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Enriched Model of Intuitionistic Fuzzy Adaptive Noise Filtering on MR Brain Image

SN computer science 2023年第2期4卷 166页

作者： Srinivasan, Preethi Saroj Gurunathan, Pradeep Department of Computer Science and Engineering Anna University Chennai India Department of Computer Applications A.V.C. College of Engineering Mayiladuthurai India

MRI is one of the major modality in assisting the medical experts to diagnose and treat different brain diseases such as cancer, epilepsy and stroke. Poor light illumination of MRI scanners, electronic interferences and radiofrequency emissions cause noise in MR images. Handling such noises in MR brain images is a challenging task. To overcome the issue, this paper aims to develop an enhanced model that has the ability to handle three different types of noises namely salt and pepper noise, speckle noise and Gaussian noise. The proposed enhanced intuitionistic fuzzy adaptive filter (IFAF) model removes noises in MR brain images by categorizing pixels into membership and non-membership grade. IFAF preserves the edges and detailed information of the images by adapting contrast enhancement histogram equalization. Conventional denoising models face uncertainties in distinguishing normal and noise affected pixel of an image. The performance of IFAF is compared over different noises and the results show IFAF provides better results than the other conventional noise filtering models. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Contrast enhancement Denoising Gaussian Intuitionistic fuzzy MRI Salt and pepper Speckle noise

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An Intellectual Street Lighting System using IoT 2

An Intellectual Street Lighting System using IoT

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2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Agilbert, Jefin Rama Prasath, A. Hindustan Institute of Technology and Science Department of Computer Applications Chennai India

ISBN: (纸本)9798350315905

The proposed system's goal is to create a mechanism for the automatic regulation of public lighting by turning off the street lighting when there is adequate light from the sun, the goal is to maximize energy efficiency. A camera, light dependent resistorsensor,wi-fi sensor, and arduino are used to apply this technology where the requirement to determine whether or not there is light is required, the Light Dependent Resistor Sensor is best fitted. Circuits for alarm clocks, light metres, and security systems are among the principal uses of these resistors as light sensors. Using that sensor, street lighting is turned ON or OFF based on the intensity of the surrounding environment. ESP8266 could be used for this switching accordingto the LDR sensor. The light flashes brightly at 100% when a sensor module detects the presence of a light within a particular rangeintensity;otherwise, the intensity is reduced to 60%. The essential tenet of the functioning is the sending and receiving of data across GSM, GPRS, and GPS networks either a physical server built inside the gadget that is likewise linked to the internet, or the receiving of information and exact time from a GPS-based route planning system. © 2023 IEEE.

关键词： Cameras

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Improvisation in Opinion Mining Using Negation Detection and Negation Handling Techniques: A Survey 8th

Improvisation in Opinion Mining Using Negation Detection and...

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8th International Conference on Soft Computing: Theories and applications, SoCTA 2023

作者： Makkar, Kartika Kumar, Pardeep Poriye, Monika Department of Computer Science and Applications Kurukshetra University Haryana Kurukshetra India

ISBN: (纸本)9789811998577

Negation handling is one of the challenges of natural language processing. Nowadays, negation detection and negation handling have significance in numerous fields like sentiment analysis, chat-bots, etc. In this digital era, a huge amount of data is generated from e-commerce websites, social media, etc. In order to perceive the sentiments from this data, an accurate classification of data is required, but in the opinion mining, stopwords are removed during preprocessing step and most of the negative words are removed from the text. Negation words are mostly responsible for flipping the polarity of sentences and if removed in preprocessing may cause incorrect classification of sentences or documents and result in inaccurate predictions. Negation handling is used in many domains and among all medical domains is a crucial domain. If it is not used, in the medical domain may produce wrong predictions about the disease of the patient and may prove to be fatal. Before the era of machine learning and deep learning, mainly rule based and lexicon approaches were used and these approaches were domain dependent. With the advent of machine learning and deep learning, more emphasis has been exercised on negation handling. Negations are mainly of two types implicit and explicit, and these negations can be handled using various approaches such as rule based, lexicon based, machine learning, deep learning, and hybrid. This article presents an overview of various negation detection and negation handling techniques existing in literature to get an insight into negation detection and negation handling. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Sentiment analysis

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Streaming Big Data with Open-source: A Comparative Study and Architectural Recommendations 2

Streaming Big Data with Open-source: A Comparative Study and...

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2nd International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2023

作者： Vijayakumar, G. Bharathi, R.K. Jss Science and Technology University Department of Computer Applications Mysuru India

ISBN: (纸本)9781665491990

This study focusses on providing state-of-the-art infrastructure for data pipelines in e-Commerce sector, especially for online stores. With people going digital and also latest impact of Covid-19, daily e-Commerce companies are dealing with large amount of data (terabytes to petabytes). With growing Internet of Things, systems of computing devices which are interrelated. The inter-relation may be between mechanical and digital machines, objects or people. The interrelated objects will be provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. Growth of big data poses several challenges and opportunities in every field of its usage. Realtime analysis of data and its inference gives a competitive edge over its partners in every business field especially in e-commerce. Recent advances in technology and tools have exposed new opportunities to get actionable insights from historical data like market data, customer demographics, along with real-time data. Advancement in distributed streaming technology makes it important to investigate existing streaming data pipeline capabilities in eCommerce sector with a focus on online stores. This study analyzes the published research works on streaming data pipelines in e-commerce sector also to facilitate e-commerce's variety of data streaming applications requirement. A state-of-the-art lambda architecture for streaming is proposed completely based on open-source technologies. Challenge in proprietary owned streaming platforms are vendor lock-in, limited ability to customize, cost, limited innovation & support. Proposed reference architecture will address many streaming use cases compared to its competitors, it has support of large open-source community in providing the inter-operability between streaming & related technologies like connectors, apart from providing better performance apart from other open-source based product advantages. ©

关键词： Big data

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Analysing the Emotions of Food Products Reviewsusing NLP and Adaboost Algorithm 2

Analysing the Emotions of Food Products Reviewsusing NLP and...

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2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Reshma, S. Kalpana, K. Hindustan Institute of Technology and Science Department of Computer Applications Chennai India

ISBN: (纸本)9798350315905

In the modern world, communication takes place over a large geographic region, and the Internet is expanding. Social media platforms enable text-based communication and human contact using either Emojis or text. The ability to express one's emotions through emotion is crucial to human existence. Speaking, making gestures, showing facial expression, and writing in comments are all ways to express emotions. A fascinating field of study has just arisen, and researchers are delving deeper into a variety of sorts of analysis, with emotional analysis being the most popular. Emotional analysis comes in three flavours: positive, negative, and neutral. Giving computers the ability to perceive, comprehend, and elicit certain emotional traits in a manner similar to those of humans is the aim of emotional computingso that they can communicate naturally, amicably, vividly, and with the same emotional intelligence as people. The development goal of the next-generation computer is to figure out how to humanise it and adaptively create the cosiest discussion atmosphere for the dialogue objects. In today's fiercely competitive business environment, gaining knowledge about consumer habits, wants, preferences, purchasing trends, and decision-making processes is crucial for brands and businesses. When determining the breadth and type of emotional analysis based on food reviews and feedback in e-commerce, our research will take a close look at the most often held points of view. A study on emotional analysis is required for social platforms because the information may become popular and have a big impact on social life. Emoji-based text-based emotion recognition is related to the NLP area (natural language processing). Additionally, we suggested the Adaboost algorithm as an approach to identifying emotion using only emojis. These techniques address the issue of identifying emotions both within and outside of sentences. © 2023 IEEE.

关键词： Food products

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Colossal Encipher Isolation Conserve Classifier 3

Colossal Encipher Isolation Conserve Classifier

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3rd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Nithish, R. Kunar, Prakash Sudha, S. Hindustan Institute of Technology and Science Department of Computer Applications Chennai India

ISBN: (纸本)9798350399264

This program has numerous applications, one of which is directly related to agricultural and produce areas. Since no participation is required during computation, the main limits are large cypher text growth and latency. We develop MAS-Encryption, a novel cryptographic tool that allows secure computing on the multiply-Add structure while still supporting real-value input, to get around these limitations. By connections between the Rise, yields, and farming-related empowerment, this application will give farmers some suggestions on how to increase agricultural cultivation yields. For the needs of the farmer, it will also provide more details on yields and fertilizer. In our program, MAS encryption is used to protect user information from prying eyes and the administrator, client information will not be displayed to the user. Our tests' results demonstrate that the MASE technique we've suggested and MASE-based classifiers are efficient in achieving the maximum achievable trade-off between computational performance and communication interactions. © 2023 IEEE.

关键词： Cryptography

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A Review of Moving Object Detection Techniques for Night Time 5

A Review of Moving Object Detection Techniques for Night Tim...

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5th IEEE International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Dua, Disha Bhat, Aruna Girdhar, Ashish Delhi Technological University Department Of Computer Science & Engineering Delhi India Kurukshetra University Department Of Computer Science & Applications Kurukshetra India

ISBN: (纸本)9798350330861

Moving Object Detection in low light conditions is a challenging task due to limited visibility and the presence of noise and objects in the captured images, low contrast, low brightness, low appearance information, and low Signal to Noise Ratio. The majority of night surveillance models suffer from lack of adaptability for different scenes and separation between detection and tracking. This review paper provides a comprehensive survey of recent advancements in Moving Object Detection Techniques for night-time situations. It presents an overview of various approaches proposed in the literature, including traditional and deep learning-based methods, and discusses their strengths and limitations. Moreover, the paper highlights evaluation metrics commonly used in the literature, the datasets they have been evaluated upon, along with a comparative analysis of the performance metrics & various limitations of different methods. Finally, the paper identifies the key research challenges and future directions for Moving Object Detection in Night Time viz. dim-lit environments, such as the need for more robust and efficient algorithms that can handle diverse environmental conditions and real-time applications. © 2023 IEEE.

关键词： Object detection

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Identification of Genomic Rearrangements in SARS COV-2 Viruses Leading to Evolutionary Insights using Sorting by Reversals 14

Identification of Genomic Rearrangements in SARS COV-2 Virus...

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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Shilpa, J. Jagadeeswaran, Sreelakshmi Department of Computer Science and Applications Amrita Vishwa Vidyapeetham Amritapuri India

Overtime due to many external and internal factors the genomes of various organisms go through rearrangement and mutations. The study of genome evolutions is done well by the understanding of this action. The three important ones which affect the genome changes mostly are recombination, transposition and mutation. Gene sequences are represented using permutation. Two organisms are genetically related if their genomes are closely comparable to one another else they are not. Similarity of two genomes can be measured by finding how simple it is to change one genome into another using certain operations such as reversals. Thus we get the reversal distance,the distance to change one genome to another by implementing sorting by reversal. To find the reversal distance, firstly we need to find the synteny blocks of the genome variants. Synteny blocks are converted into permutations and then with implementation of sorting by reversal algorithm we find the number of reversals needed to transmute permutation of rearranged genome to identity permutation. Various tools are used to find synteny blocks from the genome datasets and convert them into permutations. So by studying the genome rearrangement we get an insight on how the genomes are rearranged and how it will affect the genomic architecture of the organism in future. © Grenze Scientific Society, 2023.

关键词： Genome

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Optimized Web Service Composition Using Hybrid Evolutionary Algorithms 1

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3rd International Conference on Sustainable Expert Systems, ICSES 2022

作者： Subbulakshmi, S. Seethalakshmi, M. Unni, Devika Department of Computer Science and Applications Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (数字)9789811978746

ISBN: (纸本)9789811978739

Internet Web services are used to build electronic business applications so they can be interconnected and provide flexibility. When a user needs more than one service at a time, a composition of the available services is carried out in order to fulfil the user’s service request. When a wide variety of internet services are available, we demand a proper procedure of composing the services based on the aspects affecting service quality. Now a days for a single web service, there are multiple services with same functionalities are available. We made an effort to put together the web services in our recommended work with the highest overall QoS values based on the requests made by the user’s. We used particle swarm optimization (PSO) and ant colony optimization (ACO) techniques to address the service composition problem using quality of service (QoS) parameters. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality of service

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Machine Learning Approach for Securing of IoT Environment 6th

Machine Learning Approach for Securing of IoT Environment

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6th International Conference on Innovative Computing and Communication, ICICC 2023

作者： Sagu, Amit Gill, Nasib Singh Gulia, Preeti Rani, Deepti Department of Computer Science and Applications Maharshi Dayanand University Rohtak India

ISBN: (纸本)9789819933143

The term "Internet of Things" (IoT) is used to describe the global network of billions of devices, buildings, cars, and other physical things that are interconnected and exchange information. IoT security is necessary for the secure connection of devices and the components of such devices, as well as for the protection of those devices from cyberattacks which includes DoS, Botnet, brute force and SQL injection. In order to mitigate these potential attacks, several security methods and algorithms are introduced. However, the emergence and advancement of machine learning provide new options to address privacy and security concerns. Machine learning predicts the pattern of attacks that would occur in a network by analyzing past data that was generated in an IoT environment. Consequently, in this paper a number of machine learning models are employed to categorize the various types of IoT security assaults. Moreover, comparisons have demonstrated that machine learning models produce promising results. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Internet of things

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