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M.Tech. (Computational and Data Science)

Get all the information you need about the M.Tech. (Computational and Data Science) course structure, duration, core courses, soft core courses, dissertation, and electives.

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Universal Two-Qubit Computational Register for Trapped Ion Quantum Processors

Universal two-qubit computational register for trapped ion quantum processors, including state preparation, gates, and benchmarking. The experimental setup and results are discussed.

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Computational Physics (Lecture 18)

The basic structure of MPICH and its features in Computational Physics Lecture 18. Understand how MPI functions are used and linked with a static library provided by the software package. Explore how P4 offers functionality and supports parallel computer systems. Discover the concept of clusters in

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Cryptographic Reductions and Learning in Computational Complexity

This lecture explores the connection between computational complexity and cryptography, focusing on topics like pseudorandom functions, public-key cryptography, and learning from Gaussians. It delves into the implications of cryptographic reductions, lower bounds for learning MLPs, and the existence

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Understanding Signed Integers and Addition in Computational Systems

Dive into the world of signed integers, extensions, truncations, and addition in computer science with a focus on how negative values are represented and operated on. Explore concepts like sign-magnitude and two's complement representations, uncovering the intricacies of handling integers in computa

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OBPMark and OBPMark-ML: Computational Benchmarks for Space Applications

OBPMark and OBPMark-ML are computational benchmarks developed by ESA and BSC/UPC for on-board data processing and machine learning in space applications. These benchmarks aim to standardize performance comparison across different processing devices, identify key parameters, and provide recommendatio

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Computational thinking as 21st Century skill

Computational thinking is a critical skill for the digital age, involving problem-solving techniques that enable computers to process information effectively. It precedes programming and requires breaking down complex problems into manageable steps. Educators emphasize computational thinking exercis

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Computational Geometry.

Voronoi diagrams, a key concept in computational geometry, involve partitioning a space based on points sites. They have diverse applications like nearest neighbor queries and facility location. The diagrams consist of Voronoi cells, edges, and vertices, forming a connected graph. Properties include

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Understanding Natural Resources and Resource Economics

Economics of natural resources focuses on the supply, demand, and sustainable allocation of the Earth's resources. It aims to develop a sustainable economy that protects natural resources for future generations. Natural resources are essential for human survival and include biotic and abiotic resour

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Master's Program in Computational Drug Discovery and Development - Fall 2024 Curriculum

This Master's program offers a comprehensive curriculum focusing on Artificial Intelligence, Computational Drug Discovery, and Development. With a blend of cutting-edge technologies and practical applications, students delve into techniques, AI/ML, big data mining, modeling, and more. Through intens

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Understanding Computational Linguistics and Natural Language Processing

Explore the fascinating fields of Computational Linguistics and Natural Language Processing (NLP), delving into their development, applications, and significance. Learn about the study of human languages in computational models, the importance of corpora in linguistic research, and the various types

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Understanding the Importance of Pattern Recognition in Computational Thinking

Pattern recognition is a vital skill in computational thinking, enabling the identification of similarities and differences between concepts and objects. By recognizing patterns, individuals can efficiently solve complex problems, create shortcuts, and avoid duplications in problem-solving processes

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Engaging Paper-Based Problem Solving for Computational Thinking Skills

Implementing paper-based problem-solving activities using puzzles, riddles, and pattern recognition can effectively introduce computational thinking without the need for complex technology or terminology. Through real-life scenarios like transporting a fox, chicken, and corn across a river or encodi

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Insights on Computational Complexity Threshold Results

Exploring the challenges in proving major lower bounds for computational complexity, focusing on the Hardness Magnification and Minimum Circuit Size Problem (MCSP). Discusses the difficulties in proving weak and strong LBs, highlighting recent theorems and barriers that impact progress in the field.

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Recent Advances in Computational Doppler Radar Data Modeling

Explore the latest developments in computational modeling of Doppler radar data, focusing on error estimation, dual vs. single pol radars comparison, uncertainty quantification, and methodology for analyzing Doppler radar predictions against gauge measurements. The study involves data from multiple

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Understanding High Dynamic Range Sensors in Computational Photography

Dive into the world of High Dynamic Range (HDR) sensors in computational photography with topics covering sensor architectures, CMOS sensing techniques, dynamic range evaluation, and basic concepts related to image sensors and pixel integrators. Explore the importance of dynamic range in capturing a

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Computational Photography: Texture Synthesis and Hole-Filling Overview

Delve into the world of texture synthesis and hole-filling in computational photography, exploring the challenges, goals, and techniques involved in creating new textures and filling in image gaps. Learn about building probability distributions, modeling textures, and the intricacies of synthesizing

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Image-Based Lighting in Computational Photography

Explore the techniques and concepts of image-based lighting in computational photography through slides covering topics such as rendering objects in images, using environment maps and light probes, mirrored spheres, and dealing with light sources like the sun. Learn about capturing and utilizing lig

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Computational Thinking, Algorithms & Programming Overview

This unit covers key concepts in computational thinking, including decomposition, abstraction, and algorithmic thinking. Decomposition involves breaking down complex problems, abstraction focuses on identifying essential elements, and algorithmic thinking is about defining clear instructions to solv

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Introducing MatFlow: Open-source Python Tool for Computational Materials Science

MatFlow is an open-source Python code designed for computational materials science, running on HPC systems like CSF at Manchester. Users specify tasks to run in a workflow, with the main output being a workflow HDF5 file. The tool aims to make reproducibility and transparency easier, connect dispara

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Efficient Solver Techniques in CFD Simulations

This resource provides insights into the segregated solver approach in computational fluid dynamics (CFD) simulations, specifically focusing on the sweeping direction and its impact on computational efficiency and convergence rates. It discusses the benefits of employing the XY plane for 2D cases to

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Exploring Complexity in Computational Theory

Dive into a world of computational complexity and theory with a focus on topics such as NP, P, PH, PSPACE, NL, L, random vs. deterministic algorithms, and the interplay of time and space complexity. Discover insights on lower bounds, randomness, expanders, noise removal, and the intriguing question

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Exploring Computational Techniques with NLTK for Linguists

Dive into the world of computational techniques for linguists with NLTK in Lecture 24. Learn about list comprehensions, conditional forms, tokenization, part-of-speech tagging, parsing, chunking, concordance, similarity, common contexts, dispersion plots, and more. Discover where NLTK is installed o

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Understanding Computational Complexity Through Statistical Physics

In the age of vast data growth, tackling complex computational problems is crucial. Statistical physics can provide insights into handling the new challenges arising from the exponential increase in data. As we delve into understanding the complexity of computational tasks, it becomes evident that e

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Understanding Convex Hulls in Computational Geometry

Convex hulls are a fundamental concept in computational geometry, representing the smallest convex shape that contains a set of points. The process involves defining the convexity of a set, determining the unique convex polygon, and computing the convex hull efficiently using algorithms. This conten

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Understanding Minimum Edit Distance in Computational Biology

Dan Jurafsky explains the concept of minimum edit distance as the minimum number of editing operations such as insertion, deletion, and substitution needed to transform one string into another. Through examples and visual representations, he illustrates how minimum edit distance plays a crucial role

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Introduction to Priority Search Trees in Computational Geometry

This lecture outlines the structure and query process of Priority Search Trees (PST) in computational geometry. It covers heap-based point queries, range trees for windowing queries, handling query ranges in 1D and 2D spaces, and using heaps to efficiently handle query ranges. The content discusses

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Explore the World of Computational Linguistics: An Interactive Journey

Embark on a captivating interactive journey into the realm of computational linguistics through a series of engaging activities and challenges. Discover how machines process texts, decode mysterious languages, understand Japanese with data structures, and more. Test your skills in deciphering langua

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Actively Secure Arithmetic Computation and VOLE Study

Exploring actively secure arithmetic computation and VOLE with constant computational overhead at Tel Aviv University. Understanding how functions are represented in secure computation using arithmetic circuits over boolean circuits. Efficiently evaluating arithmetic circuits over large finite field

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Computational Complexity and NP-Complete Problems

In today's discussion, we delved into computational complexity and the challenges faced in finding efficient algorithms for various problems. We explored how some problems defy easy categorization and resist polynomial-time solutions. The concept of NP-complete problems was also introduced, highligh

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Ladner's Theorem in Computational Complexity Theory

Ladner's Theorem is a significant result in computational complexity theory that deals with NP-intermediate problems, which are languages in NP neither in P nor NP-complete. The theorem states that if P is not equal to NP, then there must exist an NP-intermediate language. The proof involves a delic

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Understanding the Key Articles of the Nagoya Protocol on Access to Genetic Resources and Benefit-Sharing

The Nagoya Protocol aims to promote fair sharing of benefits from genetic resources utilization for conservation efforts. It encompasses access, technology transfer, funding, and respect for rights over resources and technologies. The protocol applies to genetic resources, traditional knowledge, and

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Advances in Aviation Fuel Surrogates and Computational Modeling

This study explores the formulation of petroleum and alternative jet fuel surrogates, coupling chemical kinetics with computational fluid mechanics for engine design, and the variability of aviation fuels. It delves into the concept of surrogate fuel models, previous research on jet fuel surrogates,

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Understanding Levels of Object Recognition in Computational Models

Explore the levels of object recognition in computational models, from single-object recognition to recognizing local configurations. Discover how minimizing variability aids in interpreting complex scenes and the challenges faced by deep neural networks in achieving human-level recognition on minim

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Understanding Computational Geometry: Triangulations and Art Gallery Guarding

Explore the concepts of triangulations and guarding art galleries in computational geometry. Learn about the problem of placing cameras or guards strategically in an art gallery to ensure every point is visible. Discover how polygons are defined, the variations in guarding strategies, and the use of

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Investigating Computational Intelligence: Reading What Machines Think at University of Rome Tor Vergata

Researchers at University of Rome Tor Vergata are delving into the intriguing realm of understanding and predicting human brain activity by observing cognitive tasks using computational machines. Their motivation lies in bridging the complexity of computers with the mysteries of the human brain, aim

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Advancing Computational Modeling for National Security and Climate Missions

Irina Tezaur leads the Quantitative Modeling & Analysis Department, focusing on computational modeling and simulation of complex multi-scale, multi-physics problems. Her work benefits DOE nuclear weapons, national security, and climate missions. By employing innovative techniques like model order re

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Insights into Computational Complexity Hierarchy and SAT Algorithms

The computational complexity hierarchy explores classes of problems like EXP-complete, PSPACE-complete, and more. SAT algorithms, such as local search methods and survey propagation, offer new insights into practical complexity. Discover the interplay between tractable and intractable structures in

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Unlocking Synergistic Opportunities in Computational Resources and IT

Explore the evolving relationship dynamics between computational resource providers and local IT organizations. Break the traditional perceptions and foster collaboration through early engagement in grants, innovative deployments, and shared ownership. Embrace new technologies and stakeholder involv

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Understanding Decision Problems in Polynomial Time Complexity

Decision problems play a crucial role in computational complexity theory, especially in the context of P and NP classes. These problems involve questions with yes or no answers, where the input describes specific instances. By focusing on polynomial-time algorithms, we explore the distinction betwee

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