| Subrahmanyam Kalyanasundaram |
IIT HYDERABAD |
CSE |
Theoretical Computer Science, Complexity Theory, Combinatorics and Graph Algorithms |
|
| Antony Franklin |
IIT HYDERABAD |
CSE |
Wireless Networks, Mobile Networks,5G Network and Systems, Low Latency transport protocol |
|
| Bheemarjuna Reddy Tamma |
IIT HYDERABAD |
CSE |
Converged Radio Access Technologies,SDN/NFV for 5G,M2M/IoT,Mobile Social Networks in Proximity,Green ICT and Network Security |
|
| Fahad Panolan |
IIT HYDERABAD |
CSE |
Parameterized Algorithms and Complexity, Approximation Algorithms, and Graph Theory |
|
| j. saketha nath |
IIT HYDERABAD |
CSE |
Machine Learning |
|
| Jyoti Vedurada |
IIT HYDERABAD |
CSE |
Program Analysis, Program Understanding, Automated Concurrency Testing, and High-Performance Computing. |
|
| Karteek Sreenivasaiah |
IIT HYDERABAD |
CSE |
Theoretical Computer Science, Computational Complexity |
|
| Kotaro Kataoka |
IIT HYDERABAD |
CSE |
Internet over Broadcast Media, Ipv6 Multicast, Post-Disaster Networking |
|
| M. V. Panduranga Rao |
IIT HYDERABAD |
CSE |
Theoretical Computer Science |
|
| Manish Singh |
IIT HYDERABAD |
CSE |
Databases, Data Mining, HCI, Information Retrieval, Information Visualization |
|
| Manohar Kaul |
IIT HYDERABAD |
CSE |
Applied Algebraic Topology, Topological Analysis Data, Machine Learning, and Spatial Databases |
|
| Maria Francis |
IIT HYDERABAD |
CSE |
Computational Algebra, Symbolic Computation, Lattice Cryptography |
|
| Maunendra Sankar Desarkar |
IIT HYDERABAD |
CSE |
Recommender Systems, Information Retrieval, Machine Learning, Data Mining |
|
| N.R.Aravind |
IIT HYDERABAD |
CSE |
Graph Theory, Combinatorics and Algorithms |
|
| Praveen |
IIT HYDERABAD |
CSE |
Systems and Networking, Network Security, Software-Defined Networking, ML for Networks |
|
| Ramakrishna Upadrasta (U.Ramakrishna) |
IIT HYDERABAD |
CSE |
Programming Languages, Compiler Optimizations, Parallelizing Compilers, Program Optimizations, Static Analysis, Verification, Algorithms, Combinatorial Optimization, Theory of Algorithms |
|
| Rogers Mathew |
IIT HYDERABAD |
CSE |
Combinatorics, Graph Theory, and Graph Algorithms. |
|
| Sathya Peri |
IIT HYDERABAD |
CSE |
Parallel Programming, Software Transactional Memory, Distributed Systems, Theory of Databases, Algorithm Analysis, Networking Algorithms |
|
| Saurabh Joshi |
IIT HYDERABAD |
CSE |
Program Analysis, Formal Methods, Verification, Concurrency, Constraint Solving |
|
| Sobhan Babu |
IIT HYDERABAD |
CSE |
Big Data Analytics, Graph Theory and Applied Algorithms |
|
| P. K. Srijith |
IIT HYDERABAD |
CSE |
Bayesian Data Analysis, Probabilistic Machine Learning, Bayesian Non-Parametrics, Survival Analysis and Text Analytics |
|
| Vineeth N Balasubramanian |
IIT HYDERABAD |
CSE |
Machine Learning |
|
| GAYATHRI ANANTHANARAYANAN |
IIT DHARWAD |
CSE |
Computer architecture and embedded systems, with specific focus on Power, Thermal and Performance modeling, characterization and management. |
|
| Kedar Khandeparkar |
IIT DHARWAD |
CSE |
Cyber Physical Systems, Data Science and Cyber Security in Smart Grids, Applied Machine Learning |
|
| Koteswararao Kondepu |
IIT DHARWAD |
CSE |
N/A |
|
| Nikhil Hegde |
IIT DHARWAD |
CSE |
Parallel and Distributed computing, and Programming Languages |
|
| Prabuchandran K.J. |
IIT DHARWAD |
CSE |
N/A |
|
| Rajshekar K |
IIT DHARWAD |
CSE |
Computer architecture, hardware reliability, hardware security, accountability issues in heterogeneous 3PIP-containing SOCs, and microarchitectural simulation. |
|
| Ramchandra Phawade |
IIT DHARWAD |
CSE |
Concurrency, Automata Theory and Logic in Computer Science |
|
| Sandeep R. B. |
IIT DHARWAD |
CSE |
Graph Theory and Algorithms |
|
| Siba Narayan |
IIT DHARWAD |
CSE |
Efficient radio resource and device discovery algorithms for enabling Device-to-Device Communications in LTE-A Networks. |
|
| Tamal Das |
IIT DHARWAD |
CSE |
Software defined networking ,Data center network architectures,Network function virtualization,Network Migration,High-speed networks |
|
| Dharmendra Singh |
IIT ROORKEE |
CSE |
Radar,MW/MMW/THzImaging, AI, ML/DL, IoT, Cloud Based Solution, DRONE Applications, Image Processing, ICT, Microwave and Optical Remote Sensing, Radar Polarimetry and Interferometry,Stealth Technology, Electromagnetic |
|
| Durga Toshniwal |
IIT ROORKEE |
CSE |
Data Mining and Big Data, Artificial Intelligence, and Machine Learning, Time Series Data Mining, Privacy Preserving Data Mining, Anomaly detection, Data Stream mining, Data Mining and Big Data, Artificial Intelligence, and Machine Learning, |
|
| Manoj Mishra |
IIT ROORKEE |
CSE |
Distributed Computing, Information and Network Security |
|
| Neetesh Kumar |
IIT ROORKEE |
CSE |
High Performance Computing:, Parallel Computing, Cloud/Fog/Edge Computing, Evolutionary Computing:, Soft Computing, Nature Inspired Computing, Wireless Sensors Network (WSN):, |
|
| Peddoju Sateesh Kumar |
IIT ROORKEE |
CSE |
Pervasive Computing, Internet of Things (IoT), Sensor Networks, Edge/Fog Computing, Cyber Security, Mobile Security, IoT Security, Cloud Security, Network Security, etc. |
|
| Pradumn K. Pandey |
IIT ROORKEE |
CSE |
Complex Networks and Diffusion Dynamics, Modeling of complex networks and diffusion processes on networks, Network Representation Learning, Vector embedding over networks , Network Decomposition , Community detection |
|
| Pravendra Singh |
IIT ROORKEE |
CSE |
Model Compression, Few-Shot Learning, Zero-Shot Learning, Continual Learning, Deep Learning, Machine Learning, Computer Vision |
|
| R. Balasubramanian |
IIT ROORKEE |
CSE |
Computer Vision- Optical Flow and Video Analytics, Fractional Transform Theory, Wavelet Analysis, Multimedia Security: Encrypted Domain Processing of Big Multimedia Data over Cloud, Biometrics, Content Based Video |
|
| Rahul Thakur |
IIT ROORKEE |
CSE |
Wireless Communication, Cellular Networks, Internet of Things(IoT), Vehicular Networks, Femtocell Resource Allocation and Cell Selection |
|
| Rajdeep Niyogi |
IIT ROORKEE |
CSE |
Automated Planning, Formal Methods, Web services Composition, Cybersecurity, Distributed Systems, Bioinformatics |
|
| Raksha Sharma |
IIT ROORKEE |
CSE |
Natural Language Processing, Applicaiton of Machine Learning, Artificial Intelligence |
|
| Sandeep Kumar Garg |
IIT ROORKEE |
CSE |
Software Engineering, Web Services, Machine Learning, Artificial Intelligence, Computer Networks, Data Analytics, Software Project Management, ICT Development |
|
| Sudip Roy |
IIT ROORKEE |
CSE |
Electronic Design Automation and Embedded System Design, Algorithm Design and Optimization Techniques, Microfluidic Biochips, CAD for VLSI, Cyber-Physical and IoT-based System Design, ICT for Disaster Management, Applications of Machine Learning |
|
| Sugata Gangopadhyay |
IIT ROORKEE |
CSE |
Cryptology, Cryptographic Boolean functions; Quantum Computing and Cryptography, Stream Cipher Cryptanalysis. |
|
| Aishwarya Thiruvengadam |
IIT Madras |
CSE |
Cryptography, Security, and Privacy |
|
| Akanksha Agrawal |
IIT Madras |
CSE |
Parameterized Complexity, Computational Geometry |
|
| Anurag Mittal |
IIT Madras |
CSE |
Computer vision, Multi-camera vision systems, Sensor planning, Surveillance, Computer graphics |
|
| Arun Rajkumar |
IIT Madras |
CSE |
Machine Learning, Rank Aggregation, Statistical Learning |
|
| Ayon Chakraborty |
IIT Madras |
CSE |
Mobile systems, Wireless sensing |
|
| B. V. Raghavendra Rao |
IIT Madras |
CSE |
Structural aspects of Arithmetic and Boolean Circuits, Computation on Algebraic and Combinatorial Structures, Combinatorial Commutative |
|
| Balaraman Ravindran |
IIT Madras |
CSE |
Machine learning, Reinforcement learning, Social Network Analysis, Data and text mining |
|
| C. Chandra Sekhar |
IIT Madras |
CSE |
Speech recognition, Neural networks, Kernel methods, Computer architecture |
|
| C. Pandu Rangan |
IIT Madras |
CSE |
Cryptography and Security Protocols, Graph theory, Computational Geometry, Randomized and Parallel Algorithms. |
|
| C. Siva Ram Murthy |
IIT Madras |
CSE |
Ad hoc wireless networks, Parallel and distributed computing, Real-time systems, Computer networks. |
|
| Chester Rebeiro |
IIT Madras |
CSE |
Hardware Security, Operating System Security, Side-channel Analysis, Cryptography |
|
| D. Janakiram |
IIT Madras |
CSE |
Large Scale Distributed Systems, Cloud and Grid Computing, Big Data Systems. |
|
| Deepak Khemani |
IIT Madras |
CSE |
Artifical intelligence, Knowledge-based systems, Case-based reasoning, Knowledge representation, Planning, Logic, Natural language processing |
|
| Deepak Padmanabhan |
IIT Madras |
CSE |
Machine Learning |
|
| Harish Guruprasad |
IIT Madras |
CSE |
Machine Learning, Learning Theory and Optimisation |
|
| Hema A. Murthy |
IIT Madras |
CSE |
Speech Processing, Music information Retrieval. |
|
| Jayalal Sarma |
IIT Madras |
CSE |
Structural & Computational Complexity theory, Circuit Complexity, Lower bounds, Derandomization. |
|
| John Augustine |
IIT Madras |
CSE |
Distributed Algorithms, Optimization Algorithms, Computational Geometry, Algorithmic Game Theory |
|
| K. C. Sivaramakrishnan |
IIT Madras |
CSE |
Programming models, Compilers, Static Analysis, Schedulers, Threading Systems, and Memory Management. |
|
| Kartik Nagar |
IIT Madras |
CSE |
Automated Formal Verification, Program Analysis, Programming Languages. |
|
| Krishna Moorthy Sivalingam |
IIT Madras |
CSE |
Wireless networks, Sensor networks, Optical networks |
|
| L A Prashanth |
IIT Madras |
CSE |
Reinforcement Learning, Stochastic Optimization, Multi-armed Bandits. |
|
| Madhu Mutyam |
IIT Madras |
CSE |
Memory subsystem design, Network-on-chip architectures, Shared resource management. |
|
| Manikandan Narayanan |
IIT Madras |
CSE |
Bioinformatics, Computational network biology, Systems biology/genomics in health and disease, Data science. |
|
| Manikantan Srinivasan |
IIT Madras |
CSE |
Data communication networks, Network virtualization and softwarized cellular mobile communication networks, Wireless LANs, Cyber security, |
|
| Meghana Nasre |
IIT Madras |
CSE |
Graph theory, Algorithms, Matching with preferences. |
|
| Mitesh Khapra |
IIT Madras |
CSE |
Statistical Machine Translation, Text Analytics, Deep Learning and Crowd-sourcing |
|
| N.S. Narayanaswamy |
IIT Madras |
CSE |
Analysis of algorithms, Parameterized Complexity theory, Artificial Intelligence |
|
| Nishad Kothari |
IIT Madras |
CSE |
Graph theory, Matching theory, Combinatorial Optimization |
|
| P. Sreenivasa Kumar |
IIT Madras |
CSE |
Database systems, Semi-structured data and XML, Data mining, Graph algorithms, Parallel computing. |
|
| Ravishankar Krishnaswamy |
IIT Madras |
CSE |
Approximation and online algorithms. |
|
| Rupesh Nasre |
IIT Madras |
CSE |
Compilers, Parallelization. |
|
| Sarath Chandar |
IIT Madras |
CSE |
Recurrent Neural Networks, Lifelong Learning, Reinforcement Learning, Deep Learning, Natural Language Processing, Machine Learning, Artificial Intelligence |
|
| Shweta Agrawal |
IIT Madras |
CSE |
Cryptography and Information theory |
|
| Sriraam Natarajan |
IIT Madras |
CSE |
Relational Learning, Reinforcement Learning, Graphical Models, and Planning |
|
| Sukhendu Das |
IIT Madras |
CSE |
Visual perception - Computer vision, digital image processing; pattern recognition; Graphics; Soft Computing; Computational brain modeling. |
|
| Sutanu Chakraborti |
IIT Madras |
CSE |
Information retrieval, Memory-based reasoning, Machine learning. |
|
| V. Kamakoti |
IIT Madras |
CSE |
Software aspects of VLSI design, Cluster computing, High-performance computing, Algorithms, Data structures, Computational geometry |
|
| V. Krishna Nandivada |
IIT Madras |
CSE |
Compilers, Program Analysis, Programming Languages, Fault Localization, Multicore systems. |
|
| Yadu Vasudev |
IIT Madras |
CSE |
Algorithms, especially Sublinear Algorithms and Computational Complexity Theory |
|
| Dr. Amit Kumar Dhar |
IIT BHILAI |
CSE |
Formal Methods,Model-Checking,Applied formal verification,Algorithms and Complexity |
|
| Dr. Anand M. Baswade |
IIT BHILAI |
CSE |
Wireless & Mobile Networks,5G Network & Systems,Software Defined Networks |
|
| Dr. Arzad Alam Kherani |
IIT BHILAI |
CSE |
omputer networks, Queueing systems, Wireless communications |
|
| Dr. Avishek Adhikary |
IIT BHILAI |
CSE |
Fractional Calculus in Microelectronics,Smart Sensor and Instrumentation,Water Quality Monitoring,Fractional Order Modelling |
|
| Dr. Barun Gorain |
IIT BHILAI |
CSE |
Approximation Algorithms,Distributed Algorithms,Algorithmic Graph Theory |
|
| Dr. Dhiman Saha |
IIT BHILAI |
CSE |
Cryptography, Theoretical Cryptanalysis, Hash functions, Authenticated / Block Ciphers, Fault Analysis Attacks, Higher Order Boolean Derivatives, |
|
| Dr. Nikhil Chander |
IIT BHILAI |
CSE |
Photovoltaics, Flexible Electronics, Plasmonics. |
|
| Dr. Nitin Khanna |
IIT BHILAI |
CSE |
Signal, image, and video processing,Computer vision, Multimedia security,Analysis of remotely sensed images |
|
| Dr. Prashant Agnihotri |
IIT BHILAI |
CSE |
Data Analytics application in Smart,Grid HVDC and FACTS,Power system dynamics and control, Machine Learning and Deep Learning |
|
| Dr. Rishi Ranjan Singh |
IIT BHILAI |
CSE |
Social & Complex Network Analysis, Approximation Algorithms, Combinatorial Optimization, Mathematical Formulation, Vehicle Routing Problems, Graph Theory, Theoretical computer science. |
|
| Dr. Sk Subidh Ali |
IIT BHILAI |
CSE |
Cyber and Hardware Security,Adversarial Machine Learning |
|
| Dr. Soumajit Pramanik |
IIT BHILAI |
CSE |
Information Retrieval,Machine Learning,Social Computing and Complex Networks |
|
| Dr. Sreejith T. V |
IIT BHILAI |
CSE |
Stochastic geometry for wireless,communications,5G non terrestrial communications studies |
|
| Dr. Vishwesh Jatala |
IIT BHILAI |
CSE |
Graphics Processing Units (GPUs),Optimizing Compilers for GPU Performance and Energy,Computer Architecture |
|
| Prof. Rajat Moona |
IIT BHILAI |
CSE |
Embedded computing,Computer security,VLSI design and Operating Systems |
|
| Prof. Santosh Biswas |
IIT BHILAI |
CSE |
VLSI Testing,Embedded Systems,Cyber Security,Fault Tolerance |
|
| Annavarapu Chandra Sekhara Rao |
IIT Dhanbad |
CSE |
Bioinformatics, Evolutionary Algorithms , Datamining , Machine Learning ,Data And Knowledge Based Systems |
|
| Ansuman Bhattacharya |
IIT Dhanbad |
CSE |
Communication And Networks, Graph Algorithm Problems, Network Security Etc. |
|
| Arup Kumar Pal |
IIT Dhanbad |
CSE |
Image Processing, Data Compression, Multimedia Security, Content-Based Image Retrieval, And Cryptography |
|
| Chiranjeev Kumar |
IIT Dhanbad |
CSE |
Wireless Networks , Software Engineering |
|
| Dharavath Ramesh |
IIT Dhanbad |
CSE |
Processing & Mining Big Data, Cloud Computing & Security, Blockchain, Distributed Databases, And Brain Computer Interface |
|
| Gadadhar Sahoo |
IIT Dhanbad |
CSE |
Wireless Sensor Network, Cloud Computing, Soft And Evolutionary Computing, Data Mining, Machine Learning |
|
| Haider Banka |
IIT Dhanbad |
CSE |
Soft Computing, Machine Learning |
|
| Hari Om |
IIT Dhanbad |
CSE |
Video-On-Demand, Cryptology, Data Mining, Information Retrieval, Network Security, Wireless Sensor Networks, Secure Distributed Computing, Signal And Image Processing |
|
| Prasanta K. Jana |
IIT Dhanbad |
CSE |
Wireless Sensor Networks, Cloud Computing, Machine Learning And Data Clustering |
|
| Rajendra Pamula |
IIT Dhanbad |
CSE |
Data Mining,Machine Learning, Wireless Networks |
|
| Sachin Tripathi |
IIT Dhanbad |
CSE |
Group Security,Ad-Hoc And Sensor Network,Artificial Intelligence |
|
| Soumen Bag |
IIT Dhanbad |
CSE |
Document Image Analysis, OCR For Indian Scripts, Handwritten Forgery, Image Forgery Detection, Medical Image Processing. |
|
| Sushanta Mukhopadhyay |
IIT Dhanbad |
CSE |
Image Processing, Fmri, Image/Video Compression, Image/Video Encryption And Image Watermarking. |
|
| Tanusree Kaibartta |
IIT Dhanbad |
CSE |
VLSI Testing |
|
| Tarachand Amgoth |
IIT Dhanbad |
CSE |
Sensor Networks, IoT, AI/ML For Intelligent Edge/Fog Computing |
|
| Abhiram Ranade |
IIT Bombay |
CSE |
Algorithms and Combinatorial Optimization |
|
| Abir De |
IIT Bombay |
CSE |
Foundation and application of machine learning on sets and sequences |
|
| Ajit A Diwan |
IIT Bombay |
CSE |
Algorithms, Theoretical Computer Science |
|
| Ajit Rajwade |
IIT Bombay |
CSE |
Image Processing, Computer Vision, Image Restoration, Image Compression, Probability Density Estimation, Bayesian Methods, Compressive Sensing and Matrix Completion |
|
| Akshay S. |
IIT Bombay |
CSE |
Formal methods |
|
| Amitabha Sanyal |
IIT Bombay |
CSE |
Functional Programming, Compilers, and Programming Languages |
|
| Ashutosh Gupta |
IIT Bombay |
CSE |
Formal verification: building model checkers for verification of sequential and concurrent software,Modelling: modelling of biological systems, Constraint solving: constraint logic programming, decision procedures, and automated theorem proving |
|
| Ashwin Gumaste |
IIT Bombay |
CSE |
SDN, NFV, Network Architecture, Carrier Ethernet |
|
| Bernard Menezes |
IIT Bombay |
CSE |
Information Appliances, Electronic Commerce, Java Security, Parallel Computing, Time Series Forecasting |
|
| Bharat Adsul |
IIT Bombay |
CSE |
Formal methods in Concurrency, Logics and Games, Geometric Complexity Theory |
|
| Bhaskar Raman |
IIT Bombay |
CSE |
Computer networks, Wireless systems, Communication system design for developing regions |
|
| Biswabandan Panda |
IIT Bombay |
CSE |
Computer Architecture for Performance and Security |
|
| G. Sivakumar |
IIT Bombay |
CSE |
Automated Reasoning, Logic Programming, Rewrite Systems, Networks, Distributed Systems |
|
| Ganesh Ramakrishnan |
IIT Bombay |
CSE |
(a) feature induction and learning feature maps (b) learning with multiple labels, multiple instances and multivariate loss functions (c) entity and relation extraction including distant supervision settings, data integration (d) relational learning (e) subset selection problems in machine learning (f) latest: deep learning |
|
| Kameswari Chebrolu |
IIT Bombay |
CSE |
Architecture and protocol design in wired, wireless and sensor networks, development of appropriate technology |
|
| Kavi Arya |
IIT Bombay |
CSE |
Functional Programming Applications (Domain Specific Languages), Embedded Systems/ Parallel Programming Languages, Distance Learning |
|
| Krishna S |
IIT Bombay |
CSE |
Formal Methods, Bio-inspired Computing |
|
| Manoj Prabhakaran |
IIT Bombay |
CSE |
Cryptography, Theoretical Computer Science |
|
| Milind Sohoni |
IIT Bombay |
CSE |
Combinatorial Optimization, Mathematical Programming, Algorithms |
|
| Mrinal Kumar |
IIT Bombay |
CSE |
Computational Complexity, Algebra and Computation, Error Correcting codes |
|
| Mythili Vutukuru |
IIT Bombay |
CSE |
Networking and Systems |
|
| Nutan Limaye |
IIT Bombay |
CSE |
Algorithms and Complexity Theory |
|
| Om P. Damani |
IIT Bombay |
CSE |
Program Derivation, Large Scale Systems, Technology for Social Development |
|
| Parag Chaudhuri |
IIT Bombay |
CSE |
Animation, Computer Graphics, Virtual and Augmented Reality, Geometric Computer Vision |
|
| Preethi Jyothi |
IIT Bombay |
CSE |
Machine learning applied to speech and language |
|
| Purushottam Kulkarni |
IIT Bombay |
CSE |
Operating systems, Virtualization, Cloud Computing, Computer Networks, Computing systems for developing regions, Technology and developmen |
|
| Pushpak Bhattacharya |
IIT Bombay |
CSE |
Natural Language Processing, Machine Learning, Machine Translation, Cross Lingual IR and Web Knowledge Processing |
|
| Rohit Gurjar |
IIT Bombay |
CSE |
Computational Complexity, Derandomization and Pseudorandomness, Polyhedral Combinatorics, Parallel Algorithms |
|
| Rushikesh K. Joshi |
IIT Bombay |
CSE |
Object Oriented Systems, Distributed Systems, Software Architectures |
|
| S. Sudarshan |
IIT Bombay |
CSE |
Query processing and optimization, Keyword querying on structured and semi-structured data, Testing database applications |
|
| Sharat Chandran |
IIT Bombay |
CSE |
Medical Imaging & Health Informatics, Graphics, Computer Vision, Parallel Algorithms, Visualization |
|
| Shivaram Kalyanakrishnan |
IIT Bombay |
CSE |
Reinforcement Learning, Humanoid Robotics & Robot Soccer, Multi-armed Bandits |
|
| Soumen Chakrabarti |
IIT Bombay |
CSE |
Hypertext databases, Data mining |
|
| Sundar Vishwanathan |
IIT Bombay |
CSE |
Algorithms, Combinatorics, Complexity Theory |
|
| Sunita Sarawagi |
IIT Bombay |
CSE |
Machine Learning, Databases, Data mining, and Graphical Models as applied to domains like web information extraction, data integration, social networking |
|
| Supratik Chakraborty |
IIT Bombay |
CSE |
Formal techniques for analysis, verification, validation of digital systems, Asynchronous timing analysis |
|
| Suyash P. Awate |
IIT Bombay |
CSE |
Image Analysis, Medical Image Computing, Machine Learning, Computer Vision |
|
| Uday Khedker |
IIT Bombay |
CSE |
Programming Languages, Compilers, Data Flow Analysis |
|
| Umesh Bellur (Department Head) |
IIT Bombay |
CSE |
Adaptive Service Orientation, Managing virtualization and server consolidation in Clouds, Adaptive QoS based routing in DEBN |
|
| Varsha Apte |
IIT Bombay |
CSE |
Performance Evaluation of Computer Systems and Networks |
|
| Vinay Ribeiro |
IIT Bombay |
CSE |
Computer and Network Security (blockchain, intrusion detection, IoT security, DDoS), Internet of Things (IoT), Wireless Networks (cognitive radio, TV white space, LTE, Wi-Fi etc.), Indoor positioning and navigation |
|


public interface Step extends Predicated
Represents a location step in a LocationPath. The node-set selected by the location step is the node-set that results from generating an initial node-set from the axis and node-test, and then filtering that node-set by each of the predicates in turn.
The initial node-set consists of the nodes having the relationship to the context node specified by the axis, and having the node type and expanded-name specified by the node test.
| Modifier and Type | Method and Description |
|---|---|
Iterator |
axisIterator(Object contextNode,
ContextSupport support)
Get an Iterator for the current axis starting in the given contextNode.
|
List |
evaluate(Context context)
For each node in the given context calls matches() for every node on the
axis, then filters the result by each of the predicates.
|
int |
getAxis()
Get an identifier for the current axis.
|
String |
getText()
Returns a
String containing the XPath expression. |
boolean |
matches(Object node,
ContextSupport contextSupport)
Performs the node-test part of evaluating the step for the given node
(which must be on the axis).
|
void |
simplify()
Simplifies the XPath step.
|
addPredicate, getPredicates, getPredicateSet
boolean matches(Object node, ContextSupport contextSupport) throws JaxenException
JaxenException
String getText()
String
containing the XPath expression.void simplify()
int getAxis()
Axis
Iterator axisIterator(Object contextNode, ContextSupport support) throws UnsupportedAxisException
contextNode
- the node from which to follow this stepsupport
- the remaining context for the traversalUnsupportedAxisException
- if the navigator does not support this step's axisList evaluate(Context context) throws JaxenException
JaxenException
Copyright © 2016. All rights reserved.


Man Utd 'hold talks' with Christian Eriksen over £42m January transfer
Tottenham midfielder is fed up waiting for Real Madrid and instead reportedly held talks with United last month
by Gareth BicknellManchester United have reportedly held talks with Tottenham midfielder Christian Eriksen over a January transfer.
Eriksen is in the final year of his contract with Tottenham and so could leave for free in the summer.
He has been linked with a move to Real Madrid , but according to latest reports from Spain the attacking midfielder has grown tired of waiting for the La Liga giants and has instead begun talks with United.
Red Devils boss Ole Gunnar Solskjaer needs to strengthen his midfield and attack, and 27-year-old Eriksen could fit the bill after impressing during his six years with Tottenham.
And United are preparing to make a £42million bid for the Danish international after holding talks with him last month, according to Spanish publication El Desmarque .
Having been a key figure for Spurs since joining from Ajax for £12m in 2013, Eriksen has been less of a fixture in the team this season, with some observers pointing out that summer speculation over a move to Real Madrid may have unsettled him.
However, earlier this week boss Mauricio Pochettino said Eriksen was still the same player he had always been since joining Tottenham.
"I don’t think the performance of Christian is any different than when we signed him five-and-a-half years ago," said Pochettino.
"His commitment is the same, sometimes we maybe look too much at whether a player has a one-year contract or a four-year contract.
"In the end it is about commitment, maybe players in the last year of their contract show more commitment than a player with four more years on their contract.
"But when you see Christian and you compare him to different seasons, he is the same player."


This app shows the deflection of a harmonically loaded beam for different boundary conditions. The beam properties (the length $L$, the real part of the Young's modulus $E'$, the area moment of inertia $I$ and the mass per unit length $\mu$), as well as the force amplitude $F$ are fixed.
The deflection can be calculated with the following equation: $$W\left(x\right) = C_1 \cdot sin\left(\frac{\lambda}{L} \cdot x\right) + C_2 \cdot cos\left(\frac{\lambda}{L} \cdot x\right) + C_3 \cdot sinh\left(\frac{\lambda}{L} \cdot x\right) + C_4 \cdot cosh\left(\frac{\lambda}{L} \cdot x\right),$$ where $$\lambda = L \cdot \sqrt[4]{\frac{\mu \cdot \Omega^2}{E \cdot I}}.$$ The complex Young's modulus can be described with $$E = E' \cdot \left(1 + \text{i} \cdot \eta\right)$$ where $\eta$ is the damping loss factor.
The drop down menu allows to choose from four different support systems. Additionally, we allow the modification of
The plot on the upper left shows the chosen system and the deformed beam. The maximum deflection is normalized to a certain value. The diagram on the upper right shows the normalized deflection of the beam at the chosen location for a fixed range of excitation frequency ratios. On the lower right the corresponding phase angle is plotted. The phase angle describes by how much the response lags behind the excitation. The green button allows the user to change between the frequency analysis and the modification of the input parameters.
The 3D plot at the bottom puts together the information displayed in the upper diagrams and shows the dependency between the excitation frequency ratio, the eigenfrequencies of the system and the normalized deflection of the beam. For a better visualization of the beam deflection at higher excitation frequencies, the normalized deflection is multiplied with the squared excitation frequency ratio $r$. One can pan to rotate the figure and scroll or pinch to zoom.


Hutong dumplings carlton, MSAC empire of the sun swanston the city loop dandenong, melb ball food bloggers pellegrini's the melbourne cup, moomba the bulldogs bourke st mall chaddie fed square, street art werribee wildlife ticket inspector.
Collingwood ferals brunswick st hippy, brunswick and brunswick st emerald peacock formula one grand prix essendon bombers a macaron connoisseur, black is alway in fashion MSAC fed square ticket inspector rocking out the espy, swanston world's most liveable city cookie the croft institute dumplings, fairy penguins etihad stadium spring racing carnival.
Formula one grand prix the croft institute, the espy a macaron connoisseur world's most liveable city fairy penguins the rebels, the hawks collingwood ferals emerald peacock ticket inspector NGV culture fix, movida kath and kim bill clinton ate two bowls victoria street dodgies street art, werribee wildlife aami park rooftop cinema.
Chapel street dame edna, east brunswick club rooftop bars empire of the sun chopper read posh brighton, trams essendon bombers brown alley lions bar ac/dc, graffiti dandenong etihad stadium running the tan chaddie, bill clinton ate two bowls don dons trams.
Werribee wildlife food bloggers, middle-aged lycra clad cyclists vic market posh brighton kath and kim Rod Laver, warehouse chic chopper read yarra cold drip coffee aami park, the emerald peacock burlesque four seasons in one day street art hook turns, brunswick and brunswick st movida south melb dim sims.
Brunswick st hippy south of the river, melbourne cricket ground brown alley shane warne kylie minogue essendon bombers, rooftop bars NGV culture fix south melb dim sims temper trap the espy, geoffrey rush formula one grand prix neatly trimmed moustaches bourke st mall the crazy wing challenge, chaddie the corner hotel secret laneway bars.
Bourke st mall fed square, swanston kath and kim MSAC cold drip coffee laksa king, the emerald peacock ball the saints grammar vs scotch pellegrini's, purple emerald burlesque ticket inspector collins place melbourne central, werribee wildlife footy collingwood ferals.

Dandenong NGV culture fix, ball citylink moomba swanston purple emerald, spencer st station mamasita the storm don dons etihad stadium, running the tan laksa king rooftop bars temper trap presets, posh brighton south of the river brunswick st hippy.
Middle-aged lycra clad cyclists melbourne cricket ground, the saints cold drip coffee brunswick and brunswick st MSAC lions bar, the melbourne cup cumulus inc shane warne the city loop swanston, old melbourne gaol posh brighton north melbourne shinboners ac/dc rooftop cinema, fairy penguins south melb dim sims aami park.
Presets melb, chopper read movida aami park don dons running the tan, purple emerald ball richmond tigers swanston burlesque, the australian open vic market moomba mamasita warehouse chic, frankston bogans geoffrey rush spring racing carnival.
Hipster map of Melbourne
How did the hipster burn her tongue?
She drank her coffee before it was cool.
Got a suggestion?
Source for this page at
Github.
Read more about the project at
Aunty.
Get in touch on Twitter with
Maia and
Steve.
Melbourne Ipsum text by
melbourneipsum.com.au.
Credits:
Steve Bennett, Maia Sauren,
Matt Cengia,
Hamish,
Mike Ebinum,
Glenn Todd,
Anthony Mockler,
Nic Smythe, Peter Dudley,
Fiona Tweedie, AJ,
Tim Hordern. (Have we missed anyone?)


If you don’t have the programming experience to create your own Sketch plugin or integration, you can submit an idea to let our team and the community know what kind of functionality you’re looking for.
Take a look at the list of plugins the community has already built.


LOA:
LWL:
Beam:
Displacement:
SailArea:
Displacement to LWL:Displacement to LWL: A medium value would be 200. 300 would be high (Heavy Cruising Boat) and 100 would be low (Ultra Light Displacement-ULDB). Boats with low numbers are probably uncomfortable and difficult to sail.
Hull Speed: Hull Speed: This is the maximum speed of a displacement hull. Some racers and lighter boats are able to achieve greater speed by lifting over the bow wave and riding on top of the water,that is, planing.
Sail area to displacement: Sail Area to Displacement: The sail area is the total of the main sail and the area of the front triangle. I cannot be sure that this datum was entered correctly for each listed boat. A racing boat typically has large sail area and low displacement. A number less than 13 probably indicates that the boat is a motorsailer. High performance boats would be around 18 or higher.
LWL to beam: LWL to Beam: A medium value would be 2.7. 3.0 would be high and 2.3 would be low
Motion comfort: Motion Comfort: Range will be from 5 to 60+ with a Whitby 42 at the mid 30's. The higher the number the more comfort in a sea. This figure of merit was developed by the Yacht designer Ted Brewer and is meant to compare the motion comfort of boats of similar size and types.
Capsize ratio: Capsize Ratio: A value less than 2 is considered to be relatively good; the boat should be relatively safe in bad conditions. The higher the number above 2 the more vulnerable the boat. This is just a rough figure of merit and controversial as to its use.
Sailing category: Sailing Category: The four categories are racer, racer/cruiser, cruiser/racer, and cruiser in order of descending performance
Pounds/Inch: Pounds per Inch Immersion: The weight required to sink the yacht one inch. If the boat is in fresh water multiply the result by 0.975. If you know the beam at the waterline (BWL) multipy the result by BWL/Beam.


The VaynerMedia Front-End Challenge: Album Sorter
Simply drag albums from one user table to the end of the other
Check the console to see the user id change in the data object!
Album ID
Album Title
Album ID
Album Title


Towards the end of my internship with FullstackLabs, I created landing pages which were to be used to demo the projects they worked on. They usually would include embedded prototypes for the user to click through or animations to demonstrate user flow.


Cambourn
This page contains an index of all the individuals in the database with the surname of Cambourn. Selecting the person’s name will take you to that person’s individual page.
| Given Name | Birth | Death | Partner | Parents |
|---|---|---|---|---|
| Albert John | c1874 | Cambourn, Thomas Williams, Mary Emily | ||
| Cecil | 1899-09-19 | 1974-06-11 | Cambourn, William Arthur Small, Sarah Jane | |
| Frank William | 1927-05-24 | 1968-01-31 | Ross, [Living] | Cambourn, Leo Tytherleigh, Alice Mary |
| Hubert, married Madeline | 1891-07-06 | 1954-12-28 | Cambourn, William Arthur Small, Sarah Jane | |
| James | c1869 | Cambourn, Thomas Williams, Mary Emily | ||
| John | c1874 | Cambourn, Thomas Williams, Mary Emily | ||
| Leo | 1896-10-20 | 1979-09-14 | Tytherleigh, Alice Mary | Cambourn, William Arthur Small, Sarah Jane |
| Linda | 1889-08-14 | 1965-08-05 | Cambourn, William Arthur Small, Sarah Jane | |
| Peter Ross | 1962-12-07 | 1962-12-09 | Cambourn, Frank William Ross, [Living] | |
| Robert Leo | 1921-07-07 | 2011-07-04 | Weavers, [Living] | Cambourn, Leo Tytherleigh, Alice Mary |
| Thomas | c1832 | 1909-08-13 | Williams, Mary Emily, Coles, Sarah Jane | |
| Thomas Edward | 1864-12-21 | 1948-08-22 | Zartman, Annie W. | Cambourn, Thomas Williams, Mary Emily |
| William Arthur | 1860-04-03 | 1924-10-28 | Small, Sarah Jane | Cambourn, Thomas Williams, Mary Emily |
| [Living] | Milton, [Living], Fludder, [Living] | Cambourn, Frank William Ross, [Living] | ||
| [Living] | Crawford, John Arundale | Cambourn, Leo Tytherleigh, Alice Mary | ||
| [Living] | Marriott, [Living] | Cambourn, Leo Tytherleigh, Alice Mary | ||
| [Living] | Hughes, [Living] | Cambourn, Leo Tytherleigh, Alice Mary | ||
| [Living] | Bock, [Living] | Cambourn, Robert Leo Weavers, [Living] | ||
| [Living] | Whitty, [Living] | Cambourn, Robert Leo Weavers, [Living] | ||
| [Living] | Cambourn, [Living] Hughes, [Living] | |||
| [Living] | Vowels, [Living] | Cambourn, [Living] Hughes, [Living] | ||
| [Living] | Cambourn, [Living] Hughes, [Living] | |||
| [Living] | Ball, [Living] | Cambourn, Frank William Ross, [Living] | ||
| [Living] | Cambourn, Thomas Edward Zartman, Annie W. |


Best Pre-Black Friday 2019 Home Deals From Walmart And Wayfair
by Forbes FindsBlack Friday is only a few weeks away, and while you may be holding your breath for huge purchases on things like accent chairs, rugs and lamps, plenty of retailers have announced some pretty huge deals already. That’s especially true when it comes to furniture from our favorite retailers. Just in time for the holiday season, here are some of the best deals from Wayfair and Walmart.
Chairs
Need a new accent chair for your space? Let these bargain-friendly deals on chairs speak for themselves. Ahead, we highlight two accent chairs that go great in any space (and are on major sale).
Fox Hill Ellis Rolled Arm Lounge Chair
Original Price: $200
Sale Price: $129.99
When it comes to accent chairs, simplicity can be key — especially if you are using it to tie your room together. We love the Fox Hill Ellis Rolled Arm Lounge Chair for its simplicity, comfort and excellent fabric options. From cowhide to jewel tones, the seat pairs well with any style.
Zipcode Design Phipps Barrel Chair
Original Price: $399.99
Sale Price: $162.99
The Zipcode Design Phipps Barrel Chair is another simple yet game-changing piece for the home. And right now you can get it for over 50 percent off. The contemporary, compact accent chair is neutral, yet statement-making with its tufted back and stunning upholstery.
Laurel Foundry Modern Farmhouse Marta Cuddler Barrel Chair
Original Price: $1,090
Sale Price: $980.99
Not all accent chairs need to be small and compact. Case in point: The Laurel Foundry Modern Farmhouse Marta Cuddler Barrel Chair is a great addition to your living or family room furniture. It has enough room to sit comfortably during family movie night and could even fit two people if need be. On top of that, it’s on major sale right now. Originally priced at $1,090, you can get the accent chair for only $980 right now.
Rugs
Area rugs are one of those home items we love but have a hard time splurging on. Which is why shopping deals on area rugs are what Black Friday dreams are made of. From contemporary to bohemian, these two rugs are a great way to make a statement and save big bucks.
Mistana Newburyport OrangeBluePink Area Rug
Original Price: $38 - $1,398
Sale Price: $29.99 - $279.99
If you want to add some color to your room without going overboard, a rug is a great way to do so. And, the Mistana Newburyport OrangeBluePink Area Rug is the perfect mix of bohemian design and whimsical color to help make any room pop. Right now, you can get a steep discount on the designer rug with sale prices ranging from 29.99 to $279.99 and originally on sale for $38 to $1,398.
The Twillery Co. Castor Exploded Medallions Slate Blue Area Rug
Original Price: Starting at $106
Sale Price: $61-$711
Contemporary rooms can also benefit from color and The Twillery Co. Castor Exploded Medallions Slate Blue Area Rug is a great way to add some flair. The slate blue color is neutral enough for a subtle pop of color while the medallion design can pair beautifully with furniture and room decor. And, you don’t need to break the bank, either. Right now, the designer rug is on sale for between $61 and $711, depending on size.
Astoria Grand Pennypacker Red/Blue Area Rug
Original Price: $75-$1,366
Sale Price: $38-$711
Add some vintage flair to your space with the Astoria Grand Pennypacker Red/Blue Area Rug. The stunning rug boasts a colorful design that can help tie in a color scheme, warm up a space, and pairs nicely with both new and antique furniture pieces. Right now, you can score a steep discount on the designer rug. Originally on sale for $75 to $1,366 (depending on size), you can now order it for between $38 and $711.
Wyona Distressed Abstract Multicolor Area Rug
Original Price: $200
Sale Price: $66.99
If you’re looking for a great way to add a nice cool tone to your home, then this rug is an excellent way to do so. It offers a modern look and a soft feel, and is available at a huge discount. You can get the rug for yourself for $66.99 — which is 67 percent off the original price of $200.
Lamps
Lamps make excellent room upgrades but, their prices sure can add up. To avoid going over budget, shop for Black Friday lamp deals. The good news? You can get a head start with these discounted options.
Wade Logan Courtney 24-inch Table Lamp
Original Price: $434.75
Sale Price: $90.99
Looking for a set of classy, well-designed lamps that you can use in pretty much any environment, this set of two lamps is an excellent option. The lamps are available in a huge variety of colors, and offers a 100 percent cotton shade that will help make the lamps more durable than they otherwise would be.
Greyleigh Flannery 28-inch Tablet Lamp
Original Price: $151.99
Sale Price: $118.99
If you’re in the market for something beautifully designed that will add a ton of flair to your living room, then this lamp is absolutely the way to go. It’s available in a few different colors, including Gold Plate, Oil Rubbed Bronze and Polished Nickel, and you can get it now for $118.99, which is 22 percent off its normal price of $151.99.
Andover Mills Peoria 3 Piece Table and Floor Lamp Set
Original Price: $183.05
Sale Price: $88.01
Three lamps for under $100? You aren’t dreaming. Right now, you can score the Andover Mills Peoria 3 Piece Table and Floor Lamp Set for $86 off the original price tag. This set is perfect for those looking for fixtures that will help tie the room together in a way that is cohesive and stylish.
Birch Lane Cumberland Table Lamp
Original Price: $134.40
Sale Price: $68.99
There are pros and cons when it comes to lamp purchases. For starters, light fixtures help spruce up any space and are a fun and relatively commitment-free way to jump onboard a trend. However, you might not hold onto them for years to come, which is why buying lamps on sale is a great way to get the best of both worlds. Speaking of trendy lamps, the Birch Lane Cumberland Table Lamp features a subtle, hammered steel-inspired design that not only brings your space into 2019 but will outlive shorter-lived trends.
Beachcrest Home Eskridge Mother of Pearl Inlay Table Lamp (Set of 2)
Original Price: $406
Sale Price: $155
Lamp deals are always best in twos! And these two Mother of Pearl table lamps are on major discount. Perfect for any space with subtle beach vibes, these lamps are as stunning as they are discounted. Right now, you can get the stunning texture design for over 60 percent off. Originally on sale for $406, this set of two is now available for just $155.


Toggle navigation
Weather Prediction
Dashboard
Open Weather Map API
Yahoo Weather API
Forecast IO API
Weather Underground API
Weather Underground API
Google Maps APIs
Notice: this API is only available in U.S.


Experience the biggest fashion sale here!
Upcoming biggest fashion Deals
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Crumop399.github.io
Hotpoint Ariston Fo 52 Handbuch.
Hotpoint Ariston Fo 52 Handbuch and Cefar easy Handbücher.


This example shows the built-in text functions performances vs. the native ones (if available in your browser).


Incoming Selection Context
Incoming Embedded Context
Outgoing JSON
Close and send (regular)
Close and send (programmatic)


class TZInfo::DataSources::ZoneinfoDataSource
A DataSource
implementation that loads data from a 'zoneinfo' directory containing compiled “TZif” version 3 (or earlier) files in addition to iso3166.tab and zone1970.tab or zone.tab index files.
To have TZInfo
load the system zoneinfo files, call {TZInfo::DataSource.set} as follows:
TZInfo::DataSource.set(:zoneinfo)
To load zoneinfo files from a particular directory, pass the directory to {TZInfo::DataSource.set}:
TZInfo::DataSource.set(:zoneinfo, directory)
To load zoneinfo files from a particular directory, but load the iso3166.tab index file from a separate location, pass the directory and path to the iso3166.tab file to {TZInfo::DataSource.set}:
TZInfo::DataSource.set(:zoneinfo, directory, iso3166_path)
Please note that versions of the 'zic' tool (used to build zoneinfo files) that were released prior to February 2006 created zoneinfo files that used 32-bit integers for transition timestamps. Later versions of zic produce zoneinfo files that use 64-bit integers. If you have 32-bit zoneinfo files on your system, then any queries falling outside of the range 1901-12-13 20:45:52 to 2038-01-19 03:14:07 may be inaccurate.
Most modern platforms include 64-bit zoneinfo files. However, Mac OS X (up to at least 10.8.4) still uses 32-bit zoneinfo files.
To check whether your zoneinfo files contain 32-bit or 64-bit transition data, you can run the following code (substituting the identifier of the zone you want to test for `zone_identifier`):
TZInfo::DataSource.set(:zoneinfo) dir = TZInfo::DataSource.get.zoneinfo_dir File.open(File.join(dir, zone_identifier), 'r') {|f| f.read(5) }
If the last line returns `“TZif\x00”`, then you have a 32-bit zoneinfo file. If it returns `“TZif2”` or `“TZif3”` then you have a 64-bit zoneinfo file.
It is also worth noting that as of the 2017c release of the IANA Time Zone Database, 64-bit zoneinfo files only include future transitions up to 2038-01-19 03:14:07. Any queries falling after this time may be inaccurate.
Constants
- DEFAULT_ALTERNATE_ISO3166_TAB_SEARCH_PATH
The default value of {ZoneinfoDataSource.alternate_iso3166_tab_search_path}.
- DEFAULT_SEARCH_PATH
The default value of {ZoneinfoDataSource.search_path}.
Attributes
(see DataSource#country_codes
)
@return [String] the zoneinfo directory being used.
Public Class Methods
An `Array` of paths that will be checked to find an alternate iso3166.tab file if one was not included in the zoneinfo directory (for example, on FreeBSD and OpenBSD systems).
Paths are checked in the order they appear in the `Array`.
The default value is `['/usr/share/misc/iso3166.tab', '/usr/share/misc/iso3166']`.
@return [Array<String>] an `Array` of paths to check in order to
locate an iso3166.tab file.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 136 def alternate_iso3166_tab_search_path @@alternate_iso3166_tab_search_path end
Sets the paths to check to locate an alternate iso3166.tab file if one was not included in the zoneinfo directory.
Can be set to an `Array` of paths or a `String` containing paths separated with `File::PATH_SEPARATOR`.
Paths are checked in the order they appear in the array.
Set to `nil` to revert to the default paths.
@param alternate_iso3166_tab_search_path
[Object] either `nil` or a
list of paths to check as either an `Array` of `String` or a `File::PATH_SEPARATOR` separated `String`.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 153 def alternate_iso3166_tab_search_path=(alternate_iso3166_tab_search_path) @@alternate_iso3166_tab_search_path = process_search_path(alternate_iso3166_tab_search_path, DEFAULT_ALTERNATE_ISO3166_TAB_SEARCH_PATH) end
Initializes a new {ZoneinfoDataSource}.
If `zoneinfo_dir` is specified, it will be checked and used as the source of zoneinfo files.
The directory must contain a file named iso3166.tab and a file named either zone1970.tab or zone.tab. These may either be included in the root of the directory or in a 'tab' sub-directory and named country.tab and zone_sun.tab respectively (as is the case on Solaris).
Additionally, the path to iso3166.tab can be overridden using the `alternate_iso3166_tab_path` parameter.
If `zoneinfo_dir` is not specified or `nil`, the paths referenced in {search_path} are searched in order to find a valid zoneinfo directory (one that contains zone1970.tab or zone.tab and iso3166.tab files as above).
The paths referenced in {alternate_iso3166_tab_search_path} are also searched to find an iso3166.tab file if one of the searched zoneinfo directories doesn't contain an iso3166.tab file.
@param zoneinfo_dir
[String] an optional path to a directory to use as
the source of zoneinfo files.
@param alternate_iso3166_tab_path [String] an optional path to the
iso3166.tab file.
@raise [InvalidZoneinfoDirectory] if the iso3166.tab and zone1970.tab or
zone.tab files cannot be found using the `zoneinfo_dir` and `alternate_iso3166_tab_path` parameters.
@raise [ZoneinfoDirectoryNotFound] if no valid directory can be found
by searching.
TZInfo::DataSource::new
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 217 def initialize(zoneinfo_dir = nil, alternate_iso3166_tab_path = nil) super() if zoneinfo_dir iso3166_tab_path, zone_tab_path = validate_zoneinfo_dir(zoneinfo_dir, alternate_iso3166_tab_path) unless iso3166_tab_path && zone_tab_path raise InvalidZoneinfoDirectory, "#{zoneinfo_dir} is not a directory or doesn't contain a iso3166.tab file and a zone1970.tab or zone.tab file." end @zoneinfo_dir = zoneinfo_dir else @zoneinfo_dir, iso3166_tab_path, zone_tab_path = find_zoneinfo_dir unless @zoneinfo_dir && iso3166_tab_path && zone_tab_path raise ZoneinfoDirectoryNotFound, "None of the paths included in #{self.class.name}.search_path are valid zoneinfo directories." end end @zoneinfo_dir = File.expand_path(@zoneinfo_dir).freeze @timezone_identifiers = load_timezone_identifiers.freeze @countries = load_countries(iso3166_tab_path, zone_tab_path).freeze @country_codes = @countries.keys.sort!.freeze string_deduper = ConcurrentStringDeduper.new posix_tz_parser = PosixTimeZoneParser.new(string_deduper) @zoneinfo_reader = ZoneinfoReader.new(posix_tz_parser, string_deduper) end
An `Array` of directories that will be checked to find the system zoneinfo directory.
Directories are checked in the order they appear in the `Array`.
The default value is `['/usr/share/zoneinfo', '/usr/share/lib/zoneinfo', '/etc/zoneinfo']`.
@return [Array<String>] an `Array` of directories to check in order to
find the system zoneinfo directory.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 103 def search_path @@search_path end
Sets the directories to be checked when locating the system zoneinfo directory.
Can be set to an `Array` of directories or a `String` containing directories separated with `File::PATH_SEPARATOR`.
Directories are checked in the order they appear in the `Array` or `String`.
Set to `nil` to revert to the default paths.
@param search_path
[Object] either `nil` or a list of directories to
check as either an `Array` of `String` or a `File::PATH_SEPARATOR` separated `String`.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 121 def search_path=(search_path) @@search_path = process_search_path(search_path, DEFAULT_SEARCH_PATH) end
Private Class Methods
Processes a path for use as the {search_path} or {alternate_iso3166_tab_search_path}.
@param path [Object] either `nil` or a list of paths to check as
either an `Array` of `String` or a `File::PATH_SEPARATOR` separated `String`.
@param default [Array<String>] the default value. @return [Array<String>] the processed path.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 167 def process_search_path(path, default) if path if path.kind_of?(String) path.split(File::PATH_SEPARATOR) else path.collect(&:to_s) end else default.dup end end
Public Instance Methods
Returns a frozen `Array` of all the available time zone identifiers. The identifiers are sorted according to `String#<=>`.
@return [Array<String>] a frozen `Array` of all the available time zone
identifiers.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 251 def data_timezone_identifiers @timezone_identifiers end
(see DataSource#inspect
)
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 270 def inspect "#<#{self.class}: #{@zoneinfo_dir}>" end
Returns an empty `Array`. There is no information about linked/aliased time zones in the zoneinfo files. When using {ZoneinfoDataSource}, every time zone will be returned as a {DataTimezone}.
@return [Array<String>] an empty `Array`.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 260 def linked_timezone_identifiers [].freeze end
(see DataSource#to_s
)
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 265 def to_s "Zoneinfo DataSource: #{@zoneinfo_dir}" end
Protected Instance Methods
(see DataSource#load_country_info
)
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 306 def load_country_info(code) lookup_country_info(@countries, code) end
Returns a {TimezoneInfo} instance for the given time zone identifier. The result will either be a {ConstantOffsetDataTimezoneInfo} or a {TransitionsDataTimezoneInfo}.
@param identifier [String] A time zone identifier. @return [TimezoneInfo] a {TimezoneInfo} instance for the given time zone
identifier.
@raise [InvalidTimezoneIdentifier] if the time zone is not found, the
identifier is invalid, the zoneinfo file cannot be opened or the zoneinfo file is not valid.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 286 def load_timezone_info(identifier) valid_identifier = validate_timezone_identifier(identifier) path = File.join(@zoneinfo_dir, valid_identifier) zoneinfo = begin @zoneinfo_reader.read(path) rescue Errno::EACCES, InvalidZoneinfoFile => e raise InvalidTimezoneIdentifier, "#{e.message.encode(Encoding::UTF_8)} (loading #{valid_identifier})" rescue Errno::EISDIR, Errno::ENAMETOOLONG, Errno::ENOENT, Errno::ENOTDIR raise InvalidTimezoneIdentifier, "Invalid identifier: #{valid_identifier}" end if zoneinfo.kind_of?(TimezoneOffset) ConstantOffsetDataTimezoneInfo.new(valid_identifier, zoneinfo) else TransitionsDataTimezoneInfo.new(valid_identifier, zoneinfo) end end
Private Instance Methods
Converts degrees, minutes and seconds to a Rational.
@param sign [String] `'-'` or `'+'`. @param degrees [String] the number of degrees. @param minutes [String] the number of minutes. @param seconds [String] the number of seconds (optional). @return [Rational] the result of converting from degrees, minutes and
seconds to a `Rational`.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 567 def dms_to_rational(sign, degrees, minutes, seconds = nil) degrees = degrees.to_i minutes = minutes.to_i sign = sign == '-'.freeze ? -1 : 1 if seconds Rational(sign * (degrees * 3600 + minutes * 60 + seconds.to_i), 3600) else Rational(sign * (degrees * 60 + minutes), 60) end end
Recursively enumerate a directory of time zones.
@param dir [Array<String>] the directory to enumerate as an `Array` of
path components.
@param exclude [Array<String>] file names to exclude when scanning
`dir`.
@yield [path] the path of each time zone file found is passed to
the block.
@yieldparam path [Array<String>] the path of a time zone file as an
`Array` of path components.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 422 def enum_timezones(dir, exclude = [], &block) Dir.foreach(File.join(@zoneinfo_dir, *dir)) do |entry| begin entry.encode!(Encoding::UTF_8) rescue EncodingError next end unless entry =~ /\./ || exclude.include?(entry) entry.untaint path = dir + [entry] full_path = File.join(@zoneinfo_dir, *path) if File.directory?(full_path) enum_timezones(path, [], &block) elsif File.file?(full_path) yield path end end end end
Finds a zoneinfo directory using {search_path} and {alternate_iso3166_tab_search_path}.
@return [Array<String>] an `Array` containing the iso3166.tab and
zone.tab paths if a zoneinfo directory was found, otherwise `nil`.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 369 def find_zoneinfo_dir alternate_iso3166_tab_path = self.class.alternate_iso3166_tab_search_path.detect do |path| File.file?(path) end self.class.search_path.each do |path| # Try without the alternate_iso3166_tab_path first. iso3166_tab_path, zone_tab_path = validate_zoneinfo_dir(path) return path, iso3166_tab_path, zone_tab_path if iso3166_tab_path && zone_tab_path if alternate_iso3166_tab_path iso3166_tab_path, zone_tab_path = validate_zoneinfo_dir(path, alternate_iso3166_tab_path) return path, iso3166_tab_path, zone_tab_path if iso3166_tab_path && zone_tab_path end end # Not found. nil end
Uses the iso3166.tab and zone1970.tab or zone.tab files to return a Hash mapping country codes to CountryInfo
instances.
@param iso3166_tab_path [String] the path to the iso3166.tab file. @param zone_tab_path [String] the path to the zone.tab file. @return [Hash<String, CountryInfo>] a mapping from ISO 3166-1 alpha-2
country codes to {CountryInfo} instances.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 451 def load_countries(iso3166_tab_path, zone_tab_path) # Handle standard 3 to 4 column zone.tab files as well as the 4 to 5 # column format used by Solaris. # # On Solaris, an extra column before the comment gives an optional # linked/alternate timezone identifier (or '-' if not set). # # Additionally, there is a section at the end of the file for timezones # covering regions. These are given lower-case "country" codes. The timezone # identifier column refers to a continent instead of an identifier. These # lines will be ignored by TZInfo. # # Since the last column is optional in both formats, testing for the # Solaris format is done in two passes. The first pass identifies if there # are any lines using 5 columns. # The first column is allowed to be a comma separated list of country # codes, as used in zone1970.tab (introduced in tzdata 2014f). # # The first country code in the comma-separated list is the country that # contains the city the zone identifier is based on. The first country # code on each line is considered to be primary with the others # secondary. # # The zones for each country are ordered primary first, then secondary. # Within the primary and secondary groups, the zones are ordered by their # order in the file. file_is_5_column = false zone_tab = [] file = File.read(zone_tab_path, external_encoding: Encoding::UTF_8, internal_encoding: Encoding::UTF_8) file.each_line do |line| line.chomp! if line =~ /\A([A-Z]{2}(?:,[A-Z]{2})*)\t(?:([+\-])(\d{2})(\d{2})([+\-])(\d{3})(\d{2})|([+\-])(\d{2})(\d{2})(\d{2})([+\-])(\d{3})(\d{2})(\d{2}))\t([^\t]+)(?:\t([^\t]+))?(?:\t([^\t]+))?\z/ codes = $1 if $2 latitude = dms_to_rational($2, $3, $4) longitude = dms_to_rational($5, $6, $7) else latitude = dms_to_rational($8, $9, $10, $11) longitude = dms_to_rational($12, $13, $14, $15) end zone_identifier = $16 column4 = $17 column5 = $18 file_is_5_column = true if column5 zone_tab << [codes.split(','.freeze), zone_identifier, latitude, longitude, column4, column5] end end string_deduper = StringDeduper.new primary_zones = {} secondary_zones = {} zone_tab.each do |codes, zone_identifier, latitude, longitude, column4, column5| description = file_is_5_column ? column5 : column4 description = string_deduper.dedupe(description) if description # Lookup the identifier in the timezone index, so that the same # String instance can be used (saving memory). begin zone_identifier = validate_timezone_identifier(zone_identifier) rescue InvalidTimezoneIdentifier # zone_identifier is not valid, dedupe and allow anyway. zone_identifier = string_deduper.dedupe(zone_identifier) end country_timezone = CountryTimezone.new(zone_identifier, latitude, longitude, description) # codes will always have at least one element (primary_zones[codes.first.freeze] ||= []) << country_timezone codes[1..-1].each do |code| (secondary_zones[code.freeze] ||= []) << country_timezone end end countries = {} file = File.read(iso3166_tab_path, external_encoding: Encoding::UTF_8, internal_encoding: Encoding::UTF_8) file.each_line do |line| line.chomp! # Handle both the two column alpha-2 and name format used in the tz # database as well as the 4 column alpha-2, alpha-3, numeric-3 and # name format used by FreeBSD and OpenBSD. if line =~ /\A([A-Z]{2})(?:\t[A-Z]{3}\t[0-9]{3})?\t(.+)\z/ code = $1 name = $2 zones = (primary_zones[code] || []) + (secondary_zones[code] || []) countries[code] = CountryInfo.new(code, name, zones) end end countries end
Scans @zoneinfo_dir and returns an `Array` of available time zone identifiers. The result is sorted according to `String#<=>`.
@return [Array<String>] an `Array` containing all the time zone
identifiers found.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 394 def load_timezone_identifiers index = [] # Ignoring particular files: # +VERSION is included on Mac OS X. # leapseconds is a list of leap seconds. # localtime is the current local timezone (may be a link). # posix, posixrules and right are directories containing other versions of the zoneinfo files. # src is a directory containing the tzdata source included on Solaris. # timeconfig is a symlink included on Slackware. enum_timezones([], ['+VERSION', 'leapseconds', 'localtime', 'posix', 'posixrules', 'right', 'src', 'timeconfig']) do |identifier| index << identifier.join('/').freeze end index.sort! end
Attempts to resolve the path to a tab file given its standard names and tab sub-directory name (as used on Solaris).
@param zoneinfo_path [String] the path to a zoneinfo directory. @param standard_names [Array<String>] the standard names for the tab
file.
@param tab_name [String] the alternate name for the tab file to check in
the tab sub-directory.
@return [String] the path to the tab file.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 352 def resolve_tab_path(zoneinfo_path, standard_names, tab_name) standard_names.each do |standard_name| path = File.join(zoneinfo_path, standard_name) return path if File.file?(path) end path = File.join(zoneinfo_path, 'tab', tab_name) return path if File.file?(path) nil end
Validates a zoneinfo directory and returns the paths to the iso3166.tab and zone1970.tab or zone.tab files if valid. If the directory is not valid, returns `nil`.
The path to the iso3166.tab file may be overridden by passing in a path. This is treated as either absolute or relative to the current working directory.
@param path [String] the path to a possible zoneinfo directory. @param iso3166_tab_path [String] an optional path to an external
iso3166.tab file.
@return [Array<String>] an `Array` containing the iso3166.tab and
zone.tab paths if the directory is valid, otherwise `nil`.
# File lib/tzinfo/data_sources/zoneinfo_data_source.rb, line 325 def validate_zoneinfo_dir(path, iso3166_tab_path = nil) if File.directory?(path) if iso3166_tab_path return nil unless File.file?(iso3166_tab_path) else iso3166_tab_path = resolve_tab_path(path, ['iso3166.tab'], 'country.tab') return nil unless iso3166_tab_path end zone_tab_path = resolve_tab_path(path, ['zone1970.tab', 'zone.tab'], 'zone_sun.tab') return nil unless zone_tab_path [iso3166_tab_path, zone_tab_path] else nil end end


Step 1: Problem and question(s)
Context
Number of students
Subject
Other information
Problem in the teaching practice
Question(s) for evaluation
Next
Step 2: Design intervention and evaluation
Intervention
Supporting tools for intervention
ILDE Tools
PyramidApp
Ld-Feedback
Google form
Other tools
Kahoot
Edpuzzle
Padlet
Socrative
Evaluation
Supporting tools for evaluation
Analytics Integrated in ILDE
PyramidApp Analytics
Ld-Feedback Analytics
Google form responses
Other analytics
Kahoot results .csv
Edpuzzle results .csv
Padlet results
Socrative results .csv or .pdf
Previous
Next
Step 3: Collected data and analysis
PyramidApp analytics
Ld-Feedback analytics
Google form responses
Other analysis
Files input
Upload here any .csv or .xlsx file with data (e.g. Kahoot, Edpuzzle, Socrative results).
Upload here any .csv or .xlsx file with data (e.g. Kahoot, Edpuzzle, Socrative results).
Upload here any .csv or .xlsx file with data (e.g. Kahoot, Edpuzzle, Socrative results).
Previous
Next
Step 4: Reflection and proposed changes
Reflection about the results in connection with the Step 1
Proposed changes in the design based on the collected data
Changes
Control better the time
Encourage more participation
Provide more instructions in the task
Previous


| 014:034 Khan | : |
And He gave you of all that you asked for, and if you count the Blessings of Allah, never will you be able to count them. Verily! Man is indeed an extreme wrong-doer, - a disbeliever (an extreme ingrate, denies Allah's Blessings by disbelief, and by worshipping others besides Allah, and by disobeying Allah and His Prophet Muhammad SAW). |
| 014:034 Maulana | : |
And He gives you of all you ask of Him. And if you count Allah's favours, you will not be able to number them. Surely man is very unjust, very ungrateful. |
| 014:034 Pickthal | : |
And He giveth you of all ye ask of Him, and if ye would count the bounty of Allah ye cannot reckon it. Lo! man is verily a wrong-doer, an ingrate. |
| 014:034 Rashad | : |
And He gives you all kinds of things that you implore Him for. If you count GOD's blessings, you can never encompass them. Indeed, the human being is transgressing, unappreciative. |
| 014:034 Sarwar | : |
He has given you everything that you asked Him for. Had you wanted to count the bounties of God, you would not have been able to do it. The human being is unjust and disbelieving. |
| 014:034 Shakir | : |
And He gives you of all that you ask Him; and if you count Allah's favors, you will not be able to number them; most surely man is very unjust, very ungrateful. |
| 014:034 Sherali | : |
And HE gives you all that you ask of HIM, and if you try to count the favours of ALLAH, you will not be able to number them. Verily man is very unjust, very ungrateful. |
| 014:034 Yusufali | : |
And He giveth you of all that ye ask for. But if ye count the favours of Allah, never will ye be able to number them. Verily, man is given up to injustice and ingratitude. |
Concepts/Themes Covered: أركان الإسلام > التوحيد > توحيد الله تعالي > وحدانيته Pillars of Islam> Islamic> Oneness of Allah> Singularity and Being Unique الإنسان والعلاقات الاجتماعية > الإنسان > أحواله وأوصافه Man and The Social Relations>Man>His Cirumstances and his Specifications
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


Preparation time
less than 30 mins
Cooking time
1 to 2 hours
Serves
Serves 6
Dietary
Try the Hairy Bikers’ recipe for a classic steamed syrup sponge, simple to make and guaranteed to impress.
Generously butter the inside of a 1.2litre/2 pint pudding basin, and cut a circle about two times larger than the pudding basin diameter, of baking parchment and and aluminium foil
Spoon 50g/2oz of the golden syrup into the base of the pudding basin and set aside.
Beat the remaining 50g/2oz golden syrup, butter, sugar and lemon zest with an electric whisk until light and fluffy. Whisk in half of the eggs followed by half of the flour. Whisk in the remaining beaten eggs and flour. The mixture should be just a dropping consistency. (Add a splash of milk if the mixture is very thick.)
Spoon the mixture into the pudding basin and smooth the surface.
Pleat the baking parchment by folding over an inch of parchment in the centre. Repeat with the foil. This allows for expansion of the pudding as it cooks.
Cover the basin with the circle of baking parchment, with the pleat in the centre of the pudding. Cover the parchment with the circle of aluminium foil, again with the pleat in the centre. Tie the pudding very tightly around the rim with string. Create a carrying handle by tying the excess string across the top of the basin and tying it under the string on the opposite side – this will help you lift the pudding out of the pan once it’s cooked. Trim any excess baking paper and aluminium foil, leaving a 2.5cm/1in border, and turn the edges in on themselves to seal.
Put an upturned heatproof saucer or small trivet in a large, deep saucepan, and place the pudding basin on top. Add enough just-boiled water to the pan to come halfway up the sides of the basin. Cover the pan with a tight-fitting lid and place over a low heat. Allow to steam in the gently simmering water for 1¾ hours, adding more water to the pan if necessary. (Make sure the pan does not boil dry.)
The pudding is done when a skewer inserted into the centre of the pudding (through the aluminium foil and baking paper) comes out clean. When done, turn off the heat and carefully lift the basin from the water. Leave to stand for 5 minutes.
Cut the string from the basin and discard the aluminium foil and paper. Run a cutlery knife around the edge of the pudding to loosen the sides, carefully invert onto a deep plate and remove the basin.
To serve, spoon the extra syrup over the pudding, cut into generous wedges and serve with custard.
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Steaming a pudding
You need JavaScript to view this clip.
Wrapping a pudding for steaming


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Task Description
There is an ant and
a candy on the surface of a rectangular box. The ant
cannot fly. It can only walk on the surface of the box to
the candy. Please write a program that calculates the
distance of the shortest path from the ant to the candy.
The coordinates of the eight corners of the rectangular
box are shown in the figure below.
The initial
position of the ant can be on the top or one of the sides
of the box (including the corners). It cannot be on
the bottom. The candy is always on the top of the
box. The candy cannot be on the edges or corners of
the box (or it will fall off).
Program Input
The input to the
program is provided in prob10.in. Each input line
consists of six numbers separated by a blank. First three
numbers are the coordinates representing the position of
the ant while the remaining three numbers are the
coordinates representing the position of the candy. You
may assume these coordinates are on the surface of the
rectangular box. For example, the first line of the sample
input means that the ant is at (3,1,3) and the candy is at
(3,3,3). Assume that the data given is always valid.
Sample Input:
3 1 3 3 3 3
2.25 0 2 2.5 2 3
0 0 0 5 4 3.0
0 4 3 5 0.0 3
5 0 3 5 4.00 3
Program Output
A real number represents
the distance of the shortest path from the ant to the
candy. On the screen, print the distance accurate to two
digits to the right of the decimal point in the following
format.
Sample Output:
Shortest distance =
2.00 units
Shortest distance = 3.01 units
Shortest distance = 8.60 units
Shortest distance = 6.40 units
Shortest distance = 4.00 units
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{% extends "base-actual.html" %} {% load i18n static %} {% block meta_title %}{% trans "Rules" %}{% endblock %} {% block title %}{% endblock %} {% block main_content %} {#
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