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Fraud Detection in Financial Transactions using Machine Learning - A Comparative Study

Fraud Detection in Financial Transactions using Machine Lear...

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Delhi Section Conference (DELCON), IEEE

作者： Avati Jayanthkumar Mayakuntla Sai Sathwik Shagam Srinivasa Reddy Donadula Mounish Kumar Chougule Saish Samir Jagdish Chandra Patni Nilesh Bahadure Rohit Kumar Dept. of Computer Science Alliance School of Advanced Computing Alliance University Bengaluru India Department of Computer Science and Engineering School of Technology GSFC University Vadodara India

ISBN: (数字)9798331518592

ISBN: (纸本)9798331518608

Data analysis techniques using machine learning approaches are the most prominent when we are considering the online fraud, it may be a credit card fraud or any other online fraud in the banking system. Using Machine Learning techniques, we can easily manage the information of fake transactions by extensive data analysis of time, location and amount in the real time. This paper gives the comprehensive study of the changing scene of the fraud discovery in monetary exchanges, investigating the most recent patterns, advances, and techniques utilized by financial institutions and other administrative bodies. An extensive review of various machine learning techniques has been done to find out the effective solution to protect the online fraud.

关键词： Machine learning algorithms Data analysis Recurrent neural networks Reviews Design methodology Machine learning Real-time systems Data models Fraud Safety

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Analogous Particle Swarm Optimization for Choosing Optimal Selection of Virtual Machine in Cloud 12

Analogous Particle Swarm Optimization for Choosing Optimal S...

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12th International Conference on computer Communication and Informatics, ICCCI 2022

作者： Kumar, R. Prasanna Vignesh, T. Venkateswarulu, Balaji Vijayan Sivakumar, R. Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Vidyapeetham Chennai India Srm Institute of Science and Technology Department of Master of Computer Application Chennai Ramapuram India Vignan's Foundation for Science Technology and Research Department of Computer Science and Engineering Vadlamudi AP Guntur India Easwari Engineering College Dept of Physics Chennai Ramapuram India

ISBN: (纸本)9781665480352

Cloud computing is one of the chief elements in Medical Care Administrations. It tends to be utilized to recover data about patients, their records identified with diagnosing, therapy taken and other clinical data in less measure of time. In this field picking of an ideal VM is a difficult and more intriguing in medical care administrations. The way to deal with pick the best ideal VM helps in expanding the exhibition of medical care benefits consequently decreasing the running opportunity to execute the solicitation. This paper proposes a novel and upgraded rendition of PSO called Similar to Molecule Multitude Enhancement (APSO). The presentation is contrasted and Hereditary Calculation and PSO. The assessment is finished by considering three boundaries like holding up time, use of computer chip and turnaround time. The outcomes unmistakably express that the APSO approach performs well when contrasted with different models. The general execution time for every molecule is registered as 1s and effectiveness apparently is improved by 5.6%. © 2022 IEEE.

关键词： Genetic algorithms

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Hybrid Vision Transformer Model for Accurate Prostate Cancer Classification in MRI Images

Hybrid Vision Transformer Model for Accurate Prostate Cancer...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Jesika Debnath Arafath Bin Mohiuddin Al Shahriar Uddin Khondakar Pranta Anamul Sakib Amira Hossain Md. Moniruzzaman Shanto Shamim Forhad Md. Redwan Ahmed Rezaul Haque Shafiur Rahman Dept. of Computer Science Westcliff University Irvine CA USA Department of Collage of Engineering and Technology Westcliff University CA USA Dept. of Computer Science Wright State University Dayton USA Department of Business Administration International American University CA USA Dept. of Computer Science and Engineering East West University Dhaka Bangladesh Dept. of Electrical and Electronics Engineering American International University Bangladesh Dept. of Software Engineering Daffodil International University Dhaka Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Prostate cancer is a widespread disease in men worldwide, posing challenges in early detection due to its diverse nature and the limitations of current diagnostic techniques. In this study, we have developed a new method that combines CNNs with Vision Transformers (ViTs) to improve the classification of prostate cancer using MRI images. To address data imbalance and enhance model robustness, we used dual synthetic oversampling techniques and data augmentation methods. Our preprocessing pipeline reduced noise, preserved edges, and improved local contrast without amplifying noise. For feature extraction, we utilized the GrayLevel Co-occurrence Matrix (GLCM) and shape-based features to represent complex MRI data better. Among the evaluated architectures, ConvNeXt showed the best performance. Using SMOTE, it achieved an F1-score of 97.21% and a MCC of 95.32%. With ADASYN, performance improved further, reaching an F1-score of 98.82% and an MCC of 97.86%. Additionally, we created a web-based application for realtime analysis of prostate MRI scans, which can aid in clinical decision-making. These results demonstrate the potential of our approach to improve the accuracy of prostate cancer diagnosis and provide an interpretable model for clinical use.

关键词： computer vision Accuracy Magnetic resonance imaging Noise Pipelines Transformers Feature extraction Robustness Prostate cancer Resilience

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Efficient Optimization in Dispensation of Cloud applications using Novel Stochastic Gradient with Forward Back Propagation Algorithm

Efficient Optimization in Dispensation of Cloud applications...

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Pervasive Computing and Social Networking (ICPCSN), International Conference on

作者： Anithaashri T.P V. Loganathan R. Lalitha Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Dept of Computer Science and Engineering Saveetha Engineering College Chennai Tamil Nadu India Dept of Computer Science and Engineering Rajalakshmi Institute of Technology Chennai Tamil Nadu India

ISBN: (数字)9798350386349

ISBN: (纸本)9798350386356

The effective use of cloud server is a major challenge in the recent days. To handle the computation speed, space complexity, network accessibility is playing vital role in achieving the efficiency of cloud server. The objective is to obtain the energy efficiency in cloud servers using a novel stochastic gradient with forward back propagation algorithm. Two sample groups with number of iterations 20 each have been tested with G-power of 80% with the total sample size of 360, divided into two groups with Group 1=180, Group 2=180 and an independent sample t-test has been done. To improve the accuracy of energy optimization, a novel stochastic gradient with forward back propagation algorithm is proposed and compared with the machine learning algorithm. The results prove that the novel stochastic gradient with forward back propagation algorithm has a high accuracy of 92.1%, which is significantly better than the other machine learning algorithms. The level of significance p=0.02 (p<0.05) shows that there is a significant difference between these two algorithms. Thus, the cloud server optimization is achieved using stochastic gradient with forward back propagation algorithm through various testbeds.

关键词： Backpropagation Pervasive computing Data centers Machine learning algorithms Accuracy Costs Social networking (online)

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InterACT: Enhancing Human-AI Interaction 2

InterACT: Enhancing Human-AI Interaction

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2nd International Conference on Machine Learning and Autonomous Systems, ICMLAS 2025

作者： Katta, Jithendra Kodumuru, Nikhil Reddy Katta, Swathi School of Engineering and Applied Sciences The George Washington University WashingtonDC United States Vignana Bharathi Institute of Technology Computer Science & Engineering dept. Hyderabad India

ISBN: (纸本)9798331505745

The rapid advancement of large language models and computer vision systems has opened new frontiers in artificial intelligence. This paper introduces InterACT, a novel cross-modal system that integrates leading language and vision models to enable more intuitive and context-aware human AI interactions. By leveraging the strengths of both modalities, InterACT processes natural language queries to guide object detection in visual environments, bridging the gap between linguistic and visual understanding. We evaluate the performance of three language models of varying sizes in conjunction with an advanced object detection model, exploring the balance between computational efficiency and interaction quality. Our experiments demonstrate InterACT's potential across diverse real-world scenarios, revealing promising results in maintaining contextual relevance and adaptability. This research contributes to the growing field of cross-modal AI systems and lays the groundwork for more sophisticated human AI interactions, with implications for applications ranging from assistive technologies to educational tools. © 2025 IEEE.

关键词： Object detection

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Smart Beds Designed for Monitoring and Treatment of Pressure Ulcers

Smart Beds Designed for Monitoring and Treatment of Pressure...

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technology, engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET), IEEE International Conference on

作者： Sheryl Robinson Aishwarya Mohan Kumar J Bethanney Janney Poojahsri Sivakumar K Dhanalakshmi P. Grace Kanmani Prince Dept. of Biomedical Engg Sathyabama Institute of Science and Technology Chennai India Dept. of Computer Science Engg Sathyabama Institute of Science and Technology Chennai India

One of the most common risks for individuals who are bedridden is the development of bedsores (Pressure Ulcers). The number of senior persons who are permanently disabled and semi-impaired is growing as the population ages. The conventional methods used to relieve bed sores tend to focus on the pressure distribution and very minimal focus is provided for therapy. In order to detect patterns of warning signs or pathogens that can be treated early to reduce morbidity and mortality as well as length and expense of hospitalization, it is crucial to continuously monitor the patient’s health while they are in the hospital. Healthcare workers continuously monitor the patient’s vital signs, making it simple and safe to shield the patient from unforeseen threats and to reduce harmful health issues. On the other hand, a major side effect of hospitalization is the impact of pressure ulcers on the bedridden patient as a result of strong shear forces. A pressure ulcer or bedsores is a damage to tissue that has been disturbed or lacks blood flow as a result of prolonged pressure and shear forces, and it can give the patient pain and discomfort. This review focuses on research articles that deals with monitoring as well as treatment of patients inflicted with pressure ulcers. Furthermore, we have also proposed a basic system and methodology that can be followed by others for future research work.

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Development of an Instrumented Glove for the Characterization of Human Wrist Tremor 7

Development of an Instrumented Glove for the Characterizatio...

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7th International Conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Lakineni, Prasanna Kumar Dhana Sony, J. Sharma, Ruchi Chitra, M. Jose Anand, A. Anchitaalagammai, J.V. GITAM School of Technology Department of Computer Science and Engineering GITAM University Visakhapatnam India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Department of Biomedical Engineering Chennai600062 India JECRC Foundation Department of AI&DS Rajasthan Jaipur302022 India Rajalakshmi Institute of Technology Dept of ECE Tamilnadu Chennai India KCG College of Technology Karapakkam Department of Electronics and Communication Engineering Chennai600097 India Velammal College of Engineering and Technology Department of Computer Science and Engineering Tamilnadu Madurai India

ISBN: (纸本)9798350340600

It is common for human beings to present some diseases and disorders as they age, due to neuromusculoskeletal disorders. One of the problems that can appear is the human tremor. There are numerous strategies for tremor attenuation. Among the most common methods, the use of medications, local surgical procedures, electrical stimulation and the use of active orthoses stand out. In this context, robotic rehabilitation is of interest to science more and more. Among the methods for inhibiting tremor, active orthoses are the most efficient and non-invasive means. With that in mind, and also in terms of their quality of life, studies on orthoses to suppress tremor were carried out. Due to the complexity of the device, the present study aims to develop and evaluate an instrumented glove, properly constructed to characterize human wrist tremor in patients affected with such dysfunction. To this end, the basic operating principle of the active orthosis is presented, seeking to highlight more specifically the instrumented glove with its motion and muscle actuation sensors. © 2023 IEEE.

关键词： Biomedical signal processing

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Fuzzy Search with Multi-Keyword Security and Improved Service Quality

Fuzzy Search with Multi-Keyword Security and Improved Servic...

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Data science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： E. Bhuvaneswari V. Anjana Devi R. Gowri Dept. of Computer Science and Engg. Chennai Institute of Technology Chennai Tamil Nadu India Dept. of Computer Science and Engg. Rajalakshmi Institute of Technology Chennai Tamil Nadu India

Over the past ten years, there has been a tremendous advancement in machine learning and computer vision, which has led to a large decrease in computing complexity and an increase in efficiency for visual learning algorithms. The Automated Question and Answering System combines stemming with a partial match retrieval technique to do this. The answer provided by the suggested method will be improved over the standard text answer provided by the visual learning system by using text and multimedia, like an image or video. Based on the classifiers for all the predefined qualities, an attribute feature, including the answers from these classifiers, represents each image. The proposed uses a novel picture re-ranking architecture that learns different semantic spaces for different query phrases. The features of the photographs are projected. Images are reranked online by comparing their semantic signatures, retrieved from the semantic space the query term specifies. The suggested semantic fingerprints specific to a query greatly increase the precision and effectiveness of image reranking. Our project primarily focuses on making retrieving data from the internet simple to boost productivity and shorten the time it takes a user to look for the necessary query. Our software uses an application programming interface or API to locate the specific term the user seeks in the WordNet database. A stemming algorithm is used to modify the query multiple times until the right match is identified in the database. Utilizing Levenshtein distance, The classified data is entered into the relevant columns. Consequently, the user can examine the three columns separately and find his needs in that specific speech context. The main advantage of this type of searching is that everything is available in the API we use; therefore, no data set is required.

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Selective Kernel Spatial Feature Extraction based Deep Learning Approach for Identification and Classification of Archaeological Sites

Selective Kernel Spatial Feature Extraction based Deep Learn...

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2024 International Conference on Intelligent Algorithms for Computational Intelligence Systems, IACIS 2024

作者： Sajja, Sri Lavanya Alsalami, Zaid Sunil, G. Sunil Kumar, V. Mohamad Ramadan, Ghazi Malla Reddy Engineering College for Women Secunderabad India The Islamic University Engineering College of Technical Engineering Department of Computers Techniques Najaf Iraq Sr University School of Computer Science & Artificial Intelligence Warangal India Nitte Meenakshi Institute of Technology Dept. of Ai and Ml Bengaluru India Ahl Al Bayt University College of Mlt Karbala Iraq

ISBN: (纸本)9798350360660

Deep Learning (DL) based identification and classification of archaeological sites are being used progressively from satellite images obtained from Geographic Information System (GIS). Even though, there were promising results from the existing researches, there is still need to enhance the classification with distinct features of the satellite images. The methods found challenging to accurately or partially identify an archaeological feature especially in a complex landscape due to lack of distinction between archaeological and non-archaeological features. For this, the geo-referenced satellite images are considered in this research, which are pre-processed using min-max normalization for efficient data analysis and to remove unwanted data. The Selective kernel spatial Feature Extraction (SFE) module is used to improve the feature extraction process where the spatial features are extracted. The extracted features are then classified using Fully Convoluted Deep Neural Network (FCDNN) for effective identification and classification of archaeological sites. The results showed that the proposed SFE-FCDNN achieved better classification accuracy with 98.83%, precision of 97.41%, and an error rate of 1.71 when compared to the existing methods such as Neural Network (NN), and Backpropagation Neural Network (BNN). © 2024 IEEE.

关键词： Satellite imagery

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Exploration of verbal descriptions and dynamic indoors environments for people with sight loss

Exploration of verbal descriptions and dynamic indoors envir...

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Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023

作者： Alrashidi, Abdulaziz Cudd, Peter Abhayaratne, Charith Gotoh, Yoshihiko The Dept. of Computer Science The University of Sheffield Sheffield United Kingdom The Centre for Assistive Technology and Connected Healthcare The University of Sheffield Sheffield United Kingdom The Dept of Electronic and Electrical Engineering The University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9781450394222

Our study explored the navigational challenges of an unfamiliar room (with moving furniture and people) and what verbal guidance would be useful for visually impaired people(VIPs). A mainly qualitative approach of observation and interviews with ten VIPs revealed a lot about the challenges, guidance content and delivery. Further research is indicated to explore effective implementation. © 2023 Owner/Author.

关键词： Air navigation

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