Template-Type: ReDIF-Article 1.0
Author-Name: Sridhar Joshi
Author-X-Name-First: Sridhar
Author-X-Name-Last: Joshi
Author-Name: S. Silvia Priscila
Author-X-Name-First: S. Silvia
Author-X-Name-Last: Priscila
Author-Name: S. Suman Rajest
Author-X-Name-First: S. Suman
Author-X-Name-Last: Rajest
Author-Name: Kriti Srivastava
Author-X-Name-First: Kriti
Author-X-Name-Last: Srivastava
Author-Name: S. Prasath Alias Surendhar
Author-X-Name-First: S. Prasath Alias
Author-X-Name-Last: Surendhar
Author-Name: Rajkumar Rajasekaran
Author-X-Name-First: Rajkumar
Author-X-Name-Last: Rajasekaran
Title: Nonlinear control-based class-D amplifier for audio intelligent infrastructure applications
Abstract:
A nonlinear control-based class-D amplifier using a DC power source for medium-power audio applications is proposed in this paper. The amplifier utilises switches in a half-bridge configuration to realise the class-D power stage. A passive second-order bandpass filter is cascaded with the power stage to render a highly linear audio amplifier for high-quality audio reproduction. A nonlinear technique-based controller is used for a closed-loop amplifier system which offers high immunity to power supply noise, robustness, and fault tolerance without using a triangular carrier generator. An 80 W, 20 Hz to 20 kHz amplifier model is developed considering the nonlinearity present in the power electronic switches of the power stage. Simulation results of the proposed amplifier with a full range 4 Ω loudspeaker load are presented. The amplifier's response at different frequencies in the audio spectrum is presented, which confirms the amplifier's linearity and command following property. To confirm the high linearity of the amplifier, the THD versus frequency plot is depicted, which ensures the suitability of the proposed amplifier for high-fidelity audio amplification.
Journal: Int. J. of Critical Infrastructures
Pages: 309-328
Issue: 4
Volume: 20
Year: 2024
Keywords: nonlinear control; class-D; amplifier; audio applications; intelligent infrastructures; power supply noise; robustness; half-bridge audio amplifier; HBAA; PWM wave; variable structure system; VSS.
File-URL: http://www.inderscience.com/link.php?id=140554
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:4:p:309-328

Template-Type: ReDIF-Article 1.0
Author-Name: Sarita Mishra
Author-X-Name-First: Sarita
Author-X-Name-Last: Mishra
Author-Name: Suresh Kumar Sahoo
Author-X-Name-First: Suresh Kumar
Author-X-Name-Last: Sahoo
Author-Name: P. Srinivas Subbarao
Author-X-Name-First: P. Srinivas
Author-X-Name-Last: Subbarao
Title: Adoption of cloud accounting for critical infrastructure within small medium enterprises in Odisha through prioritisation of its sustainable benefits
Abstract:
This study has attempted to use relative to an identified distribution (RIDIT) algorithm-based modelling for analysing real time empirical data related to benefits realised by an enterprise through adoption of critical infrastructure of cloud accounting in context of small medium enterprises of Odisha. The study focuses on demand side aspect of cloud accounting aspects by considering its realised benefits in context of SMEs in Odisha. Reduction of cost, reduction of wastage and gaining more sustainability, security of financial information comes on the top positions in the priority list of benefits. The finding of the study is significant with respect to its practical orientation as the responses collected from real user of the system. Modelling of realised benefits of cloud accounting by enterprises with RIDIT analysis could contribute towards demand creation of cloud accounting; its adoption and improvement of services to the clients. The finding of the study could be informative to such enterprises for taking proper decision towards adoption of cloud accounting in critical infrastructure.
Journal: Int. J. of Critical Infrastructures
Pages: 329-340
Issue: 4
Volume: 20
Year: 2024
Keywords: cloud accounting; sustainable benefits; critical infrastructure; prioritisation; RIDIT analysis.
File-URL: http://www.inderscience.com/link.php?id=140555
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:4:p:329-340

Template-Type: ReDIF-Article 1.0
Author-Name: K.N. Asha
Author-X-Name-First: K.N.
Author-X-Name-Last: Asha
Author-Name: R. Rajkumar
Author-X-Name-First: R.
Author-X-Name-Last: Rajkumar
Title: Cross domain and adversarial learning based deep learning approach for web recommendation
Abstract:
The web has become a massive source of knowledge in the internet age. This extra information makes it hard to choose items based on individual needs. Today, choosing suitable products takes time and effort. Daily uploads and downloads from YouTube, Instagram, Facebook, and others generate massive volumes of data. Keep up with the internet's wealth of information. Recommender systems can help users find useful data in vast datasets. User-interested recommender systems provide personalised and non-personalised recommendations. Real-time applications need recommender systems, but conventional methods have problems. In this work, we identified the issues and developed a cross-domain web recommendation system using a deep learning-based scheme. A joint reconstruction loss model reduces learning error with an autoencoder and adversarial learning technique. An open-source cross-domain dataset tests the proposed approach. For the Movie dataset, average HR, NDCG, and MRR are 0.8951, 0.5911, and 0.6121. The book dataset averages 0.8358, 0.6824, and 0.5575.
Journal: Int. J. of Critical Infrastructures
Pages: 341-355
Issue: 4
Volume: 20
Year: 2024
Keywords: cross domain; adversarial learning; deep learning; web recommendation; cross-domain recommender system; demographic information; internet age.
File-URL: http://www.inderscience.com/link.php?id=140556
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:4:p:341-355

Template-Type: ReDIF-Article 1.0
Author-Name: Jaspal Singh
Author-X-Name-First: Jaspal
Author-X-Name-Last: Singh
Author-Name: R.K. Tomar
Author-X-Name-First: R.K.
Author-X-Name-Last: Tomar
Author-Name: N.D. Kaushika
Author-X-Name-First: N.D.
Author-X-Name-Last: Kaushika
Author-Name: Gopal Nandan
Author-X-Name-First: Gopal
Author-X-Name-Last: Nandan
Title: Thermal performance analysis of PCM incorporated roof slab infrastructures using deep learning algorithms
Abstract:
PCM technology uses thermal energy storage (TES) to lessen the effects of changes in the outside temperature. PCM thermal energy storage may reduce ambient temperature changes (TES). Latent heat storage (LHS) reduces HVAC needs and enhances indoor comfort in conventional buildings. In buildings without HVAC, latent heat storage (LHS) enhances indoor thermal comfort by reducing the demand for HVAC. This study examines and measures the advantages of using PCM for building envelopes. In order to generalize the findings, a 1 m * 1 m * 1 m reference model is employed with four Indian towns located in various climate zones. Decision tree monitors temperature over time. Root mean square transforms actual and anticipated values, while mRMR selects features. Thermal testing equipment, a PCM wallboard heat storage experiment, and investigations on 5 mm, 10 mm, and 20 mm PCM plasterboard with a 220 C melting temperature are constructed to validate the results. PCM thickness reduced energy use logarithmically in all climatic zones, with temperate office buildings benefiting most.
Journal: Int. J. of Critical Infrastructures
Pages: 372-389
Issue: 4
Volume: 20
Year: 2024
Keywords: phase change material; adaptive envelopes; PCM thickness and energy thermal energy storage; infrastructures energy efficiency; passive strategies.
File-URL: http://www.inderscience.com/link.php?id=140557
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:4:p:372-389

Template-Type: ReDIF-Article 1.0
Author-Name: Vivek Basavegowda Ramu
Author-X-Name-First: Vivek Basavegowda
Author-X-Name-Last: Ramu
Author-Name: Ajay Reddy Yeruva
Author-X-Name-First: Ajay Reddy
Author-X-Name-Last: Yeruva
Title: Unsupervised strategies in detecting log anomalies using AIOps monitoring to amplify performance by PCA and ANN systems
Abstract:
A fundamental task that artificial intelligent operations (AIOps) perform is to mitigate the risk of abnormal system behaviours, identify and demystify the alerts when encountering the presence of log anomalies, and assess the reasons for the different system failures and run smoothly. System flaws must be fixed and to empower this functionality, the infusion of related artificial intelligence needs to be integrated. There have been several innovative strategies that have been incorporated with systems utilising AIOps platforms. However, the study has been limited, and some grey areas remain. Suppressing incorrect logs in system performance analysis is unsupervised in this paper. PCA and ANN produce a feed input for detailed analysis. System performance improves. 'Pseudo positives' - false alerts in log anomaly detection theories - are introduced in the study. The proposed strategy reduces aberrant logs by 72%, outperforming most other experiments. It is unique in log analysis since it reduces false positives, making it easier to find true anomalies and improving system efficiency. This approach has promising research possibilities.
Journal: Int. J. of Critical Infrastructures
Pages: 356-371
Issue: 4
Volume: 20
Year: 2024
Keywords: artificial intelligent operations; AIOps; anomaly log detection; log data analysis; performance; pseudo positives; recurring anomalies; monitoring; observability.
File-URL: http://www.inderscience.com/link.php?id=140558
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:4:p:356-371

Template-Type: ReDIF-Article 1.0
Author-Name: Manikant Panthi
Author-X-Name-First: Manikant
Author-X-Name-Last: Panthi
Author-Name: Tanmoy Kanti Das
Author-X-Name-First: Tanmoy Kanti
Author-X-Name-Last: Das
Title: Stacking-based multi-objective approach for detection of smart power grid attacks using evolutionary ensemble learning
Abstract:
Smart power grid (SPG) has gained a reputation as the advanced paradigm of the power grid. It provides a medium for exchanging real-time data between the company and users through the advanced metering infrastructure delivering transparent and resilient service to electricity consumers. The widespread deployment of remotely accessible networked equipment for grid monitoring and control has vastly increased the surface of SPG for attackers to locate vulnerable points. The early and accurate identification of the above counteracts is paramount to ensure stable and efficient power distribution. This paper proposes a stacking-based multi-objective evolutionary ensemble scheme to identify various attacks in the SPG. The proposed method used a non-dominated sorting genetic algorithm to learn the non-linear, overlapping, and complex electrical grid features to predict the type of malicious attacks. The experimental results and comparison using multiclass dataset validate the presented 'Stacking-NSGA-II' approach notably outperformed the others benchmark classifiers.
Journal: Int. J. of Critical Infrastructures
Pages: 195-215
Issue: 3
Volume: 20
Year: 2024
Keywords: non-dominated sorting genetic algorithm; cyber-attack; power grid; machine learning.
File-URL: http://www.inderscience.com/link.php?id=138783
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:3:p:195-215

Template-Type: ReDIF-Article 1.0
Author-Name: Jonathan Atrey
Author-X-Name-First: Jonathan
Author-X-Name-Last: Atrey
Author-Name: Rajeshkannan Regunathan
Author-X-Name-First: Rajeshkannan
Author-X-Name-Last: Regunathan
Author-Name: Rajkumar Rajasekaran
Author-X-Name-First: Rajkumar
Author-X-Name-Last: Rajasekaran
Title: Real-world application of face mask detection system using YOLOv6
Abstract:
The COVID-19 pandemic has drastically reshaped the human lifestyle and has placed immense importance on our health, safety, and sanitation practices. Among the various safety protocols assigned by the World Health Organisation (WHO) for the same, the usage of face masks to prevent the spread of the virus from an infected person to a healthy person has been of prime significance. To enable efficient execution of the WHO protocol, this case study proposes creating a real-time detection model built explicitly for capturing an audience to alert people who are not following COVID prevention protocols. The proposed case study utilises the state-of-the-art (SOTA) YOLOv6 algorithm along with different iterations of the YOLO algorithm, such as YOLOv4, and YOLOv5, for representing the variation in training performance among various iterations of YOLO. Further, it discusses and analyses the effectiveness of using a real-time detector for face mask detection. This study aims to decrease the risk of a healthy person being affected by the COVID-19 virus by keeping a check on a designated crowd and contributes towards the prevention of the further spread of the virus by crowd monitoring and control methods. The real-time implementation of the proposed case study reports a positive impact, with a 36% increment in people following the standard COVID-19 protocol of wearing masks in public places.
Journal: Int. J. of Critical Infrastructures
Pages: 216-240
Issue: 3
Volume: 20
Year: 2024
Keywords: YOLOv6; DarkNetCSP; CNN; COVID-19; case study; computer vision; ecological studies; healthcare-related research; real-time monitoring system.
File-URL: http://www.inderscience.com/link.php?id=138785
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:3:p:216-240

Template-Type: ReDIF-Article 1.0
Author-Name: Sunil Gupta
Author-X-Name-First: Sunil
Author-X-Name-Last: Gupta
Author-Name: Goldie Gabrani
Author-X-Name-First: Goldie
Author-X-Name-Last: Gabrani
Title: IoT cloud-based telecare medical healthcare system with lightweight authentication scheme
Abstract:
TMIS has huge potential for enhancing health care delivery, it also creates certain issues with regards to accessibility, privacy, security and confidentiality of sensitive patient information. Son et al. 's (2020) proposal for a secure authentication mechanism for cloud-based TMIS differs from Amin and Biswas' (2015a) proposal for a TMIS architecture based on numerous physical servers. For gaining access to the medical servers, they have devised an authentication system. They have argued that their scheme removes all the shortcomings of earlier schemes. We, in this paper, will show that their architecture based on dedicated multiple physical servers has certain limitations. Such systems are usually either under-provisioned or over-provisioned and are quite expensive. In addition, Amin and Biswas (2015a) Mutual authentication and user anonymity are not provided by the scheme, and therefore is vulnerable to malicious assaults. In order to get over these restrictions, we suggest a unique design for the TMIS based on cloud based on OTP. We show that the performance of our suggested system is enhanced while simultaneously overcoming the drawbacks of Amin and Biswas (2015a) approach.
Journal: Int. J. of Critical Infrastructures
Pages: 261-287
Issue: 3
Volume: 20
Year: 2024
Keywords: smart card; IoT-cloud computing; mutual authentication; telecare medical information systems; TMIS; one-time password; OTP; anonymity; AVISPA.
File-URL: http://www.inderscience.com/link.php?id=138789
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:3:p:261-287

Template-Type: ReDIF-Article 1.0
Author-Name: Haitao Wang
Author-X-Name-First: Haitao
Author-X-Name-Last: Wang
Author-Name: Mingyang Xu
Author-X-Name-First: Mingyang
Author-X-Name-Last: Xu
Author-Name: Tao Guo
Author-X-Name-First: Tao
Author-X-Name-Last: Guo
Author-Name: Minghua Cui
Author-X-Name-First: Minghua
Author-X-Name-Last: Cui
Author-Name: Jiangtao Tian
Author-X-Name-First: Jiangtao
Author-X-Name-Last: Tian
Title: Study on the influence of deep foundation pit excavation on the deformation of adjacent viaduct pile foundation
Abstract:
In order to study the influence of deep foundation pit excavation on the deformation of adjacent viaduct pile foundation in water-rich karst environment, a three-dimensional finite element analysis model was established, and the dewatering process of deep foundation pit was simulated. The results show that with the increasing of pile depth, the horizontal displacement of pile foundation is larger at the top and smaller at the bottom. The dewatering of deep foundation pit has influence on the bending moment and axial force of adjacent viaduct pile foundation, but they are in a relatively safe range. The horizontal displacement of bridge pile is negatively correlated with the distance between bridge pile and deep foundation pit, the supporting stiffness of deep foundation pit and the elastic modulus of the first layer soil.
Journal: Int. J. of Critical Infrastructures
Pages: 288-307
Issue: 3
Volume: 20
Year: 2024
Keywords: deep foundation pit; pile foundation; bridge pier; numerical calculation; influence parameters; Karst cave.
File-URL: http://www.inderscience.com/link.php?id=138790
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:3:p:288-307

Template-Type: ReDIF-Article 1.0
Author-Name: Avin Shekhar Chourasia
Author-X-Name-First: Avin Shekhar
Author-X-Name-Last: Chourasia
Author-Name: Narendra N. Dalei
Author-X-Name-First: Narendra N.
Author-X-Name-Last: Dalei
Author-Name: Karunakar Jha
Author-X-Name-First: Karunakar
Author-X-Name-Last: Jha
Title: Assessment of critical success factors for PPP airports using the AHP
Abstract:
Critical success factors (CSFs) for various infrastructure projects have been the subject of numerous research, but there are relatively few studies available for airports, and none have been done as yet to identify the CSFs for the development of PPP airports in India. To bridge this gap, this study was carried out using the analytical hierarchy process (AHP) to identify the critical factors for the development of PPP airports in India. The success of the PPP airport was estimated using ordinary least square (OLS) and tobit models. The result shows that effective project management, procurement process, profit expectations, and information disclosure have statistically, and significantly positive impacts on the success of PPP airport as perceived by professionals in India. The study recommends that the government and all other PPP airport stakeholders must properly take into account the identified CSFs for the development of PPP airports in India to be successful.
Journal: Int. J. of Critical Infrastructures
Pages: 241-260
Issue: 3
Volume: 20
Year: 2024
Keywords: critical success factors; CSFs ranking; public-private partnership; PPP; analytical hierarchy process; AHP; airport development; PPP airport.
File-URL: http://www.inderscience.com/link.php?id=138831
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:3:p:241-260

Template-Type: ReDIF-Article 1.0
Author-Name: Mostafa Pouyakian
Author-X-Name-First: Mostafa
Author-X-Name-Last: Pouyakian
Author-Name: Ali Akbar Shafikhani
Author-X-Name-First: Ali Akbar
Author-X-Name-Last: Shafikhani
Author-Name: Amir Abbas Najafi
Author-X-Name-First: Amir Abbas
Author-X-Name-Last: Najafi
Author-Name: Behrouz Afshar-Najafi
Author-X-Name-First: Behrouz
Author-X-Name-Last: Afshar-Najafi
Author-Name: Amir Kavousi
Author-X-Name-First: Amir
Author-X-Name-Last: Kavousi
Title: Utilising the fuzzy analytic network process technique to prioritise safety challenges in construction projects
Abstract:
This study aims to identify and rank the obstacles to implementing a safety program in the Iranian construction industry. The obstacles were identified through literature review and interviews with experts in the Iranian construction industry. Because of the complex structure of the relationships between the obstacles and their mutual effects, the fuzzy analysis network Process method was used to model them. Obstacles to safety implementation were identified and ranked using the proposed model. Fourteen obstacles were identified in the three organisational, contractors, and systems dimensions. The most critical obstacles include tight project schedules, resource constraints, fierce competition between contractors to reduce time and cost. This study showed that the Iranian construction industry, despite its advantages, faces obstacles in the successful implementation of safety programs. It seems that the identified obstacles can be removed by modelling the safety program in project scheduling. However, more studies are needed in this area.
Journal: Int. J. of Critical Infrastructures
Pages: 16-32
Issue: 1
Volume: 20
Year: 2024
Keywords: safety; accidents; construction; analytic network process; ANP; fuzzy evaluation.
File-URL: http://www.inderscience.com/link.php?id=136285
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:1:p:16-32

Template-Type: ReDIF-Article 1.0
Author-Name: Fery Safaria
Author-X-Name-First: Fery
Author-X-Name-Last: Safaria
Author-Name:  Najid
Author-X-Name-First: 
Author-X-Name-Last: Najid
Author-Name: Carunia Mulya Firdausy
Author-X-Name-First: Carunia Mulya
Author-X-Name-Last: Firdausy
Title: Land value capture as breakthrough of financing scheme in urban railway development in Indonesia
Abstract:
This study aims at examining whether or not the LVC can be used as an alternative financing instrument in urban railway infrastructure in Indonesia. The results confirmed that the LVC can be a breakthrough scheme in financing the development of urban railway infrastructure in Indonesia. The most urgent aspect to be prepared by the government to implement the LVC scheme in financing the urban railway infrastructure is the availability of regulations. Also, the approach to developing and executing the plan of LVC needs to be based on an assessment of the cost of the benefit analysis, the land value, the market condition of the location, sustainability, and people's participation in urban railway development. Further detailed research to examine the full potential and the benefits of applying the LVC in financing urban railway infrastructure development is needed as Indonesia faces budget constraints and as we move into a post-pandemic recovery.
Journal: Int. J. of Critical Infrastructures
Pages: 56-71
Issue: 1
Volume: 20
Year: 2024
Keywords: land value capture; LVC; financial scheme; budget limit; urban railway infrastructures; Indonesia.
File-URL: http://www.inderscience.com/link.php?id=136287
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:1:p:56-71

Template-Type: ReDIF-Article 1.0
Author-Name: Fabrizio Zuena
Author-X-Name-First: Fabrizio
Author-X-Name-Last: Zuena
Author-Name: Marco Dell'Isola
Author-X-Name-First: Marco
Author-X-Name-Last: Dell'Isola
Author-Name: Giorgio Ficco
Author-X-Name-First: Giorgio
Author-X-Name-Last: Ficco
Author-Name: Luisa Lavalle
Author-X-Name-First: Luisa
Author-X-Name-Last: Lavalle
Author-Name: Alberto Tofani
Author-X-Name-First: Alberto
Author-X-Name-Last: Tofani
Title: Social and economic risk analysis of natural gas distribution networks
Abstract:
The continuity of service as well as with its safety and security represent a crucial issue for natural gas transmission and distribution networks and a detailed analysis of the associated risks is essential to increase their reliability. In particular, natural gas distribution networks are characterised by a high number of users and present a very complex structure (with nodes and stretches and presenting mixed typologies, e.g., point to point, star, meshed) which make often difficult to forecast the effects of localised failure events, especially by a social and economic point of view. In this work, the authors develop a methodology for the analysis of the economic and social risk associated with natural gas distribution network failures and for the quantification of the related consequences on residential, commercial and/or industrial users. To this aim, the authors present and discuss the case study represented by a city distribution network located in southern Italy. The results demonstrate the developed method is effective in identifying the structural criticalities of the network, allowing the quick detection of the most critical areas affected by significant risk of service disruption.
Journal: Int. J. of Critical Infrastructures
Pages: 72-96
Issue: 1
Volume: 20
Year: 2024
Keywords: failure analysis; risk analysis; distribution network; natural gas.
File-URL: http://www.inderscience.com/link.php?id=136288
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:1:p:72-96

Template-Type: ReDIF-Article 1.0
Author-Name: Binod Kumar Singh
Author-X-Name-First: Binod Kumar
Author-X-Name-Last: Singh
Author-Name: Tamajeet Chatterjee
Author-X-Name-First: Tamajeet
Author-X-Name-Last: Chatterjee
Author-Name: Nistha Srivastava
Author-X-Name-First: Nistha
Author-X-Name-Last: Srivastava
Author-Name: Mahesh Amarjit Shanmugam Vaiyapuri
Author-X-Name-First: Mahesh Amarjit Shanmugam
Author-X-Name-Last: Vaiyapuri
Title: Critical success factors of composite LPG cylinders in India
Abstract:
Metal cylinders are being phased out in favour of composite LPG cylinders. These cylinders are light, have a pleasing colour and shape, are rust and corrosion resistant, UV resistant, and also 100% explosion proof. The aim of this study is to understand consumer's awareness level and likeliness to shift to composite LPG cylinders. The paper studies the relative strength and weaknesses of composite LPG cylinders in comparison with traditional metal cylinders. This paper provides the opportunity to identify the consumer's needs and to bridge by suggesting technological applications, thus giving an idea to streamline the value chain of LPG cylinder distribution. This study also provides a holistic study of both B2B and B2C segments in the LPG cylinder value chain and thus provides a scope of improving the existing system. The paper will help the business leaders in composite LPG cylinder manufacturing along with cost saving opportunities to the distributors in the long run.
Journal: Int. J. of Critical Infrastructures
Pages: 1-15
Issue: 1
Volume: 20
Year: 2024
Keywords: type IV composite cylinders; metal LPG cylinder; composite LPG cylinder; composite cylinder pricing; market feasibility; LPG cylinder safety; India.
File-URL: http://www.inderscience.com/link.php?id=136290
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:1:p:1-15

Template-Type: ReDIF-Article 1.0
Author-Name: Yanyan Fan
Author-X-Name-First: Yanyan
Author-X-Name-Last: Fan
Author-Name: Haiyan Zhang
Author-X-Name-First: Haiyan
Author-X-Name-Last: Zhang
Author-Name: Ziqi Li
Author-X-Name-First: Ziqi
Author-X-Name-Last: Li
Title: Seismic economic loss assessment of highway girder bridges using Wenchuan earthquake as a sample
Abstract:
To study the seismic economic loss of highway girder bridges, taking 596 highway girder bridges in the Wenchuan earthquake as examples, the seismic damage phenomenon of highway girder bridges was statistically analysed, the vulnerability of highway girder bridges was studied and analysed, and the vulnerability matrix and vulnerability curve of highway girder bridges were obtained. Two seismic economic loss calculation models for highway girder bridges are proposed - the probability-based seismic economic loss assessment model and the loss rate-based seismic economic loss assessment model. Then, the seismic loss of highway girder bridges is predicted. The seismic loss prediction results cannot only provide a reference range for the bridge seismic design level, but the evaluation results can also be used as a reference for the seismic capacity of highway girder bridges and as the basis for measures for earthquake prevention and disaster reduction.
Journal: Int. J. of Critical Infrastructures
Pages: 33-55
Issue: 1
Volume: 20
Year: 2024
Keywords: historical earthquake damage data; highway girder bridge; seismic vulnerability matrix; seismic vulnerability curve; seismic economic loss assessment.
File-URL: http://www.inderscience.com/link.php?id=136292
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:1:p:33-55

Template-Type: ReDIF-Article 1.0
Author-Name: Doddi Srilatha
Author-X-Name-First: Doddi
Author-X-Name-Last: Srilatha
Author-Name: N. Thillaiarasu
Author-X-Name-First: N.
Author-X-Name-Last: Thillaiarasu
Title: LSTM-CNN: a deep learning model for network intrusion detection in cloud infrastructures
Abstract:
In cloud computing, resources are shared and accessed over the internet to perform intended computations remotely to minimise infrastructure costs. The usage and dependency on the cloud network have increased, and the chances of invasion and loss of data and challenges to develop a reliable intrusion detection and prevention system (IDPS). The existing machine learning-based approaches require the manual extraction of features, which produces low accuracy and high computational time. Providing a secure network involves a framework based on multi-fold validation and privacy in information transmission. The deep learning-based network IDPS model has been proposed to handle the large volume of network traffic in the cloud. This paper proposes a tailored long short-term memory and convolution neural network (LSTM-CNN)-based approach to design a new IDS. The proposed model productively examines intrusions and generates alerts proficiently by incorporating users' information and conducting examinations to detect intrusions. The model's performance is assessed using accuracy, precision, F1-score and recall measures. The proposed model achieves outstanding performance with a test accuracy of 99.27%.
Journal: Int. J. of Critical Infrastructures
Pages: 505-523
Issue: 6
Volume: 20
Year: 2024
Keywords: cloud intelligent infrastructures; convolution neural network; intrusion detection and prevention; long short-term memory; random forest; neural network; security.
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:6:p:505-523

Template-Type: ReDIF-Article 1.0
Author-Name: Weize Liu
Author-X-Name-First: Weize
Author-X-Name-Last: Liu
Author-Name: Zhiyi Huo
Author-X-Name-First: Zhiyi
Author-X-Name-Last: Huo
Author-Name: Xinwen Luo
Author-X-Name-First: Xinwen
Author-X-Name-Last: Luo
Title: Lithium-ion batteries SoC estimation using an ANFIS-based adaptive sliding mode observer for electric vehicle applications infrastructures
Abstract:
State of charge (SoC) estimation is a key function in battery management systems (BMSs) that is not directly measurable and should be estimated using estimation methods. Estimating the SoC requires addressing model uncertainty while determining battery model parameters. Robust battery SoC estimation approaches overcome this challenge. Sliding mode parameter estimation chatters in its original form. To solve this problem, this paper adapts the sliding gain switching estimator by an adaptive fuzzy system to solve the chattering problem. A neural network is used to optimise fuzzy systems, which demand optimisation strategies. The research proposes an adaptive neuro-fuzzy SMO for SoC estimation to improve robustness, accuracy, and response chattering. SoC estimation uses a lithium-ion battery cell equivalent circuit model (ECM). The open circuit voltage's nonlinear relationship with charge makes this model nonlinear. The recommended methodology has been tested using a set of software-in-the-loop experiments, which show that chattering has been abolished and accuracy can be decreased by 5% compared to the standard SMO.
Journal: Int. J. of Critical Infrastructures
Pages: 538-556
Issue: 6
Volume: 20
Year: 2024
Keywords: fuzzy system; battery management systems; BMSs; sliding-mode; state of charge; SoC; lithium-ion battery; applications infrastructures; neural network; equivalent circuit model; ECM.
File-URL: http://www.inderscience.com/link.php?id=142453
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:6:p:538-556

Template-Type: ReDIF-Article 1.0
Author-Name: Zakeya Sanad
Author-X-Name-First: Zakeya
Author-X-Name-Last: Sanad
Author-Name: Abdalmuttaleb M.A. Musleh Al-Sartawi
Author-X-Name-First: Abdalmuttaleb M.A. Musleh
Author-X-Name-Last: Al-Sartawi
Title: The adoption of extensible business reporting language: an empirical investigation of the perceptions of accounting professionals
Abstract:
The current study aims to gain a better understanding of XBRL adoption awareness, benefits, drawbacks and suggests XBRL adoption strategies that could be implemented in the Kingdom of Bahrain. Additionally, the study also investigated the relationship between the perception of issues regarding XBRL adoption and demographic characteristics such as gender, age, and professional experience. A survey research instrument was developed and distributed to accountants and auditors working in listed companies in Bahrain Stock Exchange. The results revealed that, XBRL adoption could help in decreasing information asymmetry, while the lack of XBRL training is one of the biggest concerns. It further appears that the most suitable strategy to disseminate XBRL according to the respondents is a voluntary approach rather than a mandated policy. The empirical analysis conducted in this study shows that age, nationality, experience in XBRL and training, impact the perceptions of accountants. The findings also have various practical and policy implications indicating that regulators, policy makers and firms should work together to sustain and improve the awareness, adoption, and reliability of XBRL.
Journal: Int. J. of Critical Infrastructures
Pages: 557-578
Issue: 6
Volume: 20
Year: 2024
Keywords: extensible business reporting language; XBRL; XBRL adoption; XBRL implementation; accountants; accounting technology; financial reporting; digital transformation; digitalisation.
File-URL: http://www.inderscience.com/link.php?id=142455
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:6:p:557-578

Template-Type: ReDIF-Article 1.0
Author-Name: Naiwrita Dey
Author-X-Name-First: Naiwrita
Author-X-Name-Last: Dey
Author-Name: Ujjwal Mondal
Author-X-Name-First: Ujjwal
Author-X-Name-Last: Mondal
Title: Cubic state observer-based modified repetitive controller for uncertain systems
Abstract:
Work presented in this paper modifies the conventional repetitive controller design with a cubic state observer in a state feedback setting. The new design methodology largely enhances the tracking performance of the controller subjected to a class of LTI systems with parametric uncertainty. Repetitive controller design has been modified with a cubic order polynomial state observer. Performance advantage offered by the proposed controller design compared to the existing method and inclusion of nonlinear term in the error dynamics of the observer modifies the control law. A Lyapunov-Krasovskii functional is chosen and the sufficient robust stability condition for the proposed controller is derived. A numerical example is presented to illustrate the efficacy of the proposed method and upgraded performance is observed compared to existing method. Rapid prototyping of the proposed controller is carried out using a microcontroller board.
Journal: Int. J. of Critical Infrastructures
Pages: 524-537
Issue: 6
Volume: 20
Year: 2024
Keywords: repetitive controller; periodic reference; state observer; cubic; Lyapunov-Krasovskii; uncertainty.
File-URL: http://www.inderscience.com/link.php?id=142459
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:6:p:524-537

Template-Type: ReDIF-Article 1.0
Author-Name: Jaswant Gabra
Author-X-Name-First: Jaswant
Author-X-Name-Last: Gabra
Author-Name: Atul Desai
Author-X-Name-First: Atul
Author-X-Name-Last: Desai
Title: Effect of pylon tower spread on modal time period of cable-stayed suspension hybrid bridge
Abstract:
Cable-stayed bridge concept of longer spans shows a distinct advantage of an effective reduction in deflection of pylon in case of an earthquake when compared to traditional cable-stayed bridges. There is the feasibility of improving the seismic performance of the deck due to seismic action, during strong earthquake vibrations if spread pylons are used. In this paper, the dynamic behaviour of cable stayed suspension hybrid bridge (CSSHB) with pylon tower spread, i.e., lateral and longitudinal with seismic loading is studied. SAP2000 software is used for the modelling of structures. The study contains the response of the bridge designed towards change in the spread of the pylon under consideration of soil structure interaction. Modelling for soil is done using the spring and dashpots, i.e., Kelvin element. It is concluded from the results that the effects spread of pylon legs had a substantial impact on CSSHB.
Journal: Int. J. of Critical Infrastructures
Pages: 491-504
Issue: 6
Volume: 20
Year: 2024
Keywords: cable stayed suspension hybrid bridge; CSSHB; modal time history analysis; spread of pylon; SAP2000 software.
File-URL: http://www.inderscience.com/link.php?id=142460
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:6:p:491-504

Template-Type: ReDIF-Article 1.0
Author-Name: P. Monica
Author-X-Name-First: P.
Author-X-Name-Last: Monica
Author-Name: Kriti Srivastava
Author-X-Name-First: Kriti
Author-X-Name-Last: Srivastava
Author-Name: A. Chitra
Author-X-Name-First: A.
Author-X-Name-Last: Chitra
Author-Name: S. Malathi
Author-X-Name-First: S.
Author-X-Name-Last: Malathi
Author-Name: D. Kerana Hanirex
Author-X-Name-First: D. Kerana
Author-X-Name-Last: Hanirex
Author-Name: S. Silvia Priscila
Author-X-Name-First: S. Silvia
Author-X-Name-Last: Priscila
Title: Intelligent infrastructures using deep learning-based applications for energy optimisation
Abstract:
Renewable energy could boost electricity and wave power. Increased electricity consumption necessitates hydropower integration. Wind energy is cost-effective and promising. This study examines wind farm viability in windy areas. This study summarises deep learning models, methods, and wind and wave energy conditions. Comparing approaches for similar applications. A computation technique can substitute a comprehensive computer model, with a 94% accuracy rate compared to model simulations and 84% compared to other data. The study found great promise in deep learning-based energy optimisation, storage, monitoring, forecasting, and behaviour inquiry and detection. Energy regulators and utility management could evaluate sustainable electricity diversification using the study's findings. This study summarises deep learning models, methods, and wind and wave energy conditions. Comparing equivalent application approaches. A computing technique can replace a complex computer model with 94% accuracy compared to model simulations and 84% to other data. Deep learning applications for energy optimisation, storage, monitoring, forecasting, and behaviour identification and investigation were promising. The project would give energy regulators and utility management impartial advice on sustainable electricity diversification.
Journal: Int. J. of Critical Infrastructures
Pages: 391-415
Issue: 5
Volume: 20
Year: 2024
Keywords: renewable energy; deep learning; wind turbine blade; electricity generation; wind energy; power management; wave energy; extended short-term memory; thermal sensation; indoor climate; machine learning; presence recognition.
File-URL: http://www.inderscience.com/link.php?id=141440
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:5:p:391-415

Template-Type: ReDIF-Article 1.0
Author-Name: P. Sujai
Author-X-Name-First: P.
Author-X-Name-Last: Sujai
Author-Name: V. Sangeetha
Author-X-Name-First: V.
Author-X-Name-Last: Sangeetha
Title: Linear Kernel pattern matched discriminative deep convolutive neural network for dynamic web page ranking with big data
Abstract:
Websites and information are plentiful. Search engines return many pages based on user requests. Thus, unstructured web content compromises information retrieval. A new gestalt pattern matched linear kernel discriminant maxpooled deep convolutive neural network (GPMLKDMDCNN) is to rank web pages by query. At first, Szymkiewicz-Simpson coefficient and Gestalt pattern matching Paice-Husk method are to remove stop words and stem words during preparation. Fisher kernelised linear discriminant analysis then selects keywords from preprocessed data. Bivariate Rosenthal correlation is utilised for page rank-based correlation outcomes and saving time, and online sites are ranked by user query with higher accuracy. The experiment uses parameters such as accuracy, false-positive rate, ranking time, and memory consumption. The evaluation shows that the GPMLKDMDCNN method is superior in using the CACM dataset with maximum ranking accuracy of 5%, minimum false positive rate and memory consumption of 39% and 13%, and quicker ranking time by 20% than the existing methods, respectively.
Journal: Int. J. of Critical Infrastructures
Pages: 416-434
Issue: 5
Volume: 20
Year: 2024
Keywords: web pages ranking; maxpooled deep convolutive neural network; Szymkiewicz-Simpson coefficient; gestalt pattern matched Paice-Husk algorithm; Fisher Kernelised linear discriminant analysis; bivariate Rosenthal correlation.
File-URL: http://www.inderscience.com/link.php?id=141441
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Template-Type: ReDIF-Article 1.0
Author-Name: Ponna Mahesh Kumar
Author-X-Name-First: Ponna Mahesh
Author-X-Name-Last: Kumar
Author-Name: P. Srinivasa Rao
Author-X-Name-First: P. Srinivasa
Author-X-Name-Last: Rao
Title: Mining closed high utility itemsets using sliding window infrastructure model over data stream
Abstract:
A group of products that has utility values and that are sold together greater than a preset lowest utility cut-off is produced by mining high-utility itemsets. These itemsets' profit units have external and internal usefulness values. In each transaction, the quantity of each item sold, respectively, is considered to determine the utilities of these itemsets. As a result, assessing an itemset's high utility is symmetrically dependent on all of its internal and external utilities. Both utilities contributed equally, and there are two key deciding considerations. First, selling groupings of low-external utility commodities generally meets the minimal utility requirement. Regular itemset mining can help find such itemsets. Second, numerous high-utility itemsets are created; thus, some interesting or significant ones may be omitted. This study applies an asymmetric technique that overlooks interior utility counts to discover those with considerable external utility counts. Two genuine datasets showed that external utility values strongly affect high utility itemsets. This study also shows that high minimal utility threshold values and a faster method increase this influence.
Journal: Int. J. of Critical Infrastructures
Pages: 447-462
Issue: 5
Volume: 20
Year: 2024
Keywords: high utility itemset; sliding window; information extraction; high-utility itemset mining; HUIM; itemset mining.
File-URL: http://www.inderscience.com/link.php?id=141442
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:5:p:447-462

Template-Type: ReDIF-Article 1.0
Author-Name: Abdulaziz T. Almaktoom
Author-X-Name-First: Abdulaziz T.
Author-X-Name-Last: Almaktoom
Author-Name: Mawadda M. Samkari
Author-X-Name-First: Mawadda M.
Author-X-Name-Last: Samkari
Title: Multiple criteria decision-making for determining the optimal wind farm site under uncertainty
Abstract:
Optimal wind turbine location plays a major role in power generation and turbine life cycle. Advances have been made in the subject of multiple criteria decision-making (MCDM), resulting in new methods for improving and analysing the decision of wind farm location while considering various uncertainty resources. Sources of uncertainty, such as wind availability, demand variability, and the costs of maintenance and wind turbines on wind farm allocation, can reduce energy and operations costs. In this research, a novel robust MCDM model for wind farm allocation has been developed. A case study involving mathematical simulation for three wind farm locations in Saudi Arabia has been employed to demonstrate the developed research and tools. The research contributions proposed the developed robust MCDM approach using the analytic hierarchy process (AHP), technique for order of preference by similarity to ideal solution (TOPSIS), and robust design (RD) could empower wind farm designers to have a better grasp of the weaknesses and strengths of their decision on wind farm allocation. Also, the paper advances a new approach that is practical and flexible for decision-makers. In addition, the research gives a valuable guideline for selecting the optimal site for a wind farm in other countries.
Journal: Int. J. of Critical Infrastructures
Pages: 463-489
Issue: 5
Volume: 20
Year: 2024
Keywords: multiple criteria decision methods; MCDM; multiple criteria decision analysis; MCDA; analytic hierarchy process; AHP; TOPSIS; robust design methodology; RDM.
File-URL: http://www.inderscience.com/link.php?id=141443
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:5:p:463-489

Template-Type: ReDIF-Article 1.0
Author-Name: Pushpa Singh
Author-X-Name-First: Pushpa
Author-X-Name-Last: Singh
Author-Name: Narendra Singh
Author-X-Name-First: Narendra
Author-X-Name-Last: Singh
Author-Name: Rajnesh Singh
Author-X-Name-First: Rajnesh
Author-X-Name-Last: Singh
Author-Name: Nishu Panwar
Author-X-Name-First: Nishu
Author-X-Name-Last: Panwar
Author-Name: Sunil Gupta
Author-X-Name-First: Sunil
Author-X-Name-Last: Gupta
Title: Role of e-adoption of emerging technology in 4P organisational framework during COVID-19
Abstract:
During the COVID-19, micro, small, and medium-scale business organisations have suffered economic fragility. Apart from lockdown, social distancing and the traditional style of the business process are the factors that affect the business organisation. A business organisation utilising e-adoption of emerging technologies such as artificial intelligence (AI), blockchain, internet of things (IoT), cloud computing, etc., have survived well in the market and achieved high-profit gain. In this paper, we explore the challenges of traditional business organisations. Traditional business organisation frameworks based on 4P: people, process, product and profit are based on manual processes and away from emerging technologies. The proposed organisational framework revolutionised traditional business practices and enhanced productivity, efficiency, and customer retention. People can connect and access business organisations with end-user devices such as smartphones, desktops, laptops, and other hand-held devices.
Journal: Int. J. of Critical Infrastructures
Pages: 435-446
Issue: 5
Volume: 20
Year: 2024
Keywords: e-adoption; organisation; COVID-19; AI; blockchain.
File-URL: http://www.inderscience.com/link.php?id=141444
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:5:p:435-446

Template-Type: ReDIF-Article 1.0
Author-Name: Mostafa Pouyakian
Author-X-Name-First: Mostafa
Author-X-Name-Last: Pouyakian
Author-Name: Ali Akbar Shafikhani
Author-X-Name-First: Ali Akbar
Author-X-Name-Last: Shafikhani
Author-Name: Amir Abbas Najafi
Author-X-Name-First: Amir Abbas
Author-X-Name-Last: Najafi
Author-Name: Behrouz Afshar-Nadjafi
Author-X-Name-First: Behrouz
Author-X-Name-Last: Afshar-Nadjafi
Author-Name: Amir Kavousi
Author-X-Name-First: Amir
Author-X-Name-Last: Kavousi
Title: Investigating safety development methodologies in the construction industry and identifying gaps in the studies: a review article
Abstract:
Identifying the appropriate safety methodology is essential to improving construction safety performance. This study aims to investigate safety development methodologies in the construction industry and identify gaps in the studies. Articles published from 2000 to 2022 were reviewed. Seventy-seven eligible articles were selected based on comprehensive and exclusive criteria. After obtaining selected literature, gaps in using these methodologies were discussed. Twelve criteria were used to compare safety methodologies. The selected literature focused more on the construction phase and did not provide an effective strategy in the project planning phase. Although the studies had specific benefits, none examined the safety program based on actual project conditions (resource, time, and cost constraints). There is a need for a model that examines safety in terms of actual project conditions (time, cost, and resource constraints). In addition, the model must optimise not only safety but also other vital components of the project (cost, time, and quality) while considering resource constraints (especially equipment constraints). If such a model is designed, the project team will not resist safety changes, which benefits all the construction stakeholders.
Journal: Int. J. of Critical Infrastructures
Pages: 163-194
Issue: 2
Volume: 20
Year: 2024
Keywords: construction industry; safety management; project schedule; occupational health.
File-URL: http://www.inderscience.com/link.php?id=137403
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:2:p:163-194

Template-Type: ReDIF-Article 1.0
Author-Name: Gonzalo Cáceres
Author-X-Name-First: Gonzalo
Author-X-Name-Last: Cáceres
Title: Argentina's critical infrastructures: topics for their regulation
Abstract:
Argentina's last National Defence Policy Directive (2021) explicitly mentions the protection of critical infrastructures, making it necessary to define them, establish priorities and responsibilities. However, Argentina published a first critical infrastructure standard in 2019 that lists vaguely those sectors to be included. The resolution does not allow to program actions and establish responsibilities since there is no identification of actors and, therefore, of their duties. In this article, we will discuss the relevant aspects that could be considered for future legislative work in Argentina and the role of the Ministry of Defence. Main topics are: 1) the genesis of the notion of critical infrastructures and the aspects that gave rise to their identification as the object of security policy and that of National Defence in particular; 2) those cases that are of interest in thinking about the national case in comparative perspective; 3) a synthesis of the elements under discussion that we understand structure the treatment of critical infrastructures.
Journal: Int. J. of Critical Infrastructures
Pages: 97-110
Issue: 2
Volume: 20
Year: 2024
Keywords: critical infrastructure legislation; Argentina; national defence; security.
File-URL: http://www.inderscience.com/link.php?id=137404
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:2:p:97-110

Template-Type: ReDIF-Article 1.0
Author-Name: Edwin Shalom Soji
Author-X-Name-First: Edwin Shalom
Author-X-Name-Last: Soji
Author-Name: T. Kamalakannan
Author-X-Name-First: T.
Author-X-Name-Last: Kamalakannan
Title: Efficient Indian sign language recognition and classification using enhanced machine learning approach
Abstract:
Deafness and voice impairment are two significant disabilities that make it difficult for people to communicate in verbal languages with others in a verbally communicating population. To solve this problem, the sign language recognition (SLR) system was constructed by combining machine learning and deep learning. The SLR employs hand gestures to convey messages. Earlier research aims to develop vision-based recognisers by extracting feature descriptors from gesture photos. When dealing with a large sign vocabulary recorded under chaotic and complex backgrounds, these strategies are ineffective. Hence, an improved convolution neural network is proposed in this paper to predict the most frequently used gestures in the Indian population with improved efficiency. The presented system is compared to SVM and CNN. The suggested approach is tested on 2,565 UCI instances and 22 training attributes. It showed both-handed ISL movements against various backgrounds. The augmented CNN has a precision of 89% and 90.1% accuracy, which is higher than most other approaches. According to this survey, we had an 83% recall and a 0.4 F score. Python evaluates our work.
Journal: Int. J. of Critical Infrastructures
Pages: 125-138
Issue: 2
Volume: 20
Year: 2024
Keywords: sign language recognition; SLR; machine learning; convolution neural network; CNN; Indian sign languages; ISLs; accuracy; precision.
File-URL: http://www.inderscience.com/link.php?id=137405
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:2:p:125-138

Template-Type: ReDIF-Article 1.0
Author-Name: Arnav Bhardwaj
Author-X-Name-First: Arnav
Author-X-Name-Last: Bhardwaj
Author-Name: Hitesh Agarwal
Author-X-Name-First: Hitesh
Author-X-Name-Last: Agarwal
Author-Name: Anuj Rani
Author-X-Name-First: Anuj
Author-X-Name-Last: Rani
Author-Name: Prakash Srivastava
Author-X-Name-First: Prakash
Author-X-Name-Last: Srivastava
Author-Name: Manoj Kumar
Author-X-Name-First: Manoj
Author-X-Name-Last: Kumar
Author-Name: Sunil Gupta
Author-X-Name-First: Sunil
Author-X-Name-Last: Gupta
Title: Non-invasive prediction mechanism for COVID-19 disease using machine learning algorithms
Abstract:
This paper has focused on developing a model to detect non-diagnostically whether the person is infected with the COVID-19 disease using all relevant symptoms and details mentioned by the person and then comparing it with a pre-defined dataset of positive cases using machine learning. Different models have been developed to predict the same but none of them focused on the detection of COVID-19 based on symptoms. In a developing nation with a huge population, where the diagnostic availability is scarce, just scanning the body temperature will not help in detection of COVID-19 of a particular individual. This paper presents a model that can predict COVID-19 cases without any testing kit to an accuracy of 99.30%, performing better than other similar approaches with objective to put forward a method that can reduce the need of producing testing kits and also the need to wait for hours before we get the results.
Journal: Int. J. of Critical Infrastructures
Pages: 111-124
Issue: 2
Volume: 20
Year: 2024
Keywords: COVID-19; non-invasive; symptoms; machine learning.
File-URL: http://www.inderscience.com/link.php?id=137406
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:2:p:111-124

Template-Type: ReDIF-Article 1.0
Author-Name: Alaba O. Adejimi
Author-X-Name-First: Alaba O.
Author-X-Name-Last: Adejimi
Author-Name: Adesina Simon Sodiya
Author-X-Name-First: Adesina Simon
Author-X-Name-Last: Sodiya
Author-Name: Olusegun A. Ojesanmi
Author-X-Name-First: Olusegun A.
Author-X-Name-Last: Ojesanmi
Author-Name: Olusola J. Adeniran
Author-X-Name-First: Olusola J.
Author-X-Name-Last: Adeniran
Title: A structured model for identification and classification of critical information infrastructure
Abstract:
The growing incidence of attacks on critical information infrastructures has necessitated the development of a model for properly identifying and designating information infrastructure whose destruction or interruption could jeopardise the well-being of a state and ensure its preservation. Some of the previous methodologies and models were prejudiced, lacked scientific support, and the criticality criteria were not categorised to encompass global demands. To universally determine the criticality of information infrastructure, this work proposes a factor impact sensitivity approach (FISA), which identifies, structures, and models relevant state criteria into mathematical concepts. An application was developed to implement the structured mathematical model and designate an infrastructure as 'not critical', 'moderately critical' or 'highly critical' based on the sensitivity result. FISA was found to be 94.76% efficient and 97.62% satisfactory. The developed web application will serve as an assessment guide for the office in charge of the identification of critical national information infrastructure.
Journal: Int. J. of Critical Infrastructures
Pages: 139-162
Issue: 2
Volume: 20
Year: 2024
Keywords: criticality strength; information infrastructure; categorisation; multi-criteria; impact factor; risk assessment; alternative scope; likelihood; disruption.
File-URL: http://www.inderscience.com/link.php?id=137407
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Handle: RePEc:ids:ijcist:v:20:y:2024:i:2:p:139-162