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Conclusions summarizing the achievements and indication of scope for future work Around 100 KM which is thrice the committed number of KM have been made.

Some more are under construction and need detailed attention along with data authenticity check by experts. Collaboration with institutes and their utilization on respective platforms like websites has been a big limitation due to lack of any response or action thereof. However, as an outcome, I have also initiated the planning for an academic publication in a coffee table book style.

The technical summary outlines the budget and project plan for Theme coordination project proposals with a combined budget of approximately 9.725 crores. PEC, Chandigarh will be responsible for developing and maintaining a web-based tracking system for project progress and combining reports and indicators. To facilitate this, the budget includes funding for research staff who will develop the database, and secure web applications for tracking progress.

A travel budget of is allocated for cluster heads, project engineers, and DST representatives to travel to project sites and for necessary meetings. Additionally, equipment expenses at PEC, Chandigarh include a dedicated server and two desktops for running the website and web applications.

The budget also accommodates yearly review workshops and an ICPS Security conference which includes transportation, accommodation, meals, and inviting industry and academic experts to give keynote talks. A panel of experts is also brought in to evaluate the progress of the Theme coordination project proposals projects

The research project aims to address various terrorist activities, such as cyber recruitment and illegal procurement of modern weapons for potential mass attacks. The primary focus is on designing and developing a framework capable of extracting actionable intelligence related to terrorist activities from diverse sources, including emails, physical devices, news items, online media, social media, blogs, and formal sources. The ultimate goal is to enhance national security by predicting potential threats and taking corrective action through the analysis of criminals/terrorists' behavioral models.

The project emphasizes the efficient use of free and open-source tools available in the market to extract the most accurate and relevant information for national interests. It also aims to design a system that can predict terror attacks and perform perception management for national security agencies, providing clear indications of whether citizens should be alerted. Threats will be classified into five levels: Not Expected, Possible, Probable, Expected, and Certain.

An essential aspect of the research is to detect and classify "Radical/Anti National" or "Extremist" online social content based on specific criteria, such as religious or political motivation, unethical provocation, racism, and more. This will help identify and tag sources spreading anti-national ideologies as "Radical."

Another significant component of the research involves conducting a comprehensive study of terrorist groups operating in India. The aim is to detect malicious users, including those involved in child pornographic content, fake accounts, and followers market activities. A model will be developed to assign Trust Scores and assess online social network users.

The proposed framework will utilize probabilistic modeling techniques, machine learning approaches, and big data analytics methodologies employed by organizations like NSA, Google, and Amazon. These techniques will be used to model behaviors and maintain public welfare through surveillance or make predictions about users/customers of web services.

The anticipated outcomes of the project are twofold. Firstly, the framework's practical application will enable the prediction of potential threats to national security, facilitating timely corrective actions through the analysis of criminals/terrorists' behavioral patterns. Secondly, the system will include a predictive terror attack engine to aid national security agencies in making informed decisions about citizen alerts and alarms. Additionally, an Automated Perception Management and Influence Maximization System will be developed using machine learning and deep learning techniques, along with mobile applications employing sensors to propagate "Perceptions" and enhance influence on individuals through a chat-bot.

In conclusion, the research project seeks to contribute significantly to national security efforts by utilizing advanced technologies to detect and mitigate potential terrorist activities. By extracting actionable intelligence from various sources and employing sophisticated modeling techniques, the project aims to enhance threat prediction and perception management for the benefit of society and the nation at large.

The world is moving at a fast pace towards the renewable energy sources, especially solar power, which is abundantly available all over the world. The solar power can be used for generation of electrical energy either by solar PV or by solar thermal. Generation through solar PV is most promising as it can be used for generation of power as low as few watts to several MWs. But to convert from solar PV to ac, we need an inverter. Multilevel Inverter (MLI) is more recent and popular type of power electronic converter that synthesizes a desired output voltage from several levels of dc voltage as inputs. If sufficient number of dc sources are used, a nearly sinusoidal voltage waveform can be obtained. As compared to hard-switched two-level PWM inverter, multilevel inverter offers several advantages such as, ability to operate at higher voltage with lower dv/dt per switching, high efficiency and low electromagnetic interference etc. Nowadays, newer MLI topologies are emerging with reduced switch and driver count for reduction of switching devices without affecting the performance of inverter and reducing its cost and increasing its efficiency.

The main objective of this project is to develop an interface between solar PV and load, utilising Hybrid Multilevel Inverter (MLI) and P&O MPPT for standalone PV system with Selective Harmonic Elimination (SHE) for efficient and power quality grid code compliant inverter output.

The desire objectives have been achieved by following steps:

• Development of 15-level hybrid multilevel inverter with reduced switch count and control circuit.
• Minimization of harmonic contents in the voltage/current produced by the inverter. The equations representing the different harmonic components will be solved using Selective Harmonic Elimination (SHE) or Optimization Techniques for minimization/ elimination of harmonic components in the output line/ phase voltage/ current.
• Integration of PV array and P & O MPPT with battery to design a rigid DC voltage source.
• Integration and stabilization of developed voltage sources with hybrid MLI circuit.

The simulation results for 15-level multilevel inverters for equal values of DC sources have been verified through experimental results.