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5th IEEE India Council International Subsections Conference, INDISCON 2024

作者： Shajahan, Rasha Jain, Kurunandan Aneesh Kumar, K.B. Krishnan, Prabhakar Amrita Vishwa Vidyapeetham Amritapuri-campus Center for Cybersecurity Systems and Networks India Center for Development of Advanced Computing Cyber Security Group Kerala Thiruvanathapuram India

ISBN: (纸本)9798350376753

Quantum Key Distribution (QKD) is a secure communication method that uses quantum mechanics to exchange secret keys. Currently, the QKD process uses a static error correction method, which can lead to inaccuracies and inefficient resource use. The project aims to develop a new QKD error correction method that adapts dynamically based on real-time Quantum Bit Error Rate (QBER) measurements and Software Defined Networking (SDN) principles. Two specific error correction mechanisms, the 2D Parity check and the Cascade Protocol, will be used to match the QBER value. The investigation will be conducted using the DARPAN application, providing a quantum-enabled environment. © 2024 IEEE.

关键词： Quantum cryptography

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Multiple alignment of sequences on parallel computers

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Bioinformatics 1993年第4期9卷 397-402页

作者： Date, Shashank Kulkarni, Rajendra Kulkarni, Bhavana Kulkarni-kale, Urmila Kolaskar, A.S. Center for Development of Advanced Computing DIC Department of Zoology University of Poona Pune 411 007 India Center for Bioinformatics DIC Department of Zoology University of Poona Pune 411 007 India

A software package that allows one to carry out multiple alignment of protein and nucleic acid sequences of almost unlimited length and number of sequences is developed on C-DAC parallel computer-a transputer-based machine. The farming approach is used for data parallelization. The speed gains are almost linear when the number of transputers is increased from 4 to 64. The software is used to carry out multiple alignment of 100 sequences each of α-chain and β-chain of hemoglobin and 83 cytochrome c sequences. The signature sequence of cytochrome c was found to be PGTKMXF. The single parameter, multiple alignment score, S, has been used to categorize proteins in different subfamilies and groups. © 1993 Oxford University Press.

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Handwritten Assamese numeral recognizer using HMM & SVM classifiers

Handwritten Assamese numeral recognizer using HMM & SVM clas...

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2013 National Conference on Communications, NCC 2013

作者： Sarma, Bandita Mehrotra, Kapil Krishna Naik, R. Prasanna, S.R.M. Belhe, Swapnil Mahanta, Chitralekha Department of Electronics and Electrical Engineering Indian Institute of Technology Guwahati Guwahati 781039 India Center for Development of Advanced Computing GIST Pune India

ISBN: (纸本)9781467359528

This work describes the development of Assamese online numeral recognition system using Hidden Markov Models (HMM) and Support Vector Machines (SVM). Preprocessed (x, y) coordinates and their first and second derivatives at each point are used as features for both the modeling techniques. The two systems are developed individually using HMM and SVM. The results from both the systems are then combined using two different approaches. In the first approach, the scores from both the classifiers are directly merged and an improvement in performance is observed in the combined system (Comb - 1). In the second approach, the confusion patterns from HMM and SVM classifiers are also analyzed. Based on this, the results are further combined to obtain a final hybrid numeral recognizer with an enhanced performance (Comb - 2). The HMM, SVM, Comb-1 and Comb-2 systems provide average recognition performance of 96.5, 96.8, 98 and 98.3, respectively. © 2013 IEEE.

关键词： Hidden Markov models

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Overview of Neural Machine Translation for English-Hindi

Overview of Neural Machine Translation for English-Hindi

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2019 IEEE International Conference on Issues and Challenges in Intelligent computing Techniques, ICICT 2019

作者： Singh, Shashi Pal Darbari, Hemant Kumar, Ajai Jain, Shikha Lohan, Anu Center for Development of Advanced Computing AAIG Pune India Krishna Institute of Engineering and Technology Ghaziabad India Banasthali Vidyapith BanasthaliRajasthan India

ISBN: (纸本)9781728117720

Artificial intelligence is getting shrewd in real time with massive amounts of computational power and high in demand in last quarter more than billion dollars. The Intensification of Neural Networks in Machine learning playing major revolution in Machine Translation (MT). Looking same aspect, we have prepared a paper on Machine Translation for Hindi using Neural Machine Translation techniques. The Basis of this paper is to translate the source language into target language with the help of sentence structure for source language (English sentence) and corresponding reordering rules for target language (Hindi sentence) using a deep neural network (DNN).When the source input that is English sentences are exactly matched with the target language database then the suitable translation for related input is directly fetched from the database. The fuzzy matching between the input sentence and the sample sentence in the database is done with cosine similarity between the sentence structure of input sentence and the sample sentence and then the reordering rule of the most alike sentence to the input sentence is used for *** the structure of the source language sentence and extracting the reordering rule for target sentence is the core part of the translator. Reordering of words in spite of that remains one of the complex *** is exciting to implement Deep Neural Network and fuzzy logic to build intelligent reordering rules machine learning system. © 2019 IEEE.

关键词： Neural machine translation

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Secure Multi-party kNN Search in Large-scale Spatial Data Federation

Secure Multi-party kNN Search in Large-scale Spatial Data Fe...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Zhang, Yuanyuan Shi, Yexuan Zhou, Nan Xu, Yi Xu, Ke Beihang University State Key Laboratory of Software Development Environment Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beijing China

ISBN: (纸本)9781665480451

kNN is a fundamental query in various location based services such as POI recommendation and ride planning. There is an increasing demand to scale such services by querying over a data federation, where the entire dataset is distributedly held by multiple data providers (a.k.a., silos), and each silo keeps its data partition private. However, it is challenging to provide secure kNN queries over a large-scale data federation. Prior secure kNN queries can be are highly inefficient if performed cross silos because they involve excessive secure distance operations, which can be two or three orders of magnitude slower than the corresponding plaintext operations. In this work, we propose a novel threshold based framework for efficient kNN queries over a spatial data federation. The key idea is to rewrite excessive secure distance computations as light-weight secure operations. We further propose an adaptive threshold algorithm to reduce the secure communication rounds and accelerate the query processing. Extensive evaluations on both synthetic and real-world datasets show that compared with the state-of-the-art secure kNN querying methods, our solutions reduce the time cost by up to 104.1 times and communication cost by three orders of magnitude. © 2022 IEEE.

关键词： Location based services

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Quantitative Analysis of EEG Neurofeedback using optimized 1-DPSO 10

Quantitative Analysis of EEG Neurofeedback using optimized 1...

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10th International Conference on Signal Processing and Integrated Networks, SPIN 2023

作者： Waghmare, Ms. Kiran Malhotra, Meenakshi Reeja, S.R. Center for Development of Advanced Computing Mumbai India Dayananda Sagar University Bengaluru India Ap University School of Computer Science and Engineering India

ISBN: (纸本)9781665490993

Brain-Computer Interface (BCI) systems are the leading technology in the world related to Neurosciences. Human intelligence and imagination have no bounds and this has led to vast advancement in BCI systems related to Neurological and allied sciences. This system measures the activity of the Central Nervous System (CNS) using biosignals and output is called Electroencephalography (EEG). The main purpose of BCI is to acquire EEG brain signals, identify patterns, extract features, and produce resultant actions. This process communicates with a modest electronic system designed for movements of physically challenged or paralyzed people. The purpose of this BCI system is to design a model to check the attention level of body movement. The movements are based on the EEG signals captured from the 19-electrode EEG headset. This allows gaining control over optimized real-time feature selection for EEG signals. The dataset of 30 subjects' sample EEG signals is recorded for classification and analysis purpose. The EEG signals are classified using Logistic Regression, Decision Tree, and Random Forest algorithms. It is shown that Random Forest is the most efficient classifier with the highest accuracy of 99.47%. © 2023 IEEE.

关键词： Electroencephalography

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Fault-tolerant energy scheduling system

Fault-tolerant energy scheduling system

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International Conference on Power Systems (ICPS)

作者： Lagineni Mahendra Katta Jagan Mohan R.K. Senthil Kumar G.L. Ganga Prasad C-DAC Center for Development of Advanced Computing Bangalore INDIA Centre for Development of Advanced Computing Pune Maharashtra IN

ISBN: (纸本)9781509001293

Scheduling is very important and essential process for the State Load Dispatch centers to generate various schedules like entitlements, declared capability, injection and drawl schedules etc. for disciplined management of power. Scheduling system is required for state load dispatch centers (SLDC) and their state-sector generating stations, distributed companies/beneficiaries throughout the clock because schedules can change regularly with an hour in advance. Scheduling system should provide its continuous service in the event of the failure of any of its components. So to achieve fault tolerance for scheduling system, the clustering and load balancing approach is used.

关键词： Schedules Web servers Scheduling Fault tolerant systems Open Access Systems operation

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ALDIMS - A Language for Programming Distributed Memory Multiprocessors

ALDIMS - A Language for Programming Distributed Memory Multi...

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Distributed Memory computing Conference

作者： K.G. Kumar D. Kulkarni A. Basu A. Paulraj Center for Development of Advanced Computing Bangalore India

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A library environment for distributed memory multiprocessors

A library environment for distributed memory multiprocessors

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International Symposium on Parallel Processing

作者： M.K. Kumar P.S. Kumar A. Basu Center for Development of Advanced Computing Bangalore India

The authors propose the design of a library environment, called PARUL (PARallel User Library), for distributed memory multiprocessor systems. An important feature of the environment is that it allows the data distributed for use of a library function as well as the results generated by the function to be retained in the network of processors to be used by subsequent library functions. The user of the library is given full control over the set of variables that are retained in the network. The authors describe the implementation details of PARUL on a multi-transputer system (PARAM) and discuss its performance.< >

关键词： Multiprocessing systems Software libraries Hypercubes Concurrent computing Distributed computing Multiprocessor interconnection networks Costs Scalability Parallel programming Computer networks

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Data partitioning schemes for the parallel implementation of the revised simplex algorithm for LP problems

Data partitioning schemes for the parallel implementation of...

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International Symposium on Parallel Processing

作者： U. Sridhar A. Basu Center for Development of Advanced Computing Bangalore India

The parallel implementation of the revised simplex algorithm (RSA) using eta-factorization holds the promise of significant improvement in the execution time by virtue of the existence of a high degree of parallelism in the computation within an iteration of the algorithm. However, the scheme employed to partition key data structures in a distributed memory parallel processor has a great impact on the achievable performance. The paper explores the trade-offs between block-row and block-column partitioning schemes for the matrix of constraint coefficients vis-a-vis the communication overheads and granularity of parallel computations. The results of an approximate analysis of the compute-communication balance are compared with measurements from practical implementation of the partitioning schemes on C-DAC's PARAM 8000 distributed memory parallel processor.< >

关键词： Partitioning algorithms Concurrent computing Costs Data structures Distributed computing Memory management Linear programming Engineering management Parallel processing Acceleration

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