Sanad buying hash

__________________________

📍 Verified store!

📍 Guarantees! Quality! Reviews!

__________________________

▼▼ ▼▼ ▼▼ ▼▼ ▼▼ ▼▼ ▼▼

▲▲ ▲▲ ▲▲ ▲▲ ▲▲ ▲▲ ▲▲

Sanad buying hash

Email or phone Password Forgot account? Create new account. It looks like you were misusing this feature by going too fast. Forgot account?

EP 45: XBox Underground (Part 1)

Sanad buying hash

Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation e. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors. Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression 'in press'. For example: Smith, J. Article Title. Journal Title. Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase. Online First articles are published online here, before they appear in a journal issue. Online First articles are fully citeable, complete with a DOI. They can be cited, read, and downloaded. Online First articles are published as Open Access OA articles to make the latest research available as early as possible. Register for our alerting service , which notifies you by email when new issues are published online. International Journal of Critical Infrastructures Forthcoming and Online First Articles Forthcoming and Online First Articles International Journal of Critical Infrastructures Forthcoming articles have been peer-reviewed and accepted for publication but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Articles marked with this Open Access icon are Online First articles. They are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses. Fevzi Esen Abstract : Economic losses of earthquakes raised many questions regarding the adequacy of the current seismic design criteria and seismic isolation in data centers. Some organizations have accommodated new explicit seismic isolation applications in their business continuity and disaster recovery plans. These applications aim acceptable damage levels that correspond acceptable business interruption for data centers in case of an earthquake. In this study, we aim to discuss the importance of seismic isolation technologies which can be implemented for data centers against seismic disasters within business continuity and disaster recovery planning context. We conduct a literature review to provide a clearer aspect on seismic isolation applications for data centers. These standards provide technical documentation for service functioning with high levels of availability during an outage. Keywords : information technologies; data centers; seismic isolation; business continuity. DOI: The construction progress data acquisition and decoding module circuit is set to complete the construction progress data acquisition, and the K-means algorithm is used to preprocess the construction progress data. Decompose the construction project progress, divide the large-scale construction project into different progress management levels by WBS analysis method, establish functional information module, import the construction project progress data into BIM model, and realise the BIM information function management of the method. The experimental results show that the proposed method has low response time and multiple schedule management indicators, and the shortest response time of the proposed method is only 1. Keywords : management pheromone; management rules; definition residue; BIM model. Cyber-insurance is an instrument of risk transfer, enabling organisations to insure themselves against financial losses caused by cyber incidents and get access to incident management services. This paper provides an empirical study of the use of cyber-insurance in the Norwegian maritime sector, with a particular emphasis on the effects of the General Data Protection Regulation and the Directive on Security of Network and Information Systems. Norway constitutes a significant case as a country having a highly mature IT infrastructure and well-developed maritime industry. Interviews were conducted with supplier- and demand-side maritime actors. Findings point to a widespread lack of knowledge about cyber-insurance. Keywords : security; risk; policy; regulation; cyber-insurance; information sharing. 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. 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 Keywords : cloud intelligent infrastructures; convolution neural network; intrusion detection and prevention; long short-term memory; random forest; neural network; security. 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. Keywords : fuzzy system; battery management systems; BMSs; sliding-mode; state of charge; SoC; lithium-ion battery; applications infrastructures. Silvia Priscila, Ravindra Pathak, Prasath Alias Surendhar S, Bobur Sobirov Abstract : Both technological and social systems combine to construct the infrastructure and processes of digital technologies, ensuring that an organisation's aims and objectives are achieved. The firm created and employed access controls and measures to protect its data and information systems. The exploitation of information systems and disregard for internet security protocols are the main causes of computer security breaches. Non-compliance with information security regulations is a serious risk for businesses. It is crucial to identify, investigate, and consider the elements that affect compliance and the deployment of computer security for successful conformity and human adoption of computer security technology and compliance with computer practices. Computer engineering is increasingly automated with high tech. Technology and engineering in technical control systems have improved. The study examines clever technical control in electrical automation and intelligent technologies. It also analyses this technology's potential applications and future development trends in electrical engineering. Reviewing machine learning methods for technical control issues, we concentrate on the deterministic situation to illustrate the numerically complex issues. Keywords : computer security abiding; stiffness adjusting; evaluating and monitoring; levelling; technical controls; controlling impedance. 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. Findings suggest a dilapidated infrastructure spread across SSA, which has mired productivity growth, hence slow industrial sector growth. This study fills a vacuum in the literature by investigating the economic effects of infrastructure investment on industrial sector growth in SSA. The study aims to systematically unravel the short-run and long-run effects of infrastructural inputs on industrial sector growth, using disaggregated System-GMM approach. Findings disclosed that infrastructural investment significantly influence industrial sector growth in SSA. Overall outcomes revealed diverse significant effects from various types of infrastructural tech on industrial growth across sub-regional countries. Similarly, post estimations analysis via robust Arellano-Bond Autocorrelation and Hansen tests were adopted to establish the absence of first and second-order autocorrelation and over-identifying restrictions of instruments in the estimated models. The study uniquely disaggregated short-run and long-run effects of infrastructure investment on industrial sector growth via system GMM to provide valuable insights to policymakers. Hence, sub-regional countries should draft more policy support to prioritise economically motivated factor inputs such as information techs, access to energy, transport and water resources to expedite industrial sector growth. Anandhavalli, A. Bhuvaneswari Abstract : Modern technology's blessing, the internet of things IoT , has made remote monitoring and automation a reality. IoT devices are now the most economical option for wireless sensor networks. These gadgets were created with a specific purpose; therefore, computing power and power sources are restricted to meet that need. Due to power limitations, providing security for this type of network is a real issue. The game of life-based security key mechanism GLSKM technique is designed to leverage more low-level hardware bitwise operations during the key generation and exchanging phase instead of more computationally integrated energy-starving activities. This work presents two modules: the game of life-based key exchange mechanism and the random seed and iteration limit selector. Both modules are built to use simpler bitwise hardware-targeted instructions to achieve minimal power consumption without sacrificing security. Keywords : energy efficient; internet of things; IoT; game of life; security key exchange; wireless sensor networks; WSNs. Venkata Krishnaiah, K. Vijaya Bhaskar Raju Abstract : Finding lucrative building designs has been the major problem the construction industry has been experiencing lately. This issue can be fixed by dramatically lowering the structural part's self-weight and sizing it down. Lightweight concrete LWC is the sole material that can be used to achieve this. In earlier tests, various lightweight aggregates were utilised to lower the density. The primary benefits of LWC columns are that they do not require a reinforced cage or forms because their steel tubes can be used just as well as scaffolding and are fireproof. Based on the numerous research projects undertaken, it can be concluded that circular poles should be favoured over a square LWC to boost stability and satisfy various design needs. This study defines LWC while considering strength component development. Thus, this experiment examines silica fume and pumice stone as entire substitutions. After moulding samples with the desired mix ratio, compression, tensile, and bending capacities are assessed. This specially designed LWC mix of M30 grade concrete has 0. Keywords : critical infrastructure; lightweight concrete; LWC; pumice; silica fume; nylon fibre; waste rubber powder; mechanical properties; thermal properties. To this end, the study takes Dali city as the research object and constructs a corresponding grey correlation degree model of the fragility of tourism city economic system based on the objective entropy value method and GRA. The study uses this model to systematically analyse the causes and mechanisms of action of the economic system fragility of tourism-oriented cities. The results show that Dali's economic subsystem has a relatively homogeneous industrial structure, and its coping capacity is growing flatly while its sensitivity is generally on the rise. The fragility of the social and economic subsystems correlates highly with the vulnerability of the city's economic system. This study provides targeted suggestions for sustainable development of tourism cities through a comprehensive analysis of their economic system fragility. Keywords : tourist cities; economic system vulnerability; sustainable development; entropy method; GRA. Helen Arockia Selvi, T. Rajendran Abstract : Image encryption in the healthcare sector is used to protect sensitive medical images, such as X-rays, MRI scans, and CT scans, from unauthorised access and disclosure. This is important because medical images often contain personal and confidential information that can be used for malicious purposes if it falls into the wrong hands. The proposed research utilises a hyperchaotic system along with DNA coding for the secure data transfer of medical images. The closed hash table method was used to scramble the random chaotic sequences produced by the Chen system. The encryption approach breaks down the robust pixel correlation and allows safe data transfer for teleradiology applications. The two-stage scrambling followed by a single-stage diffusion ensures security in data transfer and robustness against attacks. The real-time medical images are used in this research and validated by the performance metrics. Keywords : encryption; chaotic function; teleradiology; decryption; data transfer critical infrastructures. The study analyses the causes of enterprise financial crises from internal factors and external factors, and constructs an early warning system for enterprise management financial crises FCWS based on the analysis results. To address the shortcomings of traditional early warning methods in terms of low accuracy and efficiency, the study combines signal analysis model KLR and BP neural network BPNN to build a KLR-BP enterprise management financial crisis early warning model. Thus, the KLR-BP model can be practically applied to enterprise management financial early warning and make a certain contribution to the development of China's market economy. The article proposes a blockchain based healthcare management system that addresses critical challenge of secure medical data sharing. The system incorporates zero trust principles and blockchain technology to verify compliance with patient records and facilitate secure data exchange among research institutions, patients, and servers. The proposed distributed zero trust based blockchain structure DZTBS effectively meets the privacy and security requirements of availability, integrity, and confidentiality. Furthermore, our system outperforms existing encryption algorithms, including the advanced encryption standard and elliptic curve digital signature algorithm with a mean encryption time of 0. These results show improved security and efficiency offered by proposed healthcare management system. Keywords : blockchain technology; data sharing; electronic medical records; security; zero trust principle. Concrete fracture energy is important for safe structural design and failure behaviour modelling because it is quasi-brittle. The complex nonlinear behaviour of concrete during fracture has led to ongoing debates regarding fracture energy prediction using existing estimation techniques. Using the previous dataset, prediction approaches were developed to measure the preliminary Gf and total GF fracture energies of concrete utilising mechanical properties and mixed design elements. Two hundred sixty-four experimental recordings were gathered from an earlier study to construct and analyse ideas. Gf and GF given the rationale and model processing simplicity. Keywords : concrete; fracture energy; neural network; estimation; radial basis function; coot optimisation algorithm; whale optimisation algorithm; WOA. Parthasarathy, Arnab Jana Abstract : This research examines the evolution of snow clearance infrastructure in the Kashmir Valley and its direct link to critical infrastructure-transportation. The study analyses numerous data sources such as snow removal action plans, departmental letters, notes, presentations, requisition letters, and official communications using a qualitative research approach, specifically content analysis. The research demonstrates the severe influence of snow removal on critical infrastructure by applying the theoretical framework of punctuated equilibrium theory and analysing its components, including pluralism, conflict expansion, policy image, and venue shopping. The data show a major shift from manual snow removal practices to mechanised operations between and , which was driven by significant punctuations. Furthermore, the study emphasises the continual evolution of snow removal practices in Kashmir, with a focus on the incorporation of cutting-edge technologies and globally popular methodologies to ensure the resilience and functionality of critical transportation networks. The study provides important insights for policymakers and winter road maintenance managers involved in managing essential infrastructure in snowy regions. Keywords : critical infrastructure; snow clearance; evolution; punctuations; policy; action plans; India. This fusion transcends data processing to encompass meticulous safety monitoring via collective knowledge management. Envision a harmonised framework where management of keys, tables, hardware, and ML mining supervision coalesce to shield enterprise data robustly. This approach, examined through various lenses, including security and big data capacity testing, assesses risk mitigation enthusiastically while crafting a business management platform that contemplates corporate leadership needs, offering an ML data security architecture blueprint. Although challenges like refining neural networks for optimal global efficiency persist, the study highlights its remarkable, unblemished performance across modules on the ML-based corporate data safety regulation platform. It proficiently meets daily organisational needs and assures AI's vital role in enterprise data security management, providing a scaffold for future research and marking a paradigm for upcoming explorations in the domain. Keywords : artificial intelligence; AI; industrial information; security management; machine learning techniques; crowd sense technology; information security management. Despite the significance of its usage, there is dearth of studies that comprehend the applications of BIM and its potential benefits for construction work. The present work aims to understand the recent developments and applications of BIM research in the construction industry. In this regard, a systematic nine-step approach using bibliometric analysis is performed to scrutinise articles published in Scopus database. Based on the scrutinised articles, a detailed examination using thematic and cluster analysis was applied to explore the potential BIM areas. Findings indicated key clusters: 1 architectural design aspects; 2 sustainable development; 3 project management knowledge areas. The outcome of the study provides a holistic understanding of these clusters and suggests exploration of potentially challenging areas for future BIM applications. Keywords : building information modelling; BIM; construction industry; bibliometric analysis; thematic analysis; cluster analysis; sustainable development. Each farmer must produce high-quality harvests despite water shortages and plant illnesses. They must delicately balance soil nutrients, sustaining fertility like a nation's lifeline. From these trials emerged the modern Indian farmer's hero: an IoT-based decision support system, a smart agricultural beacon. This miracle anticipates agricultural yield and guards their livelihood like a sentinel. It monitors soil fertility, stops soil degradation, and considers excessive irrigation a crime against nature. Wireless sensor devices elegantly communicate data to a central server to arrange this technology symphony. In the digital world, a machine learning system does predictive irrigation. The weather, soil, rainfall, seed damage, drought, and alchemical pesticides and fertilisers are considered. Many pioneers in this growing industry have failed, resulting in incorrect estimates and low crop yields. This clever technique turns parched areas into bountiful goldmines by predicting crop yields with precision, making farmers contemporary alchemists. Keywords : correlation filter; sequential forward; prediction; IoT-based intelligent infrastructure; decision support system; correlation filter. Seema, S. Suman Rajest, Biswaranjan Senapati, S. Silvia Priscila, Deepak K. Sinha Abstract : The selection of exact material for shielding analysis is challenging in radiation protection. The primary objective of shielding analysis is to reduce radiation exposure to the occupational worker at their workplace. Generally, high-density concrete is selected as the shielding material to prevent accidental exposure to gamma and neutron radiation. Composite material or multilayer shielding materials are generally used to optimize the cost of concrete with maximum benefit to the society of occupational radiation workers. A surrogate model for concrete's overall strength using cement, fly ash, and coarse and fine aggregates is created using machine learning and ensemble learning. Ensemble learning in machine learning solves underfitting and overfitting problems when fitting a regression model for shielding analysis. As density increases, concrete overall strength decreases. Several samples of various types of concrete different compositions are collected as input data. Finally, a multi-attribute decision-making method is applied to select the appropriate type of concrete. The research presents the ensemble learning based regression technique coupled with multi attribute decision making method to recommend the exact variety of concrete for shielding gamma and neutron radiation. As a result, requirement for low power and high speed copyright protection system for multimedia objects is hovering. In this article, authors have projected one spatial domain-based image watermarking structure for multimedia copyright protection and its hardware level implementation based on field programmable gate array FPGA. Moreover, single electron transistor SET implementation for the structure has also been presented. The technique uses least significant bit LSB plane-based information hiding and all the modules of embedding and extraction block are realised with SET. It has been observed that this scheme shows noteworthy imperceptibility along with robustness. The result of SET execution confirms significantly low power consumption. We compared the performance concerning time and memory complexity with the FP tree and state-of-the-art boss tree. Abstract : Gasoline cars are being replaced by electric vehicles EVs , which adds to the strain on the power grid due to their charging needs. Uncontrolled EVs can disrupt the grid; therefore, reliable planning is necessary. Increased distributed generation DG resources, especially renewable energy, may disrupt the electrical system. Effective mitigation requires demand-side planning and wise utilisation of emerging technologies, including energy storage. This study recommends optimising EV and DG charging and discharging schedules to fulfil regulated planning needs. Power company schedules depend on parking lot traffic to meet grid goals. The primary objectives are to maximise vehicle holders' and companies' earnings, minimise losses, and reduce parking lot travel time. Investigating critical load sensitivity improves charge and discharge control. The proposed approach utilises a hybrid biogeographic harmony search BHS. BHS models island species movement, speciation, and extinction using biogeographical mathematics. A sample test system illustrates the method and concept in various settings. Optimal distribution resource management increases network profitability by 8. Keywords : electric vehicles; parking zone; renewable energy sources; distributed generation; DG; harmony search algorithm; HS; biogeography-based optimisation algorithm; BBO. This study examines how private and public sectors affect PPP road project performance at different stages of development and throughout the construction life cycle. The literature review and survey of private and public professionals to identify and verify CRFs may provide insights from industry experts. CFA may disclose PPP road project dynamics by comparing the six phases and private and public sectors. A mitigation handbook for avoiding and correcting issues may result from the study. Risk allocation, project management, and PPP success increase with this study. The concurrent access of diamond crossing by multiple trains, caused accidents from last decades due to signalling conflicts. This article is proposing a wireless sensor network model with LoRa communication technique and weight sensor to automate all signals related to double diamond crossing. Weight sensor is used as a train detection method to measure the threshold weight of the incoming train, then all diamond crossing signals change their aspect according to input data. Reliability and accuracy of weight sensor in any atmospheric and flood condition is shown. A novel weight sensor-based algorithm is proposed in the presented manuscript to automate all related signal aspects for the safe movement of a train with minimum time delay through double diamond crossing. Despite numerous vision-based fall detection methods, challenges persist regarding accuracy and computation costs, especially in resource-constrained IoT environments. This paper proposes a novel fall detection approach leveraging the Yolo algorithm, known for its efficiency in minimising computation costs while maintaining high accuracy. By utilising a diverse fall image dataset, the method undergoes rigorous training and evaluation, employing standard performance metrics. Notably, the Yolo algorithm's computational efficiency ensures minimal resource utilisation, making it suitable for real-time deployment in IoT devices within smart city infrastructures. Consequently, this method presents a promising solution for enhancing fall detection accuracy while optimising computational resources, thus advancing safety measures in urban environments. Keywords : anomaly detection; fall detection; vision system; Yolo; smart city; internet of things; IoT; mean average precision; mAP; algorithm's computational efficiency. Suganya, Sukhwinder Sharma, Sunita Dhotre Abstract : Artificial intelligence AI has dramatically transformed the electric power management sector, ushering in higher levels of efficiency, sustainability, and intelligent energy distribution. This shift has enabled more optimised consumption patterns and significantly reduced waste. While AI improves power management through predictive maintenance and demand-response optimisation, it also presents transparency issues related to its decision-making algorithms, complicating ESG adherence. To address these concerns, we introduce a novel architectural framework designed to enhance transparency and directly confront ESG challenges associated with AI in power management. Our thorough trials validate the concept, presenting a potential strategy to harmonising technical advancement with ESG principles. A sustainable and equitable future for power management technology requires this balance. Keywords : artificial intelligence; electric power management; environmental and social governance; ESG; transparency and information disclosure; technological advancements. In this work, smart construction techniques are implemented and investigated for risk management and quality monitoring in a cost-effective manner in a small-scale construction site in India. The proposed work focuses on the general hazards and the risks faced by engineers in such sites. To mitigate the challenges, cost effective and reusable smart solutions set up is implemented and validated in a real-time small construction site. The smart solution setup provided support to the construction site engineers to predict the damages in the Scaffolds and Formwork, and testing the quality of concrete, verticality check, surface levelling and formwork deflection. The proposed solutions can be used to improve building critical infrastructures in a cost-effective manner especially in middle- and lower-income economies. Keywords : formwork; labour safety; quality monitoring; risk management; scaffoldings; smart construction; India. Belina V. Sara, A. Jayanthiladevi Abstract : In the face of escalating threats to aquatic ecosystems posed by marine debris, the demand for precise and efficient classification techniques becomes paramount. This study employs image segmentation methods Canny edge detection, Sobel operator, and Laplacian of Gaussian LoG to partition photographs of maritime trash. A notable addition is the integration of SVM-based classification, offering promising avenues for environmental surveillance and disaster management. By incorporating the LoG process, the identification of blob-like structures enhances the accuracy of debris segmentation. Comparative analysis utilising metrics like intersection over union IoU , dice coefficient, and Hausdorff distance underscores the efficacy of the combined LoG and SVM approach. This synergistic method adeptly detects edges via the LoG operator and ensures accurate debris classification through SVM modelling. The results demonstrate significant improvements, yielding higher IoU 0. Executed in Python, this research propels marine debris analysis forward by furnishing a robust framework for automatic image categorisation, which is vital for initiatives aimed at environmental preservation. Vidhya Abstract : The widespread usage of high-end digital technologies has greatly increased cyber risks. To fight cybercrimes, a smart model should categorise and learn from data autonomously. Pop-up messages also entice users and enable fraud. We use a neural network to predict unexpected pop-up message content in this paper. Modern malware and its powerful obfuscation algorithms have made traditional malware detection methods ineffective. However, deep belief neural networks DBNNs have garnered attention from researchers for malware detection to fight conventional cybercrime prevention methods in the long run. MDDBNN malware detection deep belief neural network , based on file properties and contents, is proposed in this research for malware classification. Keywords : deep belief networks; cyber security; cybercrime; spam and deep learning; DL; support vector machine; SVM. The first section of this article introduces DLTs, focusing on blockchain as the main paradigm. It highlights three critical characteristics of blockchain: decentralisation, transparency, and security, and emphasises how blockchain is transforming various industries, including supply chain management and finance. Subsequently, the discussion shifts to new developments and approaches in the DLT space. It introduces next-generation ledgers designed to address traditional blockchains' scalability, energy efficiency, and interoperability challenges. The study delves into modern innovations that achieve higher transaction speeds and greater flexibility, such as hybrid models and directed acyclic graphs DAGs. A significant portion is dedicated to how these advanced DLTs are used to transform sectors like healthcare government, secure patient data management, and enhance transparency and citizen participation. The article also addresses the challenges and ethical considerations of using these technologies. Finally, the paper predicts that DLTs will improve efficiency and innovation in industries outside blockchain technology. To maximise these new technologies' potential, research and interdisciplinary collaboration are essential. Keywords : blockchain; decentralisation; cryptocurrency; smart contracts; ledger security; distributed computing; digital identity; interoperability; scalability; tokenisation. Ibrahim, Hamada Esmaiel, Bassem Abd-El-Atty Abstract : Since its invention by Satoshi Nakamoto in Nakamoto, as the backbone of the first successful Bitcoin digital cryptocurrency, blockchain technology has evolved and experienced several innovative breakthroughs. It has become a disruptive solution for developing distributed and decentralised applications in many domains beyond cryptocurrencies. One example of these domains is the contemporary, riskily interdependent ICT-based critical infrastructure. This multi-domain literature review explores the literature of blockchain and critical infrastructure domains, attempting to match the features and benefits provided by the former to the challenges and requirements encountered in the latter. The review concludes that despite the known limitations of blockchain technology regarding scalability, interoperability, implementation complexity, and real-time requirements, it represents a promising enabling technology for addressing several challenges and requirements in the design and development of contemporary integrated and highly interdependent CIs. Future research directions are also highlighted. Keywords : critical infrastructures; critical infrastructures requirements and challenges; interdependency; risk assessment; complexity; blockchain technology; consortium blockchains; blockchain applications. Municipalities struggle to prioritise asset rehabilitation due to financial constraints. This study aims to develop a criticality model for water pipeline prediction, integrating expert insights. Sensitivity analysis identifies key factors influencing criticality. The model combines criticality and performance indexes to form a priority index, aiding municipalities in strategic capital planning. By pinpointing critical areas requiring immediate attention, this model enhances infrastructure management decision making. Keywords : assent management; risk management; paprika; criticality index. Consumers are now ready to experiment with the new types of food products. Authors have attempted to determine percentage of consumers with respect to adoption of frozen food products in this work. The study analyses socio-demographic characteristics and understand perception with respect to adoption of frozen food products. Early adopters perceived frozen food products to be value for money, had trust on quality, safety and brand, and also found it tasty. The overall analysis leads to a better understanding of consumer adoption towards frozen food with special reference to quality and safety. Keywords : consumer; perception; frozen food; socio-demographic; adoption; India. Consequently, organisations have embraced Industry 4. However, though the adoption rates of various digital tools in construction firms have increased significantly since , there is a paucity of systematic frameworks with construction-specific digitalisation dimensions and indicators required for successful technology adoption and readiness in the construction organisation. The study therefore proposes a holistic framework comprising dimensions and indicators specific to digitalisation readiness for construction organisations. The developed framework of the study will help construction organisations develop a concrete strategic graduation that sets up the roadmap for digital transformation and also ensures the identification of appropriate digital measures and investments. Keywords : Industry 4. To understand the impact of market incentive based environmental regulations on corporate financial performance, this study proposes a financial performance calculation model based on an improved long short-term memory network to evaluate corporate financial performance. On the basis of making assumptions, impact analysis is conducted through regression analysis and other methods. The experimental results indicate that the difference between output and expected financial performance is only 0. Technological innovation TI was significantly negatively correlated with market-based environmental regulation p Keywords : circular economy; market incentives; environmental regulation; financial performance; FP; LSTM. The study analyses how IoT technology may reduce manual errors, automate inventory monitoring, and give real-time data to improve decision-making. A radical literature review reveals construction inventory management issues include theft, material waste, and inefficient supply networks. We combine qualitative and quantitative studies to focus on managed production IoT device deployment. This observation analyses stock stages before and after IoT generation implementation using samples, showing that inventory management performance and stability have improved. The results demonstrate how the internet of things may transform operational optimisation. Material waste reduction, on-web page productivity, and inventory accuracy improved significantly. We offer an internet of things IoT -based inventory management architecture with analytical tables and graphs illustrating performance advantages and fee savings. The speech discusses multinational IoT integration efforts, including operational issues and acceptance challenges. The final paragraph shows how the internet of things can change building stock management. This article also covers future research goals and limits, focusing on IoT technology conversion and production management software growth. Keywords : internet of things; IoT; inventory management; commercial construction; cost efficiency; real-time tracking; supply chain; automation; and productivity. This paper proposes a novel solution for a mobile identity framework based on Elliptic Curve Cryptography ECC encompassing user authentication and signature. Our proposed approach is hardware-agnostic and does not rely on a SIM card. Additionally, it is cost-efficient without any third-party dependency. We perform informal security analysis to prove that our framework is secure from various attacks. We also evaluate the performance of our system and compare it with other protocols. No studies have compared the trade-off between time, cost, and safety while considering resource and equipment constraints. Equipment constraints may affect project scheduling and increase safety risks. Therefore, a project scheduling model that considers equipment constraints, time, cost, and safety risks is needed. This study aims to optimise cost, time, and safety risk by modelling safety plans in project scheduling problems with resource constraints. By solving this model, feasible solutions for time, cost, and safety risk trade-offs are provided. In addition, the model could also evaluate the risks of project activity, the risk of equipment and overtime, and minimise the overall safety risk of the project. This is archived by analysing the coal content in the coal reserves. SHAP allows users to understand the extent of relationships between each unique input data along with its corresponding output, as well as rank input variables in order of efficacy. Keywords : explainable artificial intelligence; XAI; artificial intelligence; gross calorific value; explainability. The purpose of this research is to analyze the critical roles of internal and external stakeholders. Data is gathered through in-depth interviews with internal and external stakeholders of two mega-HPPs. We found that deep collaboration and trust among internal stakeholders are critical for success. Such collaboration and trust can be achieved by not only solid communications and strictly following the contract agreement, but also through strategic choices that can limit excessive transaction costs and foster credible commitments of future benefit sharing among internal stakeholders. The critical requirements for a successful management of external stakeholders are the mitigation of environmental impacts. These factors have a performance-enhancing effect upon mega-HPP construction. The results speak to the following critical infrastructure problem domains: long term investment, stakeholder engagement, and environmental management in critical infrastructure construction. Additionally, tunnelling combined with seismic waves can lead to severe consequences. This study aims to thoroughly examine the interactions among tunnels, piles, and adjacent soil TPS , focusing on vibrational effects and mathematical modelling. A framework is proposed to predict pile behaviour before tunnelling and validate results from computational simulations. Using PLAXIS3D finite element software, the study investigates the complexities of tunnel-pile-soil interaction TPSI during seismic events, particularly evaluating the impact of tunnel excavation and seismic activity on 2 Keywords : tunnelling; seismic waves; structural interaction; pile foundations; PLAXIS3D software; deformation patterns. Sarma Abstract : The field of study for this work centers on enhancing security within the expanding domain of the Internet of Things IoT , where the need for reliable detection of malicious activities is critical. As IoT integrates a wide array of applications and hardware, the inherent online nature of these technologies makes vital infrastructure susceptible to cyberattacks. Despite the involvement of a significant community in critical applications like CPSs, traditional computational methodologies in anomaly-based programs often prove insufficient. This study aims to identify and classify issues at both the network and host levels using advanced ML and DL models, which offer promising solutions. By evaluating the precision and energy efficiency of these classifiers, the study seeks to determine the most accurate and time-efficient solution for defect detection in IoT systems. This work advances the field by proposing and validating sophisticated ML and DL techniques that significantly improve the detection and classification of cyber threats, thereby enhancing the security of IoT infrastructure. Abstract : The implementation of forensic techniques for password detection has garnered substantial scientific attention recently. Prior studies have explored the detection of forensic attacks on passwords but did not optimise interactions between attackers and defenders. They also failed to accurately detect fake passwords. Addressing these issues, this approach uses appropriate datasets and a novel generative adversarial network GAN technique for detecting digital forensic attacks. Integrating game theory and GANs for forensic threat detection enhances robustness and adaptability, enabling proactive defence plans and dynamic threat modelling. This fusion improves the interaction between attackers and defenders and increases the accuracy of false password detection. The generator produces new training instances, while the discriminator classifies them. Game theory significantly optimises the generated samples through accurate decision-making, enhancing interaction comfort between attackers and defenders. The proposed framework achieves a prediction accuracy of Consistently enhancing GAN structures could further improve the creation of realistic password patterns, benefiting applications like system security and password authentication.

Sanad buying hash