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9th IEEE International Conference on Power Electronics, Drives and Energy Systems, PEDES 2020

作者： Abhijith, N. Subhash Joshi, T.G. John, Vinod Indian Institute of Science Electrical Department Bengaluru India Power Electronics Group Centre for Development of Advanced Computing Thiruvananthapuram India Indian Institute of Science Department of Electrical Engineering Bengaluru India

ISBN: (纸本)9781728156729

In DC-DC converters like Dual Active Bridge (DAB) and Dual Active Half Bridge (DAHB) where leakage inductance also acts like power transfer inductance, it is important to have optimum leakage inductance, especially in high frequency applications. High value of leakage inductance result in high RMS current through transformer with higher conduction losses in transformer and switches, whereas, low value of leakage inductance result in loss of Zero Voltage Switching (ZVS) turn-on at lower power level with higher switching losses. This paper presents analytical derivation of minimum leakage inductance and dead-time for ZVS turn-on of switches in Current Source Voltage Source (CSVS) type of Dual Active Half Bridge (DAHB) DC/DC Converter which can be used to design optimal leakage inductance. © 2020 IEEE.

关键词： Zero voltage switching

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A novel approach for tumor segmentation for lung cancer using multi-objective genetic algorithm and connected component analysis 2nd

A novel approach for tumor segmentation for lung cancer usin...

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2nd International Conference on Data Engineering and Communication Technology, ICDECT 2017

作者： Choudhury, Ananya Subramanian, Rajamenakshi R. Sunder, Gaur High Performance Computing—Medical and Bioinformatics Application Group Centre for Development of Advanced Computing Pune India

ISBN: (纸本)9789811316098

Treatment in oncology relies heavily on imaging. Automatic identification of cancerous tumors is a challenging and time-taking task. This paper presents a multi-objective genetic algorithm for calculating optimal threshold value for binarization of CT lung images and segmentation of the tumor region using connected component analysis. The threshold determination method is tested on two public datasets: Data Science Bowl: Stage 1 and NSCLC lung cancer dataset. The results obtained are compared with other genetic algorithm approach and traditional Otsu’s method. The proposed method gives better threshold value compared to Otsu’s method and outperforms other genetic algorithm approach both in terms of threshold value and computation time. Connected component analysis is done on the labeled connected component in the binarized image. Based on predetermined geometric measurements, the components are marked as tumors and non-tumors. This method when applied to 240 cancerous images, correctly identified tumors for 205 images while showed no result where there are no tumors in the image. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Tumors

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A Need-To-Basis Dust Suppression System using Wireless Sensor Network

A Need-To-Basis Dust Suppression System using Wireless Senso...

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IEEE Recent Advances in Intelligent Computational Systems (RAICS)

作者： Arun Krishnan K Shalu R Sandeep S Jithin S Lijo Thomas Senju Thomas Panicker Jerry Daniel J Control and Instrumentation Group Centre for Development of Advanced Computing Thiruvananthapuram Kerala INDIA

ISBN: (数字)9781728190525

ISBN: (纸本)9781728190532

India being the second largest producer and importer of coal in the world, coal mining industry is one of the major contributors for the economic growth of the country. However, mining activities generate tremendous amount of dust and fines leading to air pollution, which in turn causes several health and environment hazards. Hence it is important to control the dust being generated by effective dust suppression mechanisms. One of the methods employed is sprinkling or spraying of water, which is done manually at most places. However, this method can lead to wastage of water if it is overdone or not effective enough if underdone. Automating the sprinkling systems is a way to overcome this issue. The paper proposes an automatic dust suppression system which activates sprinklers on a need-to-basis depending on the concentration of airborne dust. The system monitors the amount of coal-dust present in the atmosphere and activates the sprinklers when the dust content exceeds permissible safe limits. This paper discusses the intelligent dust suppression system consisting of a scalable network of dust sensors and wireless sensor nodes that are used to measure the dust levels at various locations of the coal mines or coal handling areas and activate the sprinklers based on area wise dust concentration.

关键词： Wireless communication Temperature sensors Wireless sensor networks Coal Sensor systems Coal mining Intelligent sensors

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Aeromonas veronii specific aptamer and peroxidase mimic tyrosine-capped gold NanoZymes enable highly specific sensing of fish pathogenic bacteria

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Biosensors and Bioelectronics: X 2024年 19卷

作者： Sarkar, Dhruba Jyoti Biswas, Ayan Mondal, Shirsak Aralappanavar, Vijay Kumar Dei, Jyotsna Sinha, Swapnil Behera, Bijay Kumar Raja, Ramij Bhattacharyya, Soumyadeb Pal, Souvik Mukherjee, Subhankar Bansal, Vipul Das, Basanta Kumar Aquatic Environmental Biotechnology Division ICAR-Central Inland Fisheries Research Institute Barrackpore West Bengal Kolkata700120 India Centre for Development of Advanced Computing-Kolkata West Bengal Kolkata700091 India IITG TIDF BioNEST Indian Institute of Technology-Guwahati Assam Guwahati781039 India School of Science RMIT University GPO Box 2476 MelbourneVIC3001 Australia College of Fisheries Rani Lakshmi Bai Central Agricultural University UP Jhansi284003 India

Despite major advances in biosensing, quick, dependable, and effective on-site detection of bacterial infections remains a serious issue, owing to a lack of acceptable or appropriate diagnostic platforms. To address this gap, we presented a new colorimetric gold NanoZyme aptasensor for rapid sensing of Aeromonas veronii, an infectious bacterial disease in fish. The A. veronii-specific aptamer (AVS01) was developed through Cell-SELEX. The sensing mechanism involves inhibition of AuNPs induced peroxidase-mimic catalytic activity through surface adsorption by AVS01 which in the presence of the A. veronii desorb from the AuNPs allowing recovery of the catalytic activity leading to colorimetric response, whereas the sensor is insesnsitive to other nontarget bacterial cells. This method is very specific and sensitive, allowing for the quick and visible sensing of A. veronii with a detection limit of 1281 CFU mL−1 within 15 min. The method has great potential for rapid diagnosis of bacterial infection in fish caused by A. veronii. © 2024 The Author(s)

关键词： Fish

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A Comparative Investigation of Clamping techniques for Bi-directional Energy Harvester Interface (BEHI)

A Comparative Investigation of Clamping techniques for Bi-di...

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International Conference on Power Electronic Drives

作者： Ramesh P Aby Joseph Arya G Lal Power Electronics Group Centre for Development of Advanced Computing(C-DAC) Thiruvananthapuram INDIA

ISBN: (数字)9781728156729

ISBN: (纸本)9781728156736

This paper presents different clamping techniques; (1) Passive (2) Active (3) Flyback snubber for Bidirectional Energy Harvester Interface (BEHI) using Isolated Boost Mode Full Bridge (IBMFB) configuration in order to mitigate the transient voltage peak or voltage overshoot caused due to parasitic elements. Simulation results verify the benefits and drawbacks of each clamping methods. An experimental prototype of BEHI converter is designed, built and tested by incorporating different clamping techniques using reconfigurable hardware structure. In this work, the experimental results of BEHI converter are verified using active clamp method around rated power of 5 kW with drastic reduction in transient voltage peak (less than 100V) and thereby achieved higher converter efficiency(~92%). The comparative investigation between passive and active clamp methods has also been experimentally carried out in the prototype hardware and highlighted in this paper.

关键词： Snubbers Bridge circuits Prototypes Switches Hardware Clamps Transient analysis

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Analysing risk of Coronary heart disease through discriminative neural networks

arXiv

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arXiv 2020年

作者： Khaneja, Ayush Srivastava, Siddharth Rai, Astha Cheema, A.S. Srivastava, P.K. Vellore Institute of Technology Vellore India Centre for Development of Advanced Computing Noida India

The application of data mining, machine learning and artificial intelligence techniques in the field of diagnostics is not a new concept, and these techniques have been very successfully applied in a variety of applications, especially in dermatology and cancer research. But, in the case of medical problems that involve tests resulting in true or false (binary classification), the data generally has a class imbalance with samples majorly belonging to one class (ex: a patient undergoes a regular test and the results are false). Such disparity in data causes problems when trying to model predictive systems on the data. In critical applications like diagnostics, this class imbalance cannot be overlooked and must be given extra attention. In our research, we depict how we can handle this class imbalance through neural networks using a discriminative model and contrastive loss using a Siamese neural network structure. Such a model does not work on a probability-based approach to classify samples into labels. Instead it uses a distance-based approach to differentiate between samples classified under different labels. The code is available at https://***/DiscriminativeCHD. Copyright © 2020, The Authors. All rights reserved.

关键词： Data mining

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Using Machine Learning to Predict the Users Ratings on TripAdvisor Based on Their Reviews

Using Machine Learning to Predict the Users Ratings on TripA...

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International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2021

作者： Carneiro, João Meira, Jorge Novais, Paulo Marreiros, Goreti GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Institute of Engineering Polytechnic of Porto Porto4200-072 Portugal CITIC – Centro de Investigación en Tecnologías de la Información y las Comunicaciones University of A Coruña A Coruña15071 Spain ALGORITMI Centre University of Minho Guimarães4800-058 Portugal

ISBN: (纸本)9783030857097

Argumentation-based dialogue models have shown to be appropriate for decision contexts in which it is intended to overcome the lack of interaction between decision-makers, either because they are dispersed, they are too many, or they are simply not even known. However, to support decision processes with argumentation-based dialogue models, it is necessary to have knowledge of certain aspects that are specific to each decision-maker, such as preferences, interests, limitations, among others. Failure to obtain this knowledge could ruin the model’s success. In this work, we intend to facilitate the acquiring information process by studying strategies to automatically predict the tourists’ preferences (ratings) in relation to points of interest based on their reviews. We explored different Machine Learning algorithms (Logistic Regression, Random Forest, Decision Tree, K-Nearest Neighbors and Recurrent Neural Networks) and Natural Language Processing strategies to predict whether a review is positive or negative and the rating assigned by users on a scale of 1 to 5. The experiments carried out showed that the developed models can predict with high accuracy whether a review is positive or negative but have some difficulty in accurately predicting the rating assigned by users. © 2021, Springer Nature Switzerland AG.

关键词： Sentiment analysis

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Polynomial based non-interactive session key computation protocol for secure communication in dynamic groups

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International Journal of Information Technology (Singapore) 2020年第1期12卷 283-288页

作者： Kumar, Vinod Kumar, Rajendra Pandey, S.K. Department of I.T Centre for Development of Advanced Computing Noida India Department of Computer Science Jamia Millia Islamia New Delhi India Department of Electronics and Information Technology Ministry of Communication and Information Technology New Delhi India

In today’s world, security is the main issue in all type of communication systems. Secure group communication is that where some members out of ‘n’, have the privilege to access the data of a particular group. The non interactive key computation for secure communication in dynamic groups is a main challenging issue. In the dynamic groups, the group size is not fixed, as the members may leave or join the group anytime. The non interactivity of the group communication says that there will not be any exchange of the keys among the group members. In this paper, we proposed a polynomial based non-interactive session key computation protocol for secure communication in dynamic groups. In the proposed protocol, the polynomial is constructed in such a way that it may be used as a generalized polynomial for ‘n’ members and may be reformed every time by the server whenever there is any change in the group membership. In addition, the security of the polynomial session key depends on the value of coefficients of the variables in polynomial. In comparison with various existing protocols our proposed protocol is efficient in terms of computation, storage and communication complexities. The graphical results shows that the no. of rounds, no. of messages passed and total no. of exponentiations are completely reduced in our protocol. © 2018, Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Dynamic systems Group communication Non-interactive Polynomial session key

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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

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Computer Systems Science & Engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the ***6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration ***6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial ***,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of *** paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential ***,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack *** results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)*** proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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Computational Analysis of Online Hate Content using Cognitive -AI

Computational Analysis of Online Hate Content using Cognitiv...

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IEEE International Conference on computing, Communication and Security (ICCCS)

作者： Naganna Chetty Sreejith Alathur Dittin Andrews Vishal Kumar School of Managemnet National Institute of Technology Surathkal Mangalore Karnataka India Centre for Development of Advanced Computing(C-DAC) Thiruvananthapuram India Bipin Tripathi Kumaon Institute of Technology Dwarahat India

ISBN: (纸本)9781665440400

As the hate content is expressed based on the identity of an individual, it is influencing communal violence in society. The inappropriate content can be detected and analyzed using automated AI systems. The purpose of this paper is to study the role of AI systems in the detection of online hate content and how the cognitive processes affect the behavior of an individual. Therefore, using related keywords in the research domain, the published articles are searched through different search engines. The information from the associated articles and sources is reported in the paper. The literature review revealed that social media platforms could use AI systems to detect and analyze online hate content. It has been observed that the cognitive process affects both the perpetrators and the victims of online hate content. The paper also highlights some of the challenges in controlling online hate content. The paper concludes with a note that the hate content can be reduced by building robust AI systems and healthier cognitive processes of an individual.

关键词： Cognitive processes Social networking (online) Bibliographies Buildings Manuals Search engines Internet

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