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Application of Hadoop for Analyzing Data Using Mapper Files 6

Application of Hadoop for Analyzing Data Using Mapper Files

引用

6th international conference on contemporary computing and informatics, IC3I 2023

作者： Preethi, D. Pandey, Rajendra P. University Bangalore Karnataka Bangalore India College of Computing Science and Information Technology Teerthanker Mahaveer University Uttar Pradesh Moradabad India

ISBN: (纸本)9798350304480

In contemporary times, a substantial quantity of valuable and indeterminate data is readily accessible in numerous practical applications. This information might be used by many different industries and government agencies to get useful insights. This data has the potential to assist managers in improving their strategies and optimizing their decision-making processes. Several private enterprises and governments have started investing and funding initiatives to increase earnings and make the best use of resources. The analysis of large-scale datasets is crucial to the development and growth of future efforts, and the phrase 'big data'is used to describe such massive amounts of data. This study presents an analysis of Big Data analytics based on empirical findings. The present study involves an analysis of New York Stock Exchange data through the utilization of two mapper files within the Hadoop framework. The annual computation of the highest and lowest values of each stock exchange, as well as the mean stock price, is performed. © 2023 IEEE.

关键词： Big data data analytics Hadoop HDFS MapReduce

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Edge computing for Sustainable Energy Management: An Environmental Aspect 6

Edge Computing for Sustainable Energy Management: An Environ...

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6th international conference on contemporary computing and informatics, IC3I 2023

作者： Kanday, Rajeev Singh, Ramandeep School of Computer Science and Engineering Lovely Professional University Punjab India

ISBN: (纸本)9798350304480

The unprecedented growth of the world's population and industries has led to the ever-increasing demand for energy. However, the generation and distribution of energy have far-reaching impacts on the environment. To mitigate these impacts, sustainable energy management has become a priority for many countries. Edge computing has emerged as a promising technology that can aid in sustainable energy management. This paper explores the role of edge computing in sustainable energy management with an emphasis on the environmental aspect. The paper examines the concept of edge computing and how it can be applied to sustainable energy management. The paper also highlights the environmental benefits of using edge computing in sustainable energy management. The paper concludes that edge computing can play a significant role in sustainable energy management, particularly in mitigating environmental impacts. Complex interactions between edge devices, edge servers, and cloud data centres may explain why edge computing has received less attention to energy efficiency than cloud data centres. Reaching energy efficiency goals with edge computing requires thorough testing of edge devices, edge servers, and cloud data centres. This paper's goal is to give readers a synopsis of edge computing's history and evolution. We then shifted our focus to the fundamentals of edge computing. The study concludes with a discussion of the advantages and disadvantages of edge computing. © 2023 IEEE.

关键词： Cloud Edge Energy Efficiency Energy Management Fog Internet of Things

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A Complete Study of Methodology of Hand Gesture Recognition System for Smart Homes 4

A Complete Study of Methodology of Hand Gesture Recognition ...

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4th international conference on contemporary computing and informatics, IC3I 2019

作者： Nigam, Srishti Shamoon, Mohammad Dhasmana, Sakshi Choudhury, Tanupriya Dept. of Informatics Dehradun Uttarakhand India

ISBN: (纸本)9781728155296

Gesture Recognition is the technique that permits human to bond with the system and interconnect naturally without the use of any mechanical amenities. Gestures can be procured from movement or state but ordinarily emanates from the face or hand. Current field includes hand gesture recognition technique which is useful for processing human information which is not fetched through speech. Computer vision and image processing can be used to regulate gesture recognition. Real-Time vision-based hand gesture recognition is considered to be more attainable for Human Computer Interaction (HCI) with the use of latest evolutions in the area of technology vision and pattern determination. The incorporation of the technique of Hand Motion Acknowledgment in the control of Smart Home appliances is genuinely effective. This paper introduces a Hand Gesture Recognition System used to control shrewd home machines utilizing hand developments utilizing Hidden Markov Model Algorithm and Microsoft Kinect Sensor. © 2019 IEEE.

关键词： Domestic appliances

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A Review on Network Security Challenges and the Internet of Things (IoT) 4

A Review on Network Security Challenges and the Internet of ...

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4th international conference on contemporary computing and informatics, IC3I 2019

作者： Khurana, Madhu Choudhury, Tanupriya Malik, Priyanka Queen's University School of Electronics Belfast United Kingdom Dept. of Informatics UPES Dehradun India Amity University Uttar Pradesh India

ISBN: (纸本)9781728155296

In this paper a wide range of research work is analyzed in order to discuss the issues of network security in the Internet of Things (IoT). IoT seems to be delivering a steep change in Quality, productivity and utilization of resources. With its diverse distributed, intelligent smart devices IoT has the capability to improve basic features beyond our imagination in medical and healthcare to transportation and the likes, with a novel IoT network ecosystem for applications. This voluminous connectivity has led to multiple challenges and issues with reference to traditional network architecture ranging from heterogeneity, configuration, TCP/IP protocol stack, scalability, security and privacy to resource optimization. To start with, IoT is defined, IoT network specification is analyzed from various parameters, followed by a discussion of current research trends and possible future directions. The goal of this work is to discuss the various research tasks undertaken in this direction. © 2019 IEEE.

关键词： Internet of things

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Towards a model for the quality of local government online services 2

Towards a model for the quality of local government online s...

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2nd international conference on contemporary computing and informatics, IC3I 2016

作者： Sá, Filipe Gonçalves, Joaquim Rocha, Álvaro LIACC - Artificial Intelligence and Computer Science Laboratory Porto Portugal Department of Informatics Engineering University of Coimbra Coimbra Portugal

ISBN: (纸本)9781509052554

E-services provided by local governments should offer quality services with a great degree of proximity to people and companies. These services must be provided with the highest level of quality, and proper tools must be developed with a view to this end. In this sense, this paper sets forth the results obtained after applying a first round of the Delphi Method process towards the development of an evaluation model for the quality of local government online services. In this first round, we submitted a list of thirty quality dimensions divided amongst four domains to a group of fifty local e-government experts. The results obtained led us to exclude one dimension and assign a set of twenty two dimensions to their respective domains. Additionally, the results reveal a certain degree of hesitation as to the domain assigned to seven dimensions. Three new dimensions emerged. © 2016 IEEE.

关键词： E-Government E-Services Local Government Public Services Service Quality

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ANN based Semantic Content Based Image Retrieval with Distributed Processing

ANN based Semantic Content Based Image Retrieval with Distri...

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proc 2014 inter conf contemporary comp informatics (ic3i)

作者： Karande, Supriya Jalindar Maral, Vikas KJ Coll Engn & Management Res Dept Comp Engn Pune Maharashtra India

ISBN: (纸本)9781479966295

Content Based Image Retrieval (CBIR) has been one on the state of the art research area in the field of image processing since last decade. The bottleneck of present CBIR scheme is the existence of semantic gap between low level features and high level user semantic concepts about image. In state of the art articles methods has been proposed on reduction of semantic gap in CBIR. Semantic CBIR technique requires huge amount of computing power. In this paper we propose Artificial Neural Network (ANN) based distributed processing architecture for Semantic CBIR. Effectiveness of proposed mechanism in terms of precision is improved using learning through feedback during browsing results. Proposed distributed processing in this paper results into fast retrieval of images. Proposed system is evaluated over LAN and implementation results shows improvement in retrieval time and precision.

关键词： ANN CBIR Semantic gap Cloud computing Image retrieval Relevance Feedback

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Performance Analysis of Variants of Naïve Bayes Classifier to Identify Classes of Flowers Using Iris Recognition System 6

Performance Analysis of Variants of Naïve Bayes Classifier ...

引用

6th international conference on contemporary computing and informatics, IC3I 2023

作者： Gobi, N. Sharma, Anu University Karnataka Bangalore India College of Computing Science and Information Technology Teerthanker Mahaveer University Uttar Pradesh Moradabad India

ISBN: (纸本)9798350304480

Iris recognition is a biometric authentication technique that utilizes distinctive iris features to verify and identify individuals. It is not related to the identification of variants of species of flowers. The utilization of iris texture presents several benefits such as sustained stability, user-friendliness, and exceptional precision in identification. The extraction of effective features is considered the most crucial stage in the iris recognition system. A significant proportion of preceding techniques for iris recognition feature extraction relied on manually engineered features. The present study aims to explicate the process of constructing a proficient iris recognition system, which involves several phases of design. The process entails comprehending and delineating the issue, preparing and scrutinizing the data, implementing three iterations of the Naive Bayes algorithm, specifically Gaussian, Bernoulli, and Multinomial, and subsequently forecasting the precision of the system. © 2023 IEEE.

关键词： features extraction Gaussian Naïve Bayes Iris recognition Multinomial and Bernoulli

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Web based and voice enabled IVRS for large scale Malayalam speech data collection

Web based and voice enabled IVRS for large scale Malayalam s...

引用

2014 international conference on contemporary computing and informatics, IC3I 2014

作者： Devi P., Shobana Das, Divya Stephen, Jose Bhadran, V.K. Centre for Development of Advanced Computing Trivandrum India

ISBN: (纸本)9781479966295

Speech corpora are vital resource in development and evaluation of automatic speech recognition systems, as well as for acoustic phonetic studies. Collecting a huge corpus is not an easy task. The lack of such resources is one of the reasons for the absence of good quality speech recognition systems in Indian languages. Here we have automated such process by developing web based tool for collecting broad band speech data and an IVR system with speech recognition for collecting narrow band speech data. The main features includes the full support for the typical recording, annotation and project administration workflow, easy editing of the speech content, with an advantage of a fully localizable user interface. This paper describes in detail the development of web based speech collection tool and an IVR system which will enable end-to-end building of speech corpus with minimum manual effort. © 2014 IEEE.

关键词： Speech recognition

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Advancing Personalized Medicine - An Innovative Feature Engineering for Tailored Drug Design 7

Advancing Personalized Medicine - An Innovative Feature Engi...

引用

7th international conference on contemporary computing and informatics, IC3I 2024

作者： Mallavarapu, Jashritha Reddy Navanithi, V.K. Bejjanki, Mohit Manomay Mithun Menon, M. Jeyakumar, G. Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350350067

This paper introduces a pioneering approach integrating Advanced Encryption Standard (AES) security algorithms with multi-objective drug design, aimed at personalized medicine and optimized drug discovery. By leveraging comprehensive patient profiles including genetic markers and medical histories, machine learning and optimization algorithms generate personalized treatment plans and drug efficacy scores. Key objectives include establishing a robust multi-objective optimization framework, enhancing drug efficacy, ensuring data security with AES encryption, and elevating patient care quality. The methodology emphasizes customizing medicines based on individual patient data, employing AES security measures, and optimizing treatments for effectiveness, paving the way for a patient-centric, secure healthcare paradigm beyond traditional drug design methodologies. © 2024 IEEE.

关键词： Drug discovery

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Prediction of Defective Artifacts by Removing Redundant Metrics in Software Development Life Cycle (SDLC) 6

Prediction of Defective Artifacts by Removing Redundant Metr...

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6th international conference on contemporary computing and informatics, IC3I 2023

作者： Gupta, Rupal Ganesh, D. College of Computing Science and Information Technology Teerthanker Mahaveer University Uttar Pradesh Moradabad India University Karnataka Bangalore India

ISBN: (纸本)9798350304480

Software defect prediction (SDP) models aid software testing teams in forecasting faulty artifacts prior to actual testing. Software Development Process (SDP) models aim to comprehend previous shortcomings based on software metrics data that resulted in faulty modules. Previous research has determined that defect prediction models constructed without eliminating superfluous metrics yield unforeseen outcomes. This study examines the effect of superfluous metrics on the defect prediction performance of different software development processes. Through the analysis of five publicly available datasets containing system defects, it was determined that significant portions of the metrics examined were found to be superfluous and had only a negligible impact on predictive capabilities. The aforementioned observation leads to the inference that the development of a proficient defect prediction model necessitates the elimination of superfluous metrics from the datasets. © 2023 IEEE.

关键词： CfSubset evaluation Redundancy analysis SDLC WEKA

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