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Unique Approach of Contextual Uniqueness Assessment of Research Papers Using Multi-Label Classification and Similarity Detection 26

Unique Approach of Contextual Uniqueness Assessment of Resea...

引用

26th International Conference on computer and Information Technology, ICCIT 2023

作者： Tanvir, Sifat Islam, Md. Zihadul Moon Taher, Sidrat Muztahid, Shaikh Adib Biswas, Arpon Shopnil, Md. Shahariar Brac University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9798350359015

Research papers should possess a significant amount of novelty. However, proper paraphrasing of entire paper may not be identified as plagiarism. Therefore, in this work a unique approach of similarity detection technique has been proposed. At first the abstracts are used to classify which area the paper belongs to, then papers of the same area are extracted and then contextual similarity is detected using cosine similarity. For training and testing purposes, two datasets have been created using data from IEEE Xplore. Since, almost every paper has some elements of paraphrased contents, therefore, a maximum acceptable threshold has also been proposed in this paper. Maintaining the maximum threshold, how well cosine similarity was able to distinguish the novel, paraphrased, and fully plagiarised works has also been analyzed. © 2023 IEEE.

关键词： Contextual Similarity Detection Cosine Similarity Deep Learning Multi-Label Classification

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Accurate Detection of Aquatic Debris in Ocean Surfaces using AlexNet Algorithm over ResNet-50 Algorithm 3

Accurate Detection of Aquatic Debris in Ocean Surfaces using...

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3rd International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2023

作者： Kamal, T.M. Bharatha Devi, N. Saveetha School of Engineering Dept. of Computer Science Chennai India

ISBN: (纸本)9798350306989

This research study intends to detect the aquatic debris accurately on Ocean surfaces using Novel AlexNet algorithm in comparison with ResNet-50 algorithm. Novel AlexNet and ResNet-50 are the two groups considered for this research with 20 iterations done for each group whose G-power is 80% and confidence level is 95%. The dataset consists of 724 JPG file format images depicting clear ocean and 324 JPG file format images depicting aquatic debris, including images with noise. This work demonstrates that the Novel AlexNet algorithm achieves an accuracy of 93.77% which identifies objects accurately over the ResNet50 algorithm with an accuracy of 91.47% and there is no statistical significance difference between the Novel Alexnet Algorithm and ResNet-50 Algorithm for the value of p=0.076 (Independent Sample T-test p © 2023 IEEE.

关键词： Debris

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Relaxing Super Localization Frame Rate Requirements Utilizing a Novel 2D Interpolation Technique

Relaxing Super Localization Frame Rate Requirements Utilizin...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Tuccio, Giulia Afrakhteh, Sajjad Iacca, Giovanni Demi, Libertario University of Trento Dept. of Information Engineering and Computer Science Italy

ISBN: (纸本)9798350346459

Ultrasound Localization Microscopy (ULM) by-passes the conventional diffraction limit, allowing the imaging of the vasculature at a microscopic resolution through precise localization of intravenously injected microbubbles. Thanks to their resolution, ULM generated images hold the promise to be the next diagnostic frontier for diseases that modify the vascular structure, such as cancer. However, deploying ULM in clinical settings is currently limited by the prolonged acquisition times and high frame rates needed. To relax the high frame rate requirement, we propose a new time-efficient ULM (TEULM) pipeline. The proposed TEULM introduces the radial basis functions (RBFs) as interpolators upstream of the ULM framework, to recover the missing information consequence of a reduced frame rate. We test TEULM using in vivo Rat's Brain and Kidney datasets acquired at a high frame rate (1 KHz). The results confirm the ability of TEULM to reconstruct super-resolution (SR) images with a similarity score (Dice score) of 80% for both datasets when simulating a frame rate acquisition of 100 Hz;i.e., we can relax the frame rate requirement for ULM by a factor 10 while keeping the SR image quality acceptable. © 2023 IEEE.

关键词： Interpolation

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Distributed and Synchronized Multilingual Audio Container for Video Streams 2

Distributed and Synchronized Multilingual Audio Container fo...

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2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies, ViTECoN 2023

作者： Nidagundi, Pradnya S. Udupa, Prajna Dindore, Chinmayee Kothari, Palak Pujari, Nitin V. PES University Dept. of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347982

This paper presents a distributed and synchronised multilingual audio container for video streams. The system utilises a distributed architecture to separate audio and video streams, allowing for the independent manipulation and synchronization of multiple languages. The proposed solution addresses the challenges of providing efficient video streaming and has the potential to improve accessibility to foreign language educational content for non-native speakers. The proposed approach improves the scalability and flexibility of the system, as well as the overall user experience. The system is evaluated through simulations and real-world implementation, demonstrating its effectiveness in providing a seamless multilingual video streaming experience. The results show that the proposed system can synchronize multiple languages with high accuracy, and the distributed architecture ensures low latency and high scalability. © 2023 IEEE.

关键词： Synchronization

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Finding Type 2 Diabetes Using Sparse Balanced Support Vector Machine in Electronic Health Records

Finding Type 2 Diabetes Using Sparse Balanced Support Vector...

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2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

作者： Kaur, Ranjanpal Sekhon, Er. Navjot Kaur Chandigarh University Dept. of Computer Science & Engineering Mohali India

ISBN: (纸本)9798350331790

Early Type 2 Diabetes (T2D) diagnosis is crucial for optimal integrated therapy and patient follow-up. There has been a huge growth in the quantity of accessible Electronic Health Record (EHR) data, and developments in Machine Learning (ML) methodologies have been as amazing. Maintaining and modelling a huge data set can cause over fitting, model interpretability, and computational expenditure. We used Sparse Balanced Support Vector Machine (SB-SVM) to detect type 2 diabetes in an original EHR dataset (named FIMMG dataset). In particular, we have chosen just those aspects of the EHR collected from a homogeneous group of participants before the diagnosis of T2D, including exemptions, examinations, and medicine prescriptions. The proposed solution is trustworthy compared to other ML and Deep Learning methods utilised by the state-of-the-art to handle this problem. The SB-SVM offers the best prediction performance-computation time tradeoff, according to the data. In addition, the induced sparsity makes the model more interpretable while automatically handling high-dimensional data and the normally uneven distribution of classes. © 2023 IEEE.

关键词： Support vector machines

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Driving Behavior Classification Using Smartphone Sensor Data 8

Driving Behavior Classification Using Smartphone Sensor Data

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8th International Conference on computer science and engineering, UBMK 2023

作者： Dikbiyik, Deniz Alagoz, Fatih Boǧaziçi University Dept. of Software Engineering İstanbul Turkey Boǧaziçi University Dept. of Computer Engineering İstanbul Turkey

ISBN: (纸本)9798350340815

Given the substantial number of accidents because of human error, the development of automatic driver behavior monitoring systems has become a pressing need. By providing real-time monitoring and analysis of driving behavior, these systems have the potential to decrease the incidence of accidents and improve overall road safety. This study presents a novel analysis framework for classifying driving behavior based on data gathered from passengers' smartphones. The data were collected using our mobile application installed on the smartphones and processed using machine learning algorithms. The study utilized several machine learning classification t echniques, w ith a focus on developing a Long Short Term Memory (LSTM) algorithm for improved accuracy. A Federated Learning algorithm was also developed to collect the data not into one area and train a global model to apply for labeling the driving behavior. The results show the efficacy of the proposed approach in accurately classifying driving behavior based on data obtained from smartphones. © 2023 IEEE.

关键词： Smartphones

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SynBioTrace: Integrating Safety and Security Artifacts to Build Assurance Cases for Synthetic Biology Applications 35

SynBioTrace: Integrating Safety and Security Artifacts to Bu...

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35th IEEE International Symposium on software Reliability engineering Workshops, ISSREW 2024

作者： Firestone, Justin Cohen, Myra B. Lutz, Robyn R. University of Nebraska-Lincoln Dept. of Computer Science & Engineering LincolnNE68588 United States Iowa State University Dept. of Computer Science AmesIA50011 United States

ISBN: (纸本)9798350367041

The rapidly advancing cyber-physical domain of synthetic biology modifies the functionality of micro-organisms which can act as living computational devices. Applications include intelligent drug delivery, customized cancer therapies, and pollution detection and mitigation. While many synthetic biology applications have been proposed, prototyped, and even deployed, these systems often lack standard approaches to verify their safety and security. One approach, the assurance case, provides evidence demonstrating proper implementation in the target application, and is often used in other safety-critical domains. However, synthetic biologists lack guidance in developing assurance arguments and tracing safety and security requirements to evidence as required for building assurance cases. Although there has been some research combining safety and security artifacts, such techniques often require extensive expertise from different domains and may not be accessible to synthetic biologists. In this paper we propose SynBioTrace, an assistive process to help propagate information from risk-based analyses of such systems to preliminary assurance cases. SynBioTrace preserves traceability among its steps so that the assurance case can be further refined. We apply and evaluate it through a case study based on a real-world synthetic biology application. Our case study suggests this approach could aid synthetic biologists in identifying, documenting, and structuring safety and security artifacts, as well as linking evidence to support traceability for a complete, integrated assurance case. © 2024 IEEE.

关键词： Controlled drug delivery

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Indonesian Hate Speech and Abusive Tweets Classification with Deep Learning Pre-trained Language Models 6

Indonesian Hate Speech and Abusive Tweets Classification wit...

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6th International Conference on computer and Informatics engineering, IC2IE 2023

作者： Yulianto Darmawan, Bagus Tri Irnawan, Bassamtiano Renaufalgi Suzuki, Yoshimi Politeknik Negeri Jakarta Dept. of Computer and Informatics Engineering Depok Indonesia University of Yamanashi Dept. of Computer Science and Engineering Kofu Japan

ISBN: (纸本)9798350345162

Hate speech and abusive language on social media can spread massively and escalate into conflict between two or more individuals or parties. Previous studies about multi-label classification to identify whether the tweet contains hate speech, abusive language, or not have been conducted with machine learning techniques. They applied machine learning with a combination of feature extraction and achieved a good result in recognizing the tweet with hate speech content. In this research, we apply two approaches: first, we use vanilla pre-trained models of IndoBERT, IndoBERTweet, and Indonesian RoBERTa;second, we combine the three previous models with CNN. Our experiment shows that our proposed method has better results compared to previous research with the best performance achieved by IndoBERTweet+CNN with 93.9% Accuracy. © 2023 IEEE.

关键词： Abusive CNN Deep Learning Hate Speech IndoBERT IndoBERTweet Indonesian RoBERTa Indonesian Twitter

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Evaluation of Handwritten Descriptive Responses Using Machine Learning - A Survey 2

Evaluation of Handwritten Descriptive Responses Using Machin...

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2nd IEEE International Conference on Futuristic Technologies, INCOFT 2023

作者： Tayal, Pankhuri Shetty, Parth Praveen Pratheeksha, P. Harshita, R. Sreenath, M.V. Pes University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350308846

Evaluation of student performances is crucial to the process of learning in an education system. Currently, the most common approach adopted throughout the education industry is largely reliant on human resources as forms of evaluators. As the gap in student-teacher ratios increases, this process becomes complicated and cumbersome and such manual assessment techniques lead to unintentional biases and inconsistency. Technology has been playing a role in aiding evaluators in the recent trends. Instead of the traditional pen and paper-based methods, modes of assessments are being digitized and so are the correction processes. While there are several successful technologies available for grading multiple-choice questions, there is still growing research for methods of evaluating descriptive questions which need to account for a degree of variations in student answers. For the last few decades, there have been many researchers working on developing a system that would act as a bridge between traditional methods and digitized evaluation systems, by using techniques like Optical Character Recognition (OCR). Various Artificial Intelligence and Machine Learning techniques have been proposed to evaluate descriptive answers automatically. This paper provides a comprehensive survey of such systems and analyses the drawbacks of the current studies. It has been observed that these systems do not consider essay-type questions that do not have a defined answer. © 2023 IEEE.

关键词： Artificial Intelligence and Machine Learning Handwritten descriptive answer evaluation Natural Language Processing OCR

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Optimizing Customer Segmentation: A Comparative Analysis of Clustering Algorithms Using Evaluation Metrics 8

Optimizing Customer Segmentation: A Comparative Analysis of ...

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8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Sakina, Noor Arun, Ajith P. Pavithra, R. Vishalakshi Prabhu, H. Gupta, Praveen Kumar Rv College of Engineering Dept. of Computer Science and Engineering Bengaluru India Rv College of Engineering Dept. of Chemical Engineering Bengaluru India Rv College of Engineering Dept. of Electronics and Communication Engineering Bengaluru India Rv College of Engineering Dept. of Biotechnology Bengaluru India

ISBN: (纸本)9798331505462

Customer segmentation is the route to data-driven decisions within organizations serving a wide variety of customer needs. This research explores customer segmentation with the utilization of K-means, hierarchical clustering, fuzzy C-means, along with DBSCAN to behavioural and demographic data. These algorithms are measured against each other using their silhouette score, Davies-Bouldin index, and cluster cohesion value. These results highlight that clustering can reveal meaningful patterns in customer data for improving personalized marketing strategies, customer retention, and profitability. © 2024 IEEE.

关键词： Sales

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