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2nd International Conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Bhowmik, Ankan Basu, Arkajyoti Basu, Arittra Paul, Anish Roy, Atrri Department of Computer Application and Science Institute of Engineering and Management Kolkata India

ISBN: (纸本)9789819735938

Credit score is an important indicator to lenders of your capability to repay loans. A consumer's creditworthiness is indicated by a number between 300 and 850 called a credit score. The advanced the score, the better a borrower looks to implicit lenders. It is predicated on data gathered from lenders and is consolidated in the Credit Information Report or CIR. This paper reviews to check one’s report regularly, also helps you to identify any disagreement that may be lowered your score, and helps to recover the lower score to advanced situations score. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Credit ratings Credit score Loan Net profit

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Skin Lesion Segmentation Using Deep Learning 2nd

Skin Lesion Segmentation Using Deep Learning

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2nd International Conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Sarkar, Kaustav Haralalka, Varun Shaw, Vishal Singh, Rishav Raj Jaiswal, Rayirth Pramanick, Tridip Department of Computer Application and Science Institute of Engineering and Management Kolkata India

ISBN: (纸本)9789819735938

Dermoscopic image analysis has gained significant importance for dermatological applications due to its potential in eliminating observer bias. Segmenting lesion areas automatically in these images is crucial for expedited disease diagnosis. In this study, an innovative deep learning-based approach for precise lesion delineation has been proposed. Leveraging a deep convolutional neural network, where input images are included after appropriate preprocessing. Pedro Hispano Hospital (PH2) 2013 dataset has been employed, comprising dermoscopic images and lesion binary masks as ground truth for evaluation. The approach uses the SegNet architecture, which achieves remarkable accuracy of 99.14%, surpassing benchmark standards (DC 96.94, JI 99.11).This research offers a promising solution for automated lesion segmentation in dermoscopic images, advancing the field of medical image analysis. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image analysis

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A Random Walk-Based Approach for Clustering of Food Items 2nd

A Random Walk-Based Approach for Clustering of Food Items

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2nd International Conference on Cyber Intelligence and Information Retrieval, CIIR 2023

作者： Das, Priyanka Bhattacharya, Rupam Department of Computer Application Institute of Engineering and Management West Bengal Kolkata India

ISBN: (纸本)9789819735938

Most of the recipe sites have a distinct page structure comprising a title, list of ingredients, preparation instructions, comments, and thus it is very challenging to cluster similar recipes. The work presented here initially starts with the formation of a recipe network and finding ‘leading’ nodes from the network. To the best of our knowledge, there doesn’t exist any research that addresses the concept of finding ‘leading’ nodes from a recipe network and subsequently clustering similar recipes based on the ingredients. In order to fill this gap, we have proposed a method RWRC (Random Walk-based Recipe Clustering). To determine the ‘leading’ nodes, the proposed approach incorporates data from the breadth-first search tree. To create a breadth-first search (BFS) tree, the graph is explored in level-order, starting with each node as the root node. At each level of the traversal, we have computed the degree centrality, betweenness centrality and closeness centrality of each node. The ‘leading factor’ has been considered as the average of these centrality measures for all the nodes present in the network. A random walk-based graph clustering approach has been addressed that initiates from the root node of the original recipe network. If the ‘leading factor’ of the next visiting node in the random walk is equal to or greater than the average ‘leading factor’ of the whole network, the agent moves to its neighbours;otherwise, the stopping requirement is satisfied. Further, these nodes discovered by this random walk are organised into a cluster. When a walk comes to an end, the visited nodes from the initial graph are extracted, and the subsequent walk begins in the remaining graph. The random walk continues until there are no undiscovered node(s) left. These extracted nodes form the clusters of recipes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Trees (mathematics)

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A Crime Knowledge Discovery Scheme Based on Entity Recognition, Relation Extraction, and Development of Criminal Profiling Using Modus Operandi 11th

A Crime Knowledge Discovery Scheme Based on Entity Recognit...

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11th International Conference on Intelligent Computing and applications, ICRTC 2023

作者： Das, Priyanka Dhar, Sayan Banerjee, Shreedatri Basak, Shirsha Nandi, Sneha Saha, Sneha Department of Computer Application Institute of Engineering and Management West Bengal Kolkata India

ISBN: (纸本)9789819717231

In this paper, a criminal knowledge discovery scheme is proposed for analysing the crime situation in India. The approach pulls information regarding crime against women in Indian states and union territories from a sizable corpus of newspaper reports and then uses the retrieved corpus to identify named entities. India has experienced an increase in crime in recent years, and daily, several crime reports are published. However, it can be difficult to manually access the crime reports and extract relevant information that can aid in the analysis of crime trends by law enforcement. Even while there are many research on the analysis of crime patterns, relatively few of them include entity recognition, relation extraction, and features of modus operandi. This study focuses on phrase identification to discover the rules for determining modus operandi from police records. The effectiveness of the method is evaluated using precision and recall. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Crime

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Crime Analysis Using Graph-Based Feature Selection 11th

Crime Analysis Using Graph-Based Feature Selection

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11th International Conference on Intelligent Computing and applications, ICRTC 2023

作者： Das, Priyanka Dutta, Arindam Das, Bikash Kar, Madhuja Chakraborty, Sudipta Department of Computer Application and Science Institute of Engineering and Management West Bengal Kolkata India

ISBN: (纸本)9789819717231

The current study extracts all potential crime attributes from reported offenses and selects just those that are needed for crime pattern assessment. To accomplish this, before using a crime report, it is processed, and criminal features are gathered to build feature vectors for each report. Based on a cosine relationship score, a weighted and undirected graph evolved, with the distinguishing qualities as vertices and the inverse of the similarity rating as the weight of the accompanying edge. The threshold number is determined by averaging all edge weights. Two separate subgraphs have been formed based on the threshold. The resulting two subgraphs could be a collection of several components that were used individually as input to the next iteration of the clustering operation. Each component’s threshold has been changed independently, and they have been further partitioned into more compact subgraphs. The Silhouette Index, a cluster validation metric, is computed at each level of iteration, and the technique occurs over and over just in case the cluster quality improves. Eventually, the graph clustering method categorizes features. Thus, the primary improvement of this paper is feature selection, which not only improves the efficiency but also the veracity of the following mining process. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Crime

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Utilization of Two Cross Two Switch for Bitonic Sorting Circuit

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Micro and Nanosystems 2025年第1期17卷 45-57页

作者： Bhattacharjee, Subhasree Sarkar, Soumyadip Das, Kunal Sadhu, Arindam Sarkar, Bikramjit Department of Computer Application Narula Institute of Technology Kolkata India Department of Computer Science Acharya Prafulla Chandra College Kolkata India Department of Electronics & Communication Engineering Greater Kolkata College of Engineering and Management West Bengal India Department of Computer Science & Engineering JIS College of Engineering West Bengal India

Background: The synthesis of reversible logic has gained prominence as a crucial research area, particularly in the context of post-CMOS computing devices, notably quantum computing. Objective: To implement the bitonic sorting circuit, 2x2 switch, is used. The overarching objective of implementing a reversible sorting circuit is to mitigate power consumption while promising secure communication. The successful implementation of the bitonic sorting circuit utilizing the proposed 2x2 switch is validated through simulations conducted in IBM Qiskit. Methods: This study begins by employing the control swap gate to implement a 2x2 switch, aimed at enabling concurrent computing operations within multiprocessor systems to enhance throughput. Subsequently, following the successful implementation of the 2x2 switch, the study proceeds to design a bitonic sorting circuit. Results: Bitonic sort using a 2x2 switch on the IBM Quantum Experience (IBMQ) platform via the QISKit SDK in Python 3.6. Specifically, Qiskit v0.29.0 is utilized, with OpenQASM. OpenQASM serves as the quantum assembly and instruction language. Conclusion: This work presents a methodology for constructing a 2x2 switch, utilizing a reversible control swap gate as its core component. Additionally, it demonstrates the intricate development and implementation of a bitonic sorting circuit, capitalizing on this innovative switch architecture. © 2025 Bentham Science Publishers.

关键词： Quantum computers

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Rough Set Based Recipe Clustering Approach 10

Rough Set Based Recipe Clustering Approach

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Das, Priyanka Mukherjee, Chandrani Gupta, Samiksha Roy, Sayan Shah, Khushi Singh, Shreya Institute of Engineering & Management Dept. of Computer Application and Science Kolkata India

ISBN: (纸本)9798350384369

Online cooking instructions including ingredient lists and cooking methods are now widely available due to the proliferation of recipe sharing websites. Finding novel and complex patterns in such vast, ambiguous categorical data sets is a crucial task. Conventional clustering analysis algorithms frequently fail to address the uncertainty surrounding the exact value of features found in these categorical data sets. Thus to aid in decision-making, rough set based clustering is frequently used. This study aims to identify the optimal clustering feature from the recipe data that will result in the grouping of related food products by applying the rough purity notion. The recipe data has been regarded as a categorical valued information system in this instance, and information theoretic attribute purity is taken into account using the rough purity technique. © 2024 IEEE.

关键词： Food chemistry

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Classification of Foods based on Bijective Soft Set 15

Classification of Foods based on Bijective Soft Set

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Das, Priyanka Bhattacharya, Rupam Dept. of Computer Application and Science Institute of Engineering & Management Kolkata India

ISBN: (纸本)9798350370249

Cuisine data is typically classified using images of the cuisine, cooking methods, cooking utensils, and, most importantly, ingredients. The vast amount of recipe data available on the internet necessitates the creation of specialised systems for storing, retrieving, and effectively utilising stored knowledge and data. Neural networks based expert systems are steadily being used to classify the cuisine data. But it lacks in dealing the vagueness present in the categorical cuisine data. Also, most of the popular recipes available online are mostly unhealthy. As a result, the Bijective soft set theory has been introduced into this study since it is an intelligent method for developing classification rules from food data and then recognising ambiguity and data reliance. The classification guidelines also address the necessity to select healthy/nutritious meals. The investigation outcomes from using bijective soft set analysis to a set of data samples are presented and appraised in this work. Furthermore, the classification rules derived from this approach provides valuable help for developing food recommendation systems. The accuracy of this classification scheme has got really influenced by application of the bijective soft set when compared to other state-of-the-art classifiers. ©2024 IEEE.

关键词： bijective soft set classification classification rule generation cuisine ingredients

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A Graph Based Approach For Detecting Sybil Node In Online Social Networks 15

A Graph Based Approach For Detecting Sybil Node In Online So...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Chandra, Sucheta Das, Priyanka Institute of Engineering & Management Dept. of Computer Application and Science Kolkata India

ISBN: (纸本)9798350370249

Sybil attacks pose a significant threat to the security and integrity of online social networks by allowing malicious actors to create multiple fake identities to manipulate network behavior. The abstract outlines a method for detecting Sybil attacks in online social networks using graph analysis. It involves constructing a graph representation of the network, calculating node centrality measures such as in-degree and out-degree, and setting a degree threshold to identify potentially malicious nodes. Additional parameters like clustering coefficient and community structure are also considered to improve detection accuracy. The proposed approach aims to enhance the security of online social networks by identifying and isolating Sybil identities, thus preserving network integrity and trustworthiness. The authors' firmly assert that employing graph-based theory for Sybil node detection in online social networks stands out as one of the most effective methods. This approach not only offers robustness but also scalability, allowing for efficient detection even in large-scale networks. With its ability to unveil intricate relationships, anomalies, and patterns within the network, graph-based theory emerges as a cornerstone in the fight against Sybil attacks. © 2024 IEEE.

关键词： Cyber attacks

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Fall Detection and Alerts in Hearing Aids for Deaf using Generative AI 2

Fall Detection and Alerts in Hearing Aids for Deaf using Gen...

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2nd International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2025

作者： Tripathi, Bharat Lal Saini, Madan Jain, Manish Saxena, Apoorva Pal, Narendra Department of Computer Application Allenhouse Institute of Technology Kanpur India Department of Computer Science and Engineering Apex Institute of Technology Chandigarh University Punjab India Department of Computer Application Allenhouse Business School Kanpur India Department of Computer Science & Engineering Axis Institute of Technology & Management Kanpur India Department of Computer Science & Engineering Invertis University Bareilly India

ISBN: (纸本)9798331530389

Individuals with sensorineural hearing loss often experience difficulty comprehending speech when background noise is present. This paper investigates the extent of this problem in various listening scenarios and with different types of background sounds. Additionally, the section explores the contributing factors to this challenge such as reduced audibility, reduced frequency selectivity, loudness recruitment, and dead regions in the cochlea where there are no surviving inner hair cells and or neurons. The sections evaluate different techniques for compensating for the effects of these factors. While signal-processing methods using the output of a single microphone to compensate for reduced frequency selectivity have had limited success, techniques utilizing multiple microphones have proven effective. Amplitude compression has also been effective in compensating for the effects of loudness recruitment, enabling individuals to understand speech across a wide range of sound levels. Next, the paper delves into the technical aspects of implementing fall detection systems in hearing aids, learning algorithms are also investigated for their potential in enhancing fall detection accuracy and minimizing false alarms. Furthermore, the importance of user-friendly interfaces and customization features in ensuring the effectiveness and acceptance of fall detection alerts is also highlighted. The paper also addresses the ethical and privacy considerations associated with fall detection in hearing aids. It emphasizes the need for transparent data handling practices and user consent, while also addressing potential concerns related to user autonomy and intrusion. © 2025 IEEE.

关键词： Data privacy

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