ARTIFICIAL INTELLIGENCE AND NATIONAL SECURITY

It has been more than sixty years since the concept of Artificial Intelligence (AI) took its initial form. Since then there have been several discussions and debates on AI and its future as the focal point. Today, decades down the line; AI is standing at the door highlighting a paradigm shift of its own. The entire trajectory can also be seen because of an optimistic approach towards the future of technologies that carved the recent times, which we are living in. It can be inferred that the day has come when AI has started operating almost all facets of human life. Such a change possesses drastic potential when the perspective of the global south comes into picture. Apart from mundane activities of humankind, another pertinent aspect of contemporary society is that of national security. Every country of the global south is quite proactive when it comes to strengthening its internal security and countries try to ward off hurdles and mitigate them largely through every possible way. Furthermore, in light of the development and increase in the usage of AI, it is worth pondering on the future of AI in the domain of national security with perspective of the entire domain of the global south. Indeed every concerned government entities like the military of such nations are focusing more on AI based technologies with an objective to enhance their overall capabilities. For instance, the facets of surveillance, cyber security, and venturing towards autonomous equipment are some key areas where nations are focusing on and AI has seen an appropriate enabler towards such cause. Through this review paper, an analytical discussion has been made towards the fact that how the postulate of AI can be used to analyze large stock of data, evaluate the connected patterns, and detect potential security threats. This paper narrows down the discussion to the perspective of the global southern part of the world and analyses the entire situation of AI and its prospective future in the realm of cyber security and national security of the connected nations. The discussion also considered the existence of several concerns with regard to the congruence of AI and national security. By reviewing various existing literature, it projects a discussion and analyzes various pertinent aspect connected to this domain. Eventually, it makes an attempt to put forward suggestions to the question at hand as to whether AI in national security can be seen as a facilitator that can help in strengthening the nation’s internal security or are we overlooking a hurdle that it may entail and is still a far sighted dream.

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Synthesis and characterization of acetylferrocenyl thiosemicarbazone derivatives of dichlorobis(cyclopentadienyl)hafnium(IV)

1421-1423The reactions of Cp2HfCl2 with thiosemicarbazones (LH) derived from acetylferrocene and substituted thiosemicarbazide (phenyl/4-chlorophenyl/4-ni tropheny1/4-methylphenyl thiosemicarbazide) in various stoichiometric ratios have been studied and the complexes of the type [Cp2HfCl(L)] are obtained. Tentative structural conclusions are drawn for the reaction products based upon elemental analyses, electrical conductance, magnetic moment and spectral data (UV -Vis, IR, 1H NMR and 13C NMR)

Soil Microbes Expertly Balancing Nutrient Demands and Environmental Preservation and Ensuring the Delicate Stability of Our Ecosystems- A Review

It scrutinizes the critical role of soil microbes in balancing nutrient demands and environmental preservation, thereby ensuring the stability of our ecosystems. The document elucidates how these microscopic organisms play a pivotal role in various ecosystem processes such as nutrient cycling, organic matter decomposition, and the promotion of plant health. It details how their metabolic processes influence soil fertility and plant growth, maintaining a fine equilibrium between the soil's nutrient demand and environmental conservation. The review stresses the influence of microbes on soil health and their potential role in mitigating climate change through carbon sequestration, demonstrating their significance beyond primary production. The correlation between microbial communities, climate change, and soil degradation is emphasized, showing how these factors interact in a complex, interconnected network. Modern microbial management strategies, highlighting sustainable methods to exploit their potential in agriculture and environmental conservation. It advocates for more research into soil microbiome functionality, with a special focus on the impact of human activities and climate change. By emphasizing that soil microbes, although invisible, carry profound implications for global sustainability and food security. By optimizing microbial functions, we can improve soil health and fertility, contributing significantly to ecosystem resilience and stability

Multilevel modelling and rendering of architectural scenes

We present a novel approach for multilevel modelling and rendering of architectural scenes using a small set of photographs. Our approach is based on interactive probing of intuitive measures like lengths, widths and heights from single view metrology. These measures can then be aggregated with additional input if need be, for defining high-level primitives such as planes, prismatic blocks, cuboids, spheres, and general surfaces of translation and revolution. The modelling approach is modular and incremental which enables ease and flexibility in building large architectural scenes. Further, our approach allows multilevel modelling and rendering. That is, the model can be enhanced/reduced both in terms of changing details at the primitive level and at the model level. This requires inter-registration of two or more images with common contents. Our approach is computationally simple, fast and robust. We demonstrate our results by building a model of a magnificent historical monument in Delhi-Humayun’s tomb

Impact Propagation in Airport Systems

The effective protection of critical infrastructure against cyber and physical security threats involves many different steps from initially the identification of risks to finally the implementation of counter measures in the infrastructure. To derive counter measures and to come to intelligent decisions facing the identified risks, the impact calculation plays a central role. The impact of a specific threat can propagate through the systems of the infrastructure and thus needs to be analysed carefully. In this paper, the role of impact propagation of cyber-physical threats for infrastructure protection is discussed, exemplified for airport systems. In the ongoing EU-H2020 project SATIE (Security of Air Transport Infrastructure of Europe) a toolkit is developed containing two tools for impact propagation, namely the Business Impact Assessment (BIA) and the Impact Propagation Simulation (IPS). Both tools are described and for a small test case the propagation of a cyber threat and the transformation into a physical threat is demonstrated in a network representation as well as an agent-based model of the airport’s systems employing the IPS