Non-Contact Warfare: Lessons from the US National Defence Strategy

The 2018 National Defence Strategy (NDS) unveiled by the Pentagon can be encapsulated in three words ‘compete, deter and win’. Keyquestions that arise are: What does it mean and how it gets manifested? NDS as the capstone document has been guiding the geopolitical discourse and global security developments. The Pentagon’s efforts to redraw its dominance strategy and course correct its two decades of distraction due to endless wars in Afghanistan and West Asia have already manifested in Sino-US relations. A decade of ‘pivot to Asia’ policy put in place by Obama’s administration gathered storm during Trump’s tenure. 2018 NDS declared China and Russia as strategic competitors. Washington’s assertion of widening the competitive space is based on the premise of seamlessly integrating the US “multiple elements of national power—diplomacy, information, economics, finance, intelligence, law enforcement, and military”. A closer examination of how the game gets played by the various national power elements under the new Biden administration will determine future policy directions against China and Russia. The lessons for India are ominous as it helps it to navigate the geo-strategic labyrinth

Comparative Analysis of Daily Flow Pattern Hydrographs Used to Disaggregate Monthly Naturalized Flows to Daily

Observed and synthesized sequences of stream flow data are explored from the perspective of improving capabilities for disaggregating monthly naturalized flow volumes, representing natural undeveloped conditions, to daily volumes. The research investigates 1) characteristics of river flows and impacts of water resources development on flows, 2) capabilities for disaggregating monthly naturalized flows to daily, and 3) the sensitivity of water availability modeling results to the daily flow pattern hydrographs adopted in monthly-to-daily naturalized flow disaggregation. The Texas Commission on Environmental Quality (TCEQ) Water Availability Modeling (WAM) System consists of the Water Rights Analyses Package (WRAP) and input datasets for all the river basins of Texas. TCEQ sponsored research at Texas A&M University over the past several years has included development of a daily version of the monthly WRAP/WAM modeling system. The thesis research focuses on improving capabilities for developing daily pattern hydrographs for use in disaggregating monthly WAM naturalized flow sequences to daily within the daily WRAP modeling system. Comparative statistical analyses are performed for observed and synthesized river flows at numerous gage sites in the Brazos, Trinity, Neches, and Sabine River Basins. The datasets of monthly and daily flows investigated in the thesis include observed flows at U.S. Geological Survey (USGS) gages, TCEQ WAM System naturalized flows, unregulated flows from a U.S. Army Corps of Engineers (USACE) reservoir operations modeling system, and flows generated with the Soil and Water Assessment Tool (SWAT) and Hydrologic and Water Quality System (HAWQS) watershed rainfall-runoff modeling systems. Daily WRAP simulations of the four case study river basins for a 1940-2015 hydrologic period-of-analysis are performed with alternative flow disaggregation schemes. The USACE Hydrologic Engineering Center (HEC) Data Storage System (DSS) and HEC-DSSVue are employed in the compilation and comparative analyses of datasets. Stream flow throughout Texas is extremely variable temporally with the extremes of floods and droughts as well as seasonal and continuous variability. The impacts of water resources development on river flows vary greatly between different locations. Impacts of upstream development are very different across the range of low to median to high flows. The HEC-DSSVue based approach for compiling, analyzing, comparing, selecting, and combining datasets significantly enhances the WRAP/WAM modeling system

Low-cost and Reliable Integrated Hardware and Software Framework for Remotely Operated Water Release from Storage Units

The main contribution of this research is towards the broader area of water management that can be used for multiple purposes. For instance, floods can be mitigated using a novel approach based on the integrated dynamic management of water storage units such as reservoirs, wetlands, and ponds. This approach will enable adaptive water release from storage units hours or days ahead of rainfall events, thereby maximizing storage capacity and minimizing flooding. This approach can be implemented by retrofitting water storage units using siphon hydraulic systems and are remotely controlled in an integrated manner using the decision support system. To make it feasible in a relatively inexpensive way, this dissertation developed a modular, scalable, and integrated hardware-software platform for interfacing automated siphons/gates, sensors, and sensor control/communication to enable remote operation of hundreds and thousands of gates in storage units. In this study, a siphon hydraulic system was developed and used to implement and test the hardware and software integrated control system. The hardware architecture includes water level sensors, bilge pump, air-vent, and actuated butterfly valve. The software architecture is designed and developed in C-sharp language and displays near real-time data from the sensors employed in the lab. It also displays the functioning or malfunctioning condition of all digital and analogic lab hardware. The latter can be used to schedule maintenance operations without visiting the lab. Various cutting-edge technologies such as the Internet of Things (IoT), Software Defined Radios (SDR), and Virtual Private Network (VPN) is employed to integrate the hardware and software architecture. All the data collection and operations are performed remotely using 4G/5G cellular communication. Extensive experiments were performed in the lab, and the results indicate that the systems are reliable. Reliability is defined as the probability that the system will perform its intended function adequately without failure. The operational reliability of sensors and other field hardware, such as liquid level sensors, bilge pumps, and air vents, has been analyzed using the Reliability Block Diagram (RBD) using the ExtendSim software. In this method, the components of the system are linked through graphic blocks following their functional logic or operational relationship. The results of the operational reliability of the system are obtained through Monte Carlo simulations. The cost analysis is also performed for several scenarios based on redundancy, maintenance cost, and the components\u27 life span

Non-Contact Warfare: A Strategy for Future

Examining events after World War II shows that the emerging technological environment is shaping the future. The shift in operational doctrine from ‘massing of forces’ to ‘massing of effects’ with a quantum reduction in physical contact between adversarial forces has been scripted. Future conflict trends are likely to be diffused, diverse and disruptive. Expanding security-arena from traditional to non-traditional domains necessitates a nuanced doctrinal approach. The escalation levers are looking at non-military and military means of contestation.   &nbsp

Non-Contact Warfare: A Strategy for Future

Examining events after World War II shows that the emerging technological environment is shaping the future. The shift in operational doctrine from ‘massing of forces’ to ‘massing of effects’ with a quantum reduction in physical contact between adversarial forces has been scripted. Future conflict trends are likely to be diffused, diverse and disruptive. Expanding security-arena from traditional to non-traditional domains necessitates a nuanced doctrinal approach. The escalation levers are looking at non-military and military means of contestation.   &nbsp

Countering the Contagion Effect of COVID-19: An Appraisal of China's Influence Operations

For China to realise its millennium goal, it needs to radiate its influence globally and simultaneously engage internally with the local population to ensure social stability. COVID-19 has disrupted China's dream of showcasing to the world a model state with Chinese characteristics. Influence operations thus form the basis of curating and presenting a credible image of the Communist Party of China (CPC) besides altering the behaviour of its adversaries. China has tried to firewall the western influence besides making inroads into other countries' economic, political, and societal institutions. At the time of the COVID-19 crisis, it is employing leverages to correct the narrative while gaining situational awareness through revamped structures and employment of technologies. It is thus imperative to appraise China's influence operations capabilities

Data Classifier for Encryption in Cloud

The aim of this project is to provide the cloud security infrastructure with a security policy such that the data encryption takes place as per need of data and provide suitable security to data based on the security needs of data with resource optimization in mind, as most of the data stored in cloud database would not be a classier document. Some of, or a high percentage of, data must be no encryption required-data. A model is needed which would not only classify the data but also handle the security concerns of data according to class which could be based on any security parameter, security criteria, or a set of conditions which are to be decided in accordance with the cloud service provider .On the basis of these predefined security criteria classes are formed and eventually various types of policies can be applied to the classes for which the cloud service provider agrees and is capable of. The data have different values and characteristics that must be identified before sending to cloud severs. As per the literature review so far the model present is a combination of K-Nearest Neighbor (K-NN) classifier and the Rivest, Shamir and Adelman (RSA) algorithm ,where data is classi?ed into sensitive and non sensitive data ,only the sensitive data is encrypted using RSA algorithm. In a cloud server, the data are stored in two ways. First encrypt the received data and store on cloud servers. Second store data on the cloud servers without encryption. As the literature states, after implementing this model it is found that the confidentiality level of data is increased and this model is proved to be more cost and memory friendly for the users as well as for the cloud services providers. This classi?cation technique uses binary number of class. The sensitivity of data can vary from more than just two levels. The data can grow two large to handle by K-NN and better technique exists to handle large data sets. For encryption any outsource algorithm would do more appropriate for cloud environment. This project proposes a model with more number of target classes which can handle the sensitivity of data more precisely and satisfy the need of security architecture. The model uses decision tree induction algorithm for classifier and the encryption algorithm can be used in varieties with a single class with no encryption. The classified data is then loaded into the servers into different data centres. The model aims at classi?cation of data on basis of various security parameter or cloud policies

A case report on Duchene muscular dystrophy in an Indian family

Duchenne muscular dystrophy (DMD) is commonest X-linked syndrome muscular dystrophy in the children, present in early childhood and characterized by the proximal muscle weakness and the calf hypertrophy in exaggerated boys. There is generally delay in the motor development and ultimately wheelchair confinement leading to premature death from cardiac or the respiratory complications. For treatment we use various modalities like corticosteroid therapy. We also used intermittent positive pressure ventilation that could help in developments in function, quality of life, ambulation and life expectancy though novel therapies still focus to provide the cure for this disease. Clinically, it is categorized by the progressive muscle wasting ultimately leading to the premature death. Here we presented a case of Duchene muscular dystrophy in a 13 year old boy with clinical presentation