Newports Institute of Communications and Economics

Cloud-native architectures have revolutionized modern computing, but their fast deployment has demonstrated inconsistencies in security among the major providers of these applications, such as AWS, Azure, and GCP. Although both platforms provide a set of controls designed specifically to allow regulating certain aspects, the presence of features like sandboxing, privileged access management (PAM), as well as workload isolation varies widely. The differences have implications for the security posture of organisations trying to use a multi-cloud approach. This article will seek to identify and contrast the natural shortcomings of native security tooling, evaluate the use of cloud marketplaces to address critical security gaps, and analyse the risks architecturally arising out of excessive use of third-party integrations. A cross-platform study of the existing controls offered by AWS, Azure, and GCP was performed through the review of technical documentation, CSPM capabilities, and scholarly/commercial research published in 2020-25. To conduct this comparative evaluation, a matrix was developed to compare native features with industry best practices in cloud security, along with the particulars of PAM, sandboxing, micro-segmentation, and threat detection. We found that the implementation of least privilege access is not consistent across platforms, with Azure providing more role-based access control (RBAC), and GCP having less developed controls on sandboxing compute workloads. Configurations CSPM products tend not to notice a drift in configuration in real time, and many of the most important controls need to be tooled. Also, extensions to marketplaces make it harder to comply and respond to incidents. Cloud providers have evolved to provide security primitives, but critical gaps remain in the interpretation of the principles of zero trust in its native form. These inadequacies have to be addressed by organisations in terms of layered defence plans, active modelling of threats and enforcement of tight integration checks. Cross-platform security alignment is a vital requirement for healthy multi-cloud resilience.

Wireless sensor networks (WSNs) provides a major responsibility in the collection and processing of information from the real world. Similarly, cloud computing provides distributed platforms and resource sharing with the help of WSNs. The combination of these two technologies gives ease to communicate in virtual communities which is very beneficial in different domains. Cloud computing can be merged with WSNs in various applications. This will provide an easier way to understand sensor’s data in real-time environments. We are going to perform a detailed survey on integration of WSNs with cloud computing and its infrastructural approaches in this research paper.

S ocioeconomic progress of a country is highly de- pendent on energy which is a major determinant of quality of life and living standard.Therefore, it is important to find energy consumption pattern of a country while determining its economic development (Mirza et al., 2008).It is therefore, important to increase scale of energy production keeping in view that greater proportion of the power production comes Abstract | Extensive use of conventional energy sources with negative impacts and existing poor farming systems in Pakistan have driven implementation of biogas technology by governmental and non-governmental organizations.This study focuses on the rate of successful adoption of bio gas technology and its multiple impacts on 113 farming households in two purposively selected districts of Khyber Pakhtunkhwa province (i.e.district Mardan and Dera Ismail Khan).Based on the descriptive nature of the study, quantitative approach was used with the help of a predesigned questionnaire.Frequency distributions, percentages, and paired T-tests were used to analyze and present the data.Results indicate that time spent on cooking and fuel collection significantly reduced after biogas adoption; and it also generates opportunity of alternative activities in saved time, and enhances fuel energy consumption pattern.Biogas technology brings improvement in the economic condition in terms of reduced expenditure (on buying other fuel energy materials and on buying chemical fertilizers), and in terms of higher earnings from selling trees.In light of the findings from this research, biogas technology has been proved to have great potential to improve the quality of life of farming households which in turn would positively affect the agriculture sector.

Syed Faisal ur Rahman examines some puzzling questions about the accelerating expansion of the universe and looks forward to the data to come from radio continuum surveys and standard sirens.

In the present world, wireless communication is becoming immensely popular for plethora of applications. Technology has been advancing at an accelerated rate leading to make communication reliable. Still, there are issues need to be address to minimize errors in the transmission. This research study expounds on the rapid convergence of the signal. Convergence is considered to be an important aspect in wireless communication. For rapid convergence, two ambiguities should be addressed; Eigenvalue spread and sparse identification or sparsity of the signal. Eigen value spread is defining as the ratio of minimum to maximum Eigenvalue, whereas sparsity is defining as the loosely bounded system. In this research, two of these attributes are investigated for MAA (Multi-Array Antenna) signal using the cascading of Wavelet and Krylov processes. Specifically, the MAA signal is applied in the research because nowadays there are many physical hindrances in the communication path. These hurdles weaken the signal strength which in turn effects the quality of the reception. WT (Wavelet Transform) is used to address the Eigenvalue problem and the Krylov sequence is used to attempt the sparse identification of the MAA signal. The results show that the convergence of the MMA signal is improved by applying Wavelet transform and Krylov Subspace.