities of the cities to increase livability and quality of life for its population and decrease threats of risk. This study examines the impact of smart city initiatives on resilience to earthquakes and floods through a spatial planning perspective for the city of Pune in State of Maharashtra through series of structured interviews with key stakeholders. The findings suggest that smart city initiative is still in its primary stage and requires assimilation with the development strategy to contribute to the resilience of the city. The study further proposes the need to integrate the smart city initiative with all the current and future developmental projects. 2023, World Research Association. All rights reserved.
