In each school association, there is a constant need of meeting rooms for direct different occasions. It is discovered that there is one gathering hall in each institution, regardless of whether it is a school or univ...
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Breast cancer, a significant global health problem that is mainly affecting women, demonstrates the importance of early detection to enhance survival rates. Medical image classification is a significant field that uti...
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A remote organization comprises of the many organization geographies that are broadly circulated, associated by moving hubs alluded to as portable hubs. Transfer innovation is utilized to upgrade parcel conveyance and...
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This project aims to solve the problem of securely storing and retrieving luggage in popular public places. There have been various methods that solve the above problem but there is a need for a more simple and effici...
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Breast cancer is a common cause of death among women *** imaging is a valuable diagnostic tool in breast cancer ***,the accuracy of computer-aided diagnosis systems for breast cancer classification is limited due to t...
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Breast cancer is a common cause of death among women *** imaging is a valuable diagnostic tool in breast cancer ***,the accuracy of computer-aided diagnosis systems for breast cancer classification is limited due to the lack of well-annotated *** study proposes a deep learning(DL)-based framework for breast mass classification using ultrasound images,which incorporates a novel data augmentation technique,generative adversarial network(GAN),and transfer learning(TL).Automating early tumor identification and classification in breast cancer diagnosis can save lives by improving the accuracy of diagnoses and reducing the need for invasive ***,the limited availability of wellannotated datasets for ultrasound images of breast cancer has hampered the development of accurate computer-aided diagnosis *** accuracy of breast mass classification using ultrasound images is limited due to the lack of well-annotated *** data augmentation techniques have limitations in applications with strict guidelines,such as medical ***,there is a need to develop a novel data augmentation technique to improve the accuracy of breast mass classification using ultrasound *** proposed framework can be extended to other medical imaging applications,where the availability of well-annotated datasets is *** GAN-based data augmentation technique and TL-based feature extraction can be used to improve the accuracy of classification models in other medical imaging ***,the proposed framework can be used to develop accurate computer-aided diagnosis systems for breast cancer detection in clinical *** proposed framework incorporates a DL-based approach for breast mass classification using ultrasound *** framework includes a GAN-based data augmentation technique and TL for feature *** dataset used for training and testing the model is the breast ultraso
A complete examination of Large Language Models’strengths,problems,and applications is needed due to their rising use across *** studies frequently focus on single-use situations and lack a comprehensive understandin...
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A complete examination of Large Language Models’strengths,problems,and applications is needed due to their rising use across *** studies frequently focus on single-use situations and lack a comprehensive understanding of LLM architectural performance,strengths,and *** gap precludes finding the appropriate models for task-specific applications and limits awareness of emerging LLM optimization and deployment *** this research,50 studies on 25+LLMs,including GPT-3,GPT-4,Claude 3.5,DeepKet,and hybrid multimodal frameworks like ContextDET and GeoRSCLIP,are thoroughly *** propose LLM application taxonomy by grouping techniques by task focus—healthcare,chemistry,sentiment analysis,agent-based simulations,and multimodal *** methods like parameter-efficient tuning(LoRA),quantumenhanced embeddings(DeepKet),retrieval-augmented generation(RAG),and safety-focused models(GalaxyGPT)are evaluated for dataset requirements,computational efficiency,and performance *** for ethical issues,data limited hallucinations,and KDGI-enhanced fine-tuning like Woodpecker’s post-remedy corrections are *** investigation’s scope,mad,and methods are described,but the primary results are *** work reveals that domain-specialized fine-tuned LLMs employing RAG and quantum-enhanced embeddings performbetter for context-heavy *** medical text normalization,ChatGPT-4 outperforms previous models,while two multimodal frameworks,GeoRSCLIP,increase remote ***-efficient tuning technologies like LoRA have minimal computing cost and similar performance,demonstrating the necessity for adaptive models in multiple *** discover the optimum domain-specific models,explain domain-specific fine-tuning,and present quantum andmultimodal LLMs to address scalability and cross-domain *** framework helps academics and practitioners identify,adapt,and innovate LLMs for different *** work
The rapid growth of the Internet of Things(IoT)has raised security concerns,including MQTT protocol-based applications that lack built-in security features and rely on resource-intensive Transport Layer Security(TLS)*...
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The rapid growth of the Internet of Things(IoT)has raised security concerns,including MQTT protocol-based applications that lack built-in security features and rely on resource-intensive Transport Layer Security(TLS)*** paper presents an approach that utilizes blockchain technology to enhance the security of MQTT communication while maintaining *** approach involves using blockchain sharding,which enables higher scalability,improved performance,and reduced computational overhead compared to traditional blockchain approaches,making it well-suited for resource-constrained IoT *** approach leverages Ethereum blockchain’s smart contract mechanism to ensure trust,accountability,and user ***,we introduce a shard-based consensus mechanism that enables improved security while minimizing computational *** also provide a user-controlled and secured algorithm using Proof-of-Access implementation to decentralize user access control to data stored in the blockchain *** proposed approach is analyzed for usability,including metrics such as bandwidth consumption,CPU usage,memory usage,delay,access time,storage time,and jitter,which are essential for IoT application *** analysis demonstrated that the approach reduces resource consumption,and the proposed system outperforms TLS and existing blockchain approaches in these metrics,regardless of the choice of the MQTT ***,thoroughly addressing future research directions,including issues and challenges,ensures careful consideration of potential advancements in this domain.
IoT edge computing facilitates data to be processed at a location closer to the place where it is generated. Placing computing closer allows for faster and more reliable service to the users. It also benefits latency-...
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Understanding consumer attitudes toward specific products is crucial for boosting sales in the e-commerce industry. To effectively target customers with popular products based on reviews, the classification of consume...
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Online content moderation faces significant challenges in identifying offensive language across diverse linguistic environments. This study compares the performance of five advanced BERT models mBERT, BERT Base, BERT ...
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