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AI Dermatologist: Skin Cancer Detection with Deep Learning Technique

AI Dermatologist: Skin Cancer Detection with Deep Learning T...

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International Conference on computing and Networking Technology (ICCNT)

作者： Afraz Ul Haque Rupak Sadman Sadik Khan Alaya Parvin Alo Rupa Ghosh Md Fatin Ishrak Md Sanowar Hossain Sabuj Department of Computer Science and Engineering Daffodil International University Dhaka Bangladesh Department of Computer Science and Engineering Khulna University Khulna Bangladesh Department of Electrical and Electronic Engineering North South University Dhaka Bangladesh College of Business Administration International University of Business Agriculture and Technology Dhaka Bangladesh

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

this paper explores the application of deep learning technologies in the detection and diagnosis of skin cancer, leveraging advanced convolutional neural networks (CNNs) such as VGG-16, ResNet50, and MobileNetV2. Given the increasing incidence of skin cancer worldwide, there is a critical need for more accurate and efficient diagnostic methods. Our study employs transfer learning to enhance the capability of these networks, enabling them to detect skin cancer from dermoscopic images with a high degree of accuracy, often surpassing human expert performance. We detail the process of data collection, preprocessing, model training, and evaluation, emphasizing the adaptation of these models to skin cancer detection. the results demonstrate significant improvements in diagnostic accuracy, with MobileNetV2 showing notable efficiency in processing and resource utilization—qualities that are ideal for real-time diagnostic applications. In MobileNetV2 we achieved 97% accuracy. Furthermore, the study addresses the challenges of adversarial attacks and the integration of non-image data to refine diagnostic procedures. Our findings highlight the transformative potential of AI in medical diagnostics, suggesting that deep learning could become a cornerstone in the early detection and treatment of skin cancer, thereby improving patient outcomes substantially.

关键词： Deep learning Training Adaptation models Accuracy Transfer learning Real-time systems Convolutional neural networks Artificial intelligence Skin cancer Residual neural networks

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A Comparative Analysis of Wavelet and Fourier Transform for Image Fusion

A Comparative Analysis of Wavelet and Fourier Transform for ...

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International Conference on computing and Networking Technology (ICCNT)

作者： T. Kuppuraj Ramesh Saini R. Jayadurga Diksha Aggarwal Muktha Eti Komal M. Birare Department of Computer Applications Karpagam Academy of Higher Education Coimbatore India Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India Department of Business Administration Prince Shri Venkateshwara Padmavathy Engineering College Chennai Quantum University Research Center Quantum University School of Engineering and Technology Electrical and Electronics Engineering JAIN (Deemed to be University) Bangalore Karnataka India Department of Information Technology Vishwakarma Institute of Technology Pune India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

the purposes of image fusion are to acquire a comprehensive picture which can show extra unique visual facts while compared to its original person supply pix. On this regard, a comparative evaluation of Fourier remodel (feet) and Wavelet transform (WT) for photo fusion is proposed. Firstly, a wavelet-based totally fusion method is advanced using Discrete Wavelet transform (DWT) followed by singular fee decomposition (SVD). the proposed approach uses a pair of images which includes low-pass and high-skip images, with which the fusion method is completed. then again, a feet-primarily based fusion technique is advanced through making use of the 2d-ft at the pair of snap shots after which performing SVD on them. Secondly, each fusion algorithms are applied on a set of pictures which will compare the overall performance. In the end, several metrics together with PSNR (peak signal-to-Noise Ratio), SSIM (Structural Similarity Index) and EN (Entropy) are used to assess the fusion performance in terms of each objective and subjective criteria. the received effects virtually display that the wavelet-based totally fusion method is greater green for photograph fusion in comparison to that primarily based at the toes. the better overall performance is attributed to the better

关键词： Measurement Visualization Fourier transforms PSNR Image edge detection Noise Wavelet analysis Discrete wavelet transforms Indexes Image fusion

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Reliable distributed database systems (abstract only) 87

Reliable distributed database systems (abstract only)

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Proceedings of the 15th annual conference on computer Science

作者： Sang Hyuk Son Department of Computer Science University of Virginia Charlottesville Virginia

ISBN: (纸本)9780897912181

We are investigating the problem of ensuring global consistency in the context of distributed database systems. Our current research effort concentrates on theoretical study of reliability mechanisms such as algorithm design and performance characterization. In addition, we are building a testbed for evaluating different reliability mechanisms through detailed simulation and actual *** is the key factor in improving the availability of distributed database systems. A major restriction in using replication is that replicated copies must behave like a single copy. We have developed algorithms for replication control using tokens [2, 5]. the next step of our research in this direction would be to evaluate different partial operation policies which are critical in maintaining the correctness and achieving the high availability of distributed database systems. Two alternatives are possible when a partition occurs: pessimistic and optimistic. Neither of the two alternatives is superior to the other. higher availability achieved by an optimistic approach may be penalized during recovery from partition failures, by backing out committed transactions which violate consistency *** if the replication and concurrency control mechanisms are correct and maintain the consistency of the database, the failures of hardware and/or software at the processing site and communication network may destroy the consistency of the database. In order to cope with failures, distributed database systems must provide recovery mechanisms. the goal of checkpointing is to save database states on a separate secure device so that the database can be recovered when errors and failures occur. A checkpointing mechanism which does not interfere with the transaction processing in distributed environment is highly desirable for many applications, where restricting transaction activity during checkpointing is not feasible. Our earlier research has resulted in the developme

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Low energy routing platforms for optical interconnects using active plasmonics integrated with Silicon Photonics

Low energy routing platforms for optical interconnects using...

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International Conference on Transparent Optical Networks

作者： Konstantinos Vyrsokinos Sotirios Papaioannou Dimitrios Kalavrouziotis Filimon Zacharatos Laurent Markey Jean-Claude Weeber Alain Dereux Ashwani Kumar Sergey I. Bozhevolnyi Michael Waldow G. Giannoulis Dimitrios Apostolopoulos Tolga Tekin Hercules Avramopoulos Nikos Pleros Informatics and Telematics Institute Center for Research and Technology Hellas Thessaloniki Greece Informatics and Telematics Institute Center for Research and Technology Hellas 57001 Thessaloniki Greece School of Electrical & Computer Engineering National Technical University of Athens Athens Greece Institut Carnot de Bourgogne University of Burgundy Dijon France Faculty of Engineering Institute of Technology and Innovation University of Southern Denmark Odense M Denmark AMO GmbH Gesellschaft für Angewandte Mikro-und Optoelektronik GmbH Aachen Germany Fraunhofer Institute for Reliability and Microintegration Berlin Germany

ISBN: (纸本)9781479906840

Power consumption and bandwidth of electronics appear as the main set of technology barriers in next-generation Data Center and high-performance computing (HPC) environments. the limited capacity and pitch lane of electrically wired interconnects require the development of new disruptive technologies to cope with the massive amount of data moving across all hierarchical communication levels, namely rack-to-rack, backplane, chip-to-chip and even on-chip interconnections. Plasmonics comes indeed as a disruptive technology that enables seamless interoperability between light beams and electronic control signals through the underlying metallic layer, providing thereby an inherent energy-efficient platform for merging broadband optical links with intelligent electronic processing. In ICT PLATON project we are aiming to the exploitation of plasmonics for the demonstration of novel hybrid Si-plasmonic router prototypes for chip-to-chip and on-chip interconnection, starting with a 2×2 WDM-traffic router with up to 640 Gb/s capacity and proceeding to a 4×4 router with up to 1.12 Tb/s throughput. In this article, we will present preliminary results of a 2×2 Si-plasmonic router that employs two 8:1 Si-ring-based multiplexers followed by a novel hybrid Si-plasmonic Mach Zehnder Interferometer switch with a record low power x time constant product.

关键词： Optical waveguides Gratings Silicon Couplers Plasmons Optical switches Bandwidth

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A Hardware Accelerator for Quantile Estimation of Network Packet Attributes

A Hardware Accelerator for Quantile Estimation of Network Pa...

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Euromicro symposium on Digital System Design

作者： Carolina Gallardo-Pavesi Yaime Fernandez Javier E. Soto Cecilia Hernández Miguel Figueroa Department of Electrical Engineering Department of Computer Science Universidad de Concepcion Concepción Chile Center of Biotechnology and Bioengineering (CeBiB) Advanced Center for Electrical and Electronics Engineering (AC3E)

ISBN: (数字)9798350380385

ISBN: (纸本)9798350380392

Measuring statistical properties of network traffic can improve our understanding of traffic distribution and help us detect short and long-term anomalies. However, computing the exact value of these properties requires significant storage and computation, which limits their application in high-speed networks. Hardware accelerators provide the computational power to process a large sequence of network packets with high throughput and low latency, but their performance is ultimately limited by the amount of on-chip memory available on the device. Consequently, researchers have proposed sketch-based algorithms to estimate properties of a data stream with sub linear memory and theoretical estimation error bounds. In this paper, we present a streaming algorithm and hardware accelerator for quantile estimation, which is based on the architecture of the KLL sketch. Implemented on an AMD Virtex XCU55 UltraScale+ FPGA, the accelerator operates at a clock frequency of 356 MHz, thereby achieving a minimum line rate of 182 Gbps and a maximum estimation latency of 4.33 µs. When processing a set of 10 real traffic traces of up to 123 million packets, the accelerator estimates 1000 packet-size quantiles per trace with a median error of 0.39% or less, and a maximum error of 1.3% or less across all traces.

关键词： performance evaluation Estimation error Memory management Telecommunication traffic Logic gates throughput System-on-chip Low latency communication Hardware acceleration Field programmable gate arrays

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MANET Routing Protocol performance Comparison: DSDV, AODV, and DSR

MANET Routing Protocol Performance Comparison: DSDV, AODV, a...

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Innovative Approaches in Smart Technologies (ISAS), International symposium on

作者： Kamred Udham Singh Ankit Kumar Gaurav Kumar Tanupriya Choudhury Ketan Kotecha School of Computing Graphic Era Hill University Dehradun India Department of Computer Engineering & Applications GLA University Mathura UP India CSE Dept. Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune Maharashtra India Symbiosis Centre for Applied Artificial Intelligence Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune Maharashtra India

Mobile Ad hoc Networks (MANETs) may self-configure and rely on wireless connections rather than a permanent infrastructure; hence this research delves into their intricacies. this research aims to better understand how MANETs function. MANETs are characterized by their high degree of dynamism and adaptability to changes in network architecture. these networks are made up of mobile nodes that are independent and can perform the functions of both a host and a router. Having said that, this flexibility does provide a number of substantial issues, notably in the area of routing. the unexpected and fluid nature of MANET topology, which is related to the mobility of the nodes, makes routing a hard process. the effectiveness of the network is strongly reliant on the efficacy of the routing protocols that are implemented; therefore this is an important consideration. Our study analyses the capabilities of three popular MANET routing protocols: DSDV, AODV, and DSR. these protocols must be compared using end-to-end latency, packet delivery percentage, and lost packet ratio across different network densities and mobility patterns. In our simulations, we seek to replicate a wide variety of situations that can occur in the real world by altering the number of nodes, the connection counts, and the pause periods. these simulations are carried out with the help of the Network Simulator 2 (version 2.35), a programme that is well-known for its use in network research. Additionally, the graphical representation of the data is carried out with the assistance of gnuplot. Our first findings suggest that AODV has a significant advantage over DSDV and DSR when it comes to handling the dynamic networking environment of MANETs more effectively. this is especially true in situations characterised by high node mobility and variable network density. this research not only highlights the necessity of selecting the appropriate routing protocol in MANETs, but it also offers a thorough framework fo

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A Novel Framework for Fake News Detection Using LDA and QDA

A Novel Framework for Fake News Detection Using LDA and QDA

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International Conference on computing and Networking Technology (ICCNT)

作者： Challamalla Satya Srinivas Sp Devanandhan Venigalla Venkata Manoj S Abhishek Anjali T Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Rolls-Royce Inc Banglore India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

In today’s digital age, the rise of online media has made information readily accessible, but it has also facilitated the rapid spread of fake news. this phenomenon undermines trust in reliable news sources and fosters confusion among the public. Consequently, individuals must exercise caution when sharing information, verifying its credibility to prevent the spread of false information and uphold the trustworthiness of reputable channels. A highly accurate system has been designed to detect fake news efficiently and with a high level of accuracy. In this paper, an enhanced approach is suggested for classification based on the Linear Discriminant Analysis and Quadratic Discriminant Analysis models, some advanced methods that help fight against fake media stories. A number of natural language processing techniques, including tokenization, stop word removal, and URL and HTML tag removal, were applied to a comprehensive dataset of fake news collections. For the purpose of classification, two models-Linear Discriminant Analysis and Quadratic Discriminant Analysis models-were applied for the correct detection of fake news. In order to evaluate effectiveness, performance measures such as accuracy, precision, recall, F1 score, confusion matrix, and ROC curve were critically analyzed. the accuracy of LDA is 97%, while QDA achieves 67%. this paper attempts to provide a step toward efforts engaged in fighting misinformation in the digital age and trying to keep reliable news sources intact.

关键词： Uniform resource locators Analytical models Visualization Accuracy Predictive models Information age Tokenization Linear discriminant analysis Reliability Fake news

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Exploring Welded Joint Integrity Using Microstructural Characterization Using Deep Encoders

Exploring Welded Joint Integrity Using Microstructural Chara...

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International Conference on computing and Networking Technology (ICCNT)

作者： A. Muthumari C. Sushama Suresh Kumar Grandhi Ashish Kaushal Muhammad Nurtanto Mohana Sundaram K Department of Computer Science & Engineering Anna University Regional Campus Madurai Tamil Nadu India Department of CSE School of Computing Mohan Babu University (erstwhile Sree Vidyanikethan Engineering College) Tirupathi AP India ICFAI Foundation for Higher Education Hyderabad Telangana India Jindal Global Business School O P Jindal Global University Sonipat Haryana India Department of Mechanical Engineering Polytechnic State Jakarta Demak Indonesia Department of CSE R.M.D. Engineering College Tamilnadu India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

the integrity of welded joints is a crucial influence in the field of structural engineering, as it has significant implications for the dependability and safety of diverse sectors, including aerospace, automotive, and construction. In order to ensure the optimal performance of welded joints, it is important to evaluate their microstructural features. this paper explains a novel methodology for investigating the integrity of welded joints by employing microstructural characterization with the use of a deep encoder. the deep encoder is a neural network design that has exhibited exceptional skills in applications related to image processing and feature extraction. In the course of our study, we modified this particular framework to examine microstructural pictures of welded joints, facilitating the acquisition of significant information pertaining to their structural soundness. the methodology employed in this study entails the acquisition of high-resolution images of welded connections, often obtained by the utilization of scanning electron microscopy or comparable imaging techniques. the findings of our investigation exhibit promise, as they offer a more precise and effective approach for evaluating the integrity of welded joints in contrast to conventional manual techniques.

关键词： Scanning electron microscopy Recurrent neural networks Welding Imaging Transforms Manuals Feature extraction Structural engineering Testing Automotive engineering

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A Few-Shot Learning for HAR Using 3D Siamese Network

A Few-Shot Learning for HAR Using 3D Siamese Network

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International Conference on computing and Networking Technology (ICCNT)

作者： Hua Guanghui G. Hemantha Kumar V. N. Manjunath Aradhya Punithavalli Dept. of studies in Computer Science University of Mysore Mysuru India Dept. of Computer Applications JSS Science and Technology University Mysuru India Department of Computer Applications Bharathiar University Coimbatore India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

In artificial intelligence, deep learning techniques were applied in a wide field due to their ability to automatically learn complex patterns from raw data, such as image classification, object detection, image generation, and video analysis in computer vision. these applications are just the tip of a substantial iceberg. With the development of deep techniques to achieve state-of-art accuracy, learn precisely relevant features from raw data, and improve the robustness of models to make them versatile solutions. the traditional deep learning techniques require vast computational resources, including high-performance computer GPUs or TPUs, and can be expensive in terms of hardware. In Human Activity Recognition Systems (HARs). the video needs more computational resources than image processing. In this paper, we proposed a few-shot learning approach based on a 3D Siamese Network with depth video sequences to address the action video similarity or dissimilar problem. Convolutional Neural Networks (CNNs) are well-suited for images and spatial data processing. the 3DCNN is an extension of CNNs to incorporate an additional temporal dimension to capture the temporal pattern. From the 3D Siamese network, we extract more effective features with spatial-temporal action information from raw data. We employed the 3DCNNs Siamese Network (3DCNNs+SN) with shared weight to recognize or classify a new class of data without new sample data only based on learning training existing sample constructed model. In addition, we divided the benchmark dataset MSR Action 3D dataset into sub-dataset1 (SD-1), sub-dataset2 (SD-2) and sub-dataset3(SD-3) to train and validate our proposed method. For dissimilar sub-dataset 2 we got a 98.1% accuracy, 33% on high-similar sub-dataset 3 and $\mathbf{63.5\%}$ on merged sub-dataset SD-4 from sub-dataset2 (SD-2) and sub-dataset3(SD-3).

关键词： Solid modeling three-dimensional displays Accuracy Computational modeling Feature extraction Robustness Data models Human activity recognition Data mining Few shot learning

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Design and simulation of a rooftop PV System in Taylor's University Lakeside Campus 15

Design and simulation of a rooftop PV System in Taylor's Uni...

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15th International Engineering and computing Research Conference, EURECA 2021

作者： Krishna, Y. Fauzan, M.F. Gan, N.B. Muhammad Nurhisham Taylor's University School of Computer Science and Engineering Selangor Subang Jaya Malaysia Solar Energy Research Institute Universiti Kebangsaan Malaysia Selangor Bangi 43600 Malaysia

Solar photovoltaic (PV) system is proven to be a future-proof type of power generation for growing economies. there are almost zero pollutants released, low maintenance cost with high reliability as the lifespan of a solar PV stretches up to 30 years, a well-sought alternative form of sustainable energy. Moreover, the electricity consumption in Taylor's University (TU), Malaysia is very high, as a consequence, a huge fraction of the fund is used to settle an RM450,000 electricity bill on average annually. In this paper, the study focused on how to reduce electricity consumption in TU by proposing a design of a comprehensive solar PV system. PVSYST and Sketchup software are used to design and analyze the PV system. In the present study, a Grid-Connected Photovoltaic (GCPV) mounted on the available roof space of TU is investigated. Also, a detailed economic analysis that includes the payback period and annual savings achieved through the proposed PV installation is analyzed. Annual savings of RM 267,621.00 can be made upon utilizing the proposed idea. Besides that, TU would be able to recover the initial investment cost in approximately 8 years of payback period, proving that the implementation of a 433kWp of solar PV unit is a smart option to address the sustainable energy goals. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Energy conservation

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