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检索条件"机构=Centre For Development of Advanced Computing"

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Modified Phase Shift Control for Dual Active Bridge to achieve switching loss reduction in the High Voltage side active converter

Modified Phase Shift Control for Dual Active Bridge to achie...

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International Conference on Power Electronic Drives

作者： P Ganesan Manju R Kamalesh Hatua Centre for Development of Advanced Computing Thiruvananthapuram India Indian Institute of Technology Madras Chennai India

The Dual Active Bridge (DAB) is getting greater attention in the research area after the introduction of Wide Band Gap devices for high frequency power converters. The DAB is one of the bidirectional converters in the High Voltage (HV) DC to Low Voltage (LV) DC conversion with galvanic isolation, is widely preferred for industry applications. The Power flow between the active converters is established by popular phase shift control. The reduction of switching losses by Zero Voltage Switching (ZVS) and Zero Current Switching (ZCS) techniques is not simultaneously possible in the phase shift control by keeping the LV side DC voltage constant. Hence, higher losses and reduction in efficiency. In this paper a modified phase shift control is proposed with ZVS control loop to judiciously maintain the ZVS/ZCS for the HV side converter active switches. The proposed control dynamically controls the LV side DC voltage for varying load to supplement the required reactive power from the LV side of the converter. This paper mainly emphasizes on the estimation of ZVS control for varying load and the controller implementation in the real time control hardware. The control implementation methodology is discussed with the support of necessary experimental results presented in the paper

关键词： Photonic band gap Switching loss Bridge circuits Switches High-voltage techniques Zero voltage switching Control systems

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Detection Of Malignant Cancerous Nuclei Using Quantum Hadamard Edge Detection Algorithm

Detection Of Malignant Cancerous Nuclei Using Quantum Hadama...

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IEEE Punecon

作者： Arsheyee Shahapure Rajat Gupta Prathamesh Bhole Vethonulu Losu Madhura Kulkarni Anindita Banerjee Dept. of Computer Science MIT-WPU Pune India Centre for Development of Advanced Computing Pune Maharashtra India Centre for Translational Cancer Research Prashanti Cancer Care Mission & IISER Pune Maharashtra India

ISBN: (数字)9798331527822

ISBN: (纸本)9798331527839

Cancer is a hazardous ailment, becoming even more ominous due to its capacity to remain unnoticed. The significance of cancer research lies in its role in enhancing both the detection and treatment of this disease, ultimately leading to improved quality of life for affected individuals. The process of edge detection assumes a pivotal role in image processing, as it aids in the identification of object boundaries within images. In recent years, quantum computing has garnered substantial attention for its potential to address complex problems more efficiently than classical computers. In this work, we employed edge-detection technique to annotate images related to breast cancer. We have attempted the portion of cancerous nuclei in one biopsy data sample with several malignant nuclei and validated these findings through manual examination. We have used Quantum Hadamard Edge Detection Algorithm (QHED) to identify the nuclei edges. We implemented the algorithm on quantum simulator platforms ie qiskit and Amazon Web Services (AWS). We present the results from implementation on 4 qubits in AWS simulators i.e. State Vector (SV) Simulator and Density Matrix (DM) Simulator. In qiskit implementation, the algorithm was implemented on 4096 x 4096 pixels of biopsy image, that required 24 qubits in the qiskit platform when performing on a CPU. Further, the research presented herein compares the outcomes of Canny edge detection and the results achieved through quantum edge detection from real data and we observe that the results from the quantum approach are at par with the results obtained from the classical approach.

关键词： Computers Accuracy Web services Image edge detection Image processing Biopsy Qubit Transforms Prediction algorithms Vectors

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A Novel Forensic Methodology for SQLite Database Carving

A Novel Forensic Methodology for SQLite Database Carving

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IEEE India Conference (INDICON)

作者： Gargee Handique Satheesh Kumar S Jinu Kumar S V Priyanka V S Cyber Security Group(CSG) Centre for Development of Advanced Computing(C-DAC) Thiruvananthapuram India

ISBN: (纸本)9781665452724

The cellphones utilize SQLite to store communication as well as other data records. It is a type of small database software that is commonly found in embedded systems and application softwares. In recent years, there has been an increase in the availability of portable devices like smartphones, contributing to the expanding adoption of SQLite. This indicates that the probability of finding SQLite database files in digital evidences is very high. The forensic investigators could get treasures of evidential artifacts from the SQLite database file. This paper explores the SQLite database format and structure of lost data from an Android phone and proposes a novel methodology for recovering deleted data from unallocated space, freelist and freeblocks in SQLite database files. The proposed methodology is found very effective for recovering deleted data from SQLite database files.

关键词： Embedded systems Databases Forensics Application software Task analysis Smart phones

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A Forensic Methodology for the Analysis of Twitter Application in Android Devices

A Forensic Methodology for the Analysis of Twitter Applicati...

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IEEE Punecon

作者： Priyanka V S Satheesh Kumar S Cyber Security Group(CSG) Centre for Development of Advanced Computing(C-DAC) Thiruvananthapuram India

ISBN: (纸本)9781665498982

Twitter is one of the major social networking platforms used by millions of users every day. On every second, around 6000 tweets are sent through Twitter. The forensic analysis of Twitter application is of utmost importance to crime investigators as it can contain a rich set of evidential artefacts. The physical acquisition of Android devices can unveil the forensic artefacts stored in the Twitter application database, but only the most recent tweets and messages. This paper introduces a new methodology to forensically extract Twitter cloud data using the access tokens present in Android devices. The tokens enable investigators to get authenticated access to Twitter cloud servers and further access to the entire data using Twitter APIs. The response data is encoded in JavaScript Object Notation (JSON) format, which is further analyzed to identify the attributes of each tweet object.

关键词： Social networking (online) Databases Forensics IEEE Sections Blogs Servers Object recognition

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Design and development of Industrial Vision Sensor (IVIS) for Next Generation Industrial Applications

Design and Development of Industrial Vision Sensor (IVIS) fo...

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IEEE India Conference (INDICON)

作者： Jerry Daniel J Lijo Thomas Lajitha C S Jacob T Mathew Jithin S Anju Mohan Kichu S Kumar Control & Instrumentation Group Centre for Development of Advanced Computing (C-DAC) Thiruvananthapuram Kerala India

ISBN: (纸本)9781665452724

Industrial automation is undergoing a tremendous change due to the proliferation of the concepts, the Internet of Things (IoT), Cyber-Physical Systems (CPS) and tactile internet, which enables the interconnections of factory floor devices and enterprise network on a wider and fine-grained scale. Vision Sensor deployments are getting great momentum in factories, as it improves the quality and productivity of the systems being inspected. Smart Vision Sensors[1] removes the need of the additional infrastructures for running the image processing algorithms and vision applications, by directly running the vision logic on the device and control/monitor the various parameters on the field based on the image processing outputs. Industrial vision sensor (IVIS) is an industrial smart camera, which has a CMOS image sensor[2] and a powerful on-board processing system capable of supporting machine vision applications, for improving the product and process qualities and thereby improve the yield and profit. IVIS is capable of extracting application-specific information from the captured images and make decisions based on the image processing algorithms implemented on the system, to realize stand-alone intelligent and decision-making automation system. In this paper we present the design and development of IVIS, its application domains and preliminary test results.

关键词： Tactile Internet Productivity Automation Machine vision Decision making Smart cameras Vision sensors

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Identifying Sybil Attacks in Blockchain Networks through Behavioral Analysis and Zero Knowledge Proof implementations

Identifying Sybil Attacks in Blockchain Networks through Beh...

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Data, Computation and Communication (ICDCC), International Conference on

作者： R Giridhar Reddy Pushpinder Singh Pateja Adarsh Patel Gopinath Palaniappan Balaji Rajendran School of Computer Science and Engineering Vellore Institute of Technology Bhopal Bhopal India Centre for Development of Advanced Computing (C-DAC) Bangalore Resilient Information Systems Engineering Bengaluru India

ISBN: (数字)9798331532956

ISBN: (纸本)9798331532963

Blockchain technology is significant because it makes data sharing between several parties safe, transparent, and effective. Multi-step transactions that require verification and traceability can benefit from Blockchain technology. However, the Blockchain technology too comes with its own vulnerabilities and often Blockchain networks are attacked by attacks like 51% Attack, Eclipse Attack, Sybil Attack, Time jacking Attack, Selfish Mining Attack, Finney Attack, Race Attack and so on. One among those attacks is the Sybil attacks, which are a big threat to the integrity of Blockchain networks since they assist malicious actors to create several identities, potentially overwhelming the system and defeating the very principle of consensus mechanisms. In this paper, we have captured an approach on designing a multi-layered mechanism for identifying Sybil attacks with the integration of behavioral analysis, Blockchain analysis techniques, Zero-Knowledge Proofs (ZKPs), and a robust security architecture for governance and validator selection. The broad idea is to cancel pseudo-anonymity in the Blockchain systems by detecting behavioral patterns, identifying exchange wallets, and mapping inter-wallet relationships. Integration of these approaches with ZKPs assists in improving identity verification while simultaneously maintaining user anonymity. The proposed architecture for security uses community-based governance and adaptive validator selection processes to strengthen the defense against Sybil attacks. Token concentration analysis traces down the distribution of stakes within the network in order to find potential risks due to centralization. Our findings thus conclude that integration of the security framework along with behavior analysis and ZKPs effectively reduces the proliferation of fraudulent identities in the Blockchain networks.

关键词： Focusing Computer architecture Blockchains Fraud Consensus protocol Security Stakeholders Ransomware Data mining Zero knowledge proof

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Machine Learning Based Framework for Cryptocurrency Price Prediction

Machine Learning Based Framework for Cryptocurrency Price Pr...

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International Conference on Secure Cyber computing and Communication (ICSCCC)

作者： Mrityunjay Singh Amit Kumar Jakhar Aashima Juneja Shivam Pandey School of Computing Indian Institute of Information Technology Una Una India Department of CS/IT Jaypee University of Information Technology Waknaghat Solan India Centre for Development of Advanced Computing Noida Noida India

Cryptocurrency, a digital currency, acts as a medium of exchange through the Internet. The main agenda behind cryptocurrency being so popular these days is the desire for reliable, long-term value without the involvement of any central authority like banks. The power lies in the hands of the currency holders which resolve the problems of the traditional currencies by adopting a decentralized system. Predicting the future price of different cryptocurrencies is a prominent area of interest for individuals or investors. In this work, we use a dataset collected from the coinmarketcap website for the duration of September 2014 to March 2022. The outcome of this work is compared to the existing algorithms for time series data analysis namely the Auto Regressive Moving Average Model (ARIMA), FbProphet, and several ensemble models on the basis of their accuracy in predicting the future price. We also create different ensemble frameworks for the prediction of the cryptocurrency price. To form the ensemble models, we initially select the three best-performing regression models on the dataset, namely Extra Trees, Random Forest, and Decision Trees Regressors. Our findings indicate that the ARIMA model performs better than the ensemble model with the lowest RMSE MAE and MSE.

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Evaluation of automatic text visualization systems: a case study 5th

Evaluation of automatic text visualization systems: a case s...

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5th International Conference on advanced Machine Learning Technologies and Applications, AMLTA 2020

作者： Jain, Priyanka Bhavsar, R.P. Shaik, Karimullah Kumar, Ajai Pawar, B.V. Darbari, Hemant Bhavsar, Virendrakumar C. Centre for Development of Advanced Computing Pune India KBC-North Maharashtra University Jalgaon India University of New Brunswick FrederictonNB Canada

ISBN: (纸本)9789811533822

We have developed an automatic text visualization (ATV) system, named Preksha, that takes natural language text in Hindi as input and produces a run-time interactive 3D scene based on it. Preksha is the only ATV system which deals with complex processing of morphologically rich input in Hindi, a language of free-word-order nature. Its design and approach make Preksha extendible to other Indian languages. In this paper, we present challenges for evaluation of an ATV system and propose a subjective evaluation methodology. This evaluation design includes intelligibility, fidelity and complexity aspects of the scenes generated. Subsequently, Preksha is evaluated by using a total of 10,220 user responses through an online evaluation survey. The results show that Preksha is able to generate scenes with very high levels of intelligibility and fidelity. © Springer Nature Singapore Pte Ltd 2021.

关键词： Natural language processing systems

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Accelerated Sorting of Apples Based on Machine Learning 4th

Accelerated Sorting of Apples Based on Machine Learning

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4th International Conference on Smart computing and Informatics, SCI 2020

作者： Deb, Kiron Basu, Shobhin Palakurthy, Vamshi Krishna Bhattacharyya, Nabarun Calcutta International School Kolkata India Fremont High School Sunnyvale CA United States Centre for Development of Advanced Computing Kolkata India

ISBN: (纸本)9789811608773

Accurate classification and grading are important for the quality assurance of apples since it is necessary to ensure that they retain their freshness and texture until they reach the end user following transportation and storage. We demonstrate that machine learning makes it feasible to separate high-quality apples from the poor-quality ones, which have signs of rotting, insect damage, and other forms of degradation. An alternative to the prevalent manual process of sorting and classification of apples is proposed. We focus on apples grown in orchards in Kashmir and USA. We analyze images taken following harvest using two machine learning models—an open source model as well as a well-known commercial tool. We also propose a hybrid approach for sorting perishable inventory that streamlines the process by using a high-throughput sorter based on image classification. We weed out the apples with surface blemishes in the sorting stage to identify potentially premium grade apples. The apples sorted by our approach are further screened by existing industry-standard procedures such as manual sorting or automated processes like acoustic analysis for classification into different grades. Using this two-step approach, we reduce the time for isolating the higher quality apples compared to a process that relies on a single-step sorting process only. This also achieves greater consistency and economies of scale. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer vision

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Proposing ϵ-greedy Reinforcement Learning Technique to Self-Optimize Memory Controllers 2

Proposing ϵ-greedy Reinforcement Learning Technique to Self...

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2nd International Conference on Secure Cyber computing and Communications, ICSCCC 2021

作者： Ray, Aritra Ray, Hena University of Calcutta A. K. C. School of Information Technology Kolkata India Centre for Development of Advanced Computing Kolkata India

ISBN: (纸本)9781665444156

This paper proposes the novel algorithmic idea of ϵ-greedy based Reinforcement Learning (RL) technique to self-optimize memory controllers. It aims to overcome the limitations of the existing RL based self-optimization of memory controllers by significantly reducing the space complexity and power requirements, while considering all the formulation constraints of the aimed problem. The proposed RL based DRAM scheduler is in line with the asymptotic correctness solution approach and does long-term planning so as to maximize the utility of the bus in the long run, while balancing exploration versus exploitation, providing room for interleaving of requests from different cores, optimizing the read and write requests and allowing precedence considering the criticality of each request. We have mathematically explained in this paper, and thereafter formulated the detailed algorithm, to exhibit how our proposed design of the RL based DRAM scheduler would bring about significant improvement in the existing design. © 2021 IEEE.

关键词： Dynamic random access storage

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