Opioid abuse and dependence have emerged as a pressing global concern, posing significant challenges to public health and society. Early identification and prediction of opioid dependency represent crucial steps in mi...
Opioid abuse and dependence have emerged as a pressing global concern, posing significant challenges to public health and society. Early identification and prediction of opioid dependency represent crucial steps in mitigating its abuse impact on individuals and communities. The application of machine learning techniques to analyze medical data has opened new avenues for achieving this goal. While this field and the prediction is still in its infancy, our research explores the potential of several machine learning algorithms including LightGBM for this risk prediction. To tackle the inherent class imbalance in the MIMICIII dataset, we implemented the Synthetic Minority Oversampling Technique (SMOTE). We developed predictive models using four distinct algorithms: decision trees, random forests, support vector machines, and LightGBM. These models were meticulously evaluated to assess their performance. Ultimately, our findings revealed that the LightGBM model outperformed the other algorithms, demonstrating superior accuracy and achieving a higher Area Under the Curve value. This outcome underscores the potential of LightGBM as a valuable algorithm in the early prediction of the risk of opioid dependence, thereby offering substantial benefits to both patients and society at large.
Skin is the most powerful shield human organ that protects the internal organs of the human body from external attacks. This important organ is attacked by a diverse range of microbes such as viruses, fungi, and bacte...
Skin is the most powerful shield human organ that protects the internal organs of the human body from external attacks. This important organ is attacked by a diverse range of microbes such as viruses, fungi, and bacteria causing a lot of damage to the skin. Apart from these microbes, even dust plays important role in damaging skin. Every year several people in the world are suffering from skin diseases. These skin diseases are contagious and spread very fast. There are varieties of skin diseases. Thus it requires a lot of practice to distinguish the skin disease by the doctor and provide treatment. In order to automate this process several deep learning models are used in recent past years. This paper demonstrates an efficient and lightweight modified SqueezeNet deep learning model on the HAM10000 dataset for skin cancer classification. This model has outperformed state-of-the-art models with fewer parameters. As compared to existing deep learning models, this SqueezeNet variant has achieved 99.7%, 97.7%, and 97.04% as train, validation, and test accuracies respectively using only 0.13 million parameters.
In recent times, Diabetic Retinopathy (DR) has become a complication of major degree for diabetic patients, in which the blood vessels present in the eye retina are severely damaged. This in most cases has lead to a l...
In recent times, Diabetic Retinopathy (DR) has become a complication of major degree for diabetic patients, in which the blood vessels present in the eye retina are severely damaged. This in most cases has lead to a loss of vision as observed from records of DR patients, and if left untreated, can cause blindness. As per the estimates of the World Health Organization, DR will impact around 224 million people by 2040. This research study presents a convolutional neural network (CNN) model, followed by employing ensemble learning over various ML algorithms through max voting, for the task of image classification for detecting Diabetic Retinopathy using color fundus images, with the goal of improving the accuracy and efficiency of the diagnostic process. The proposed model is designed to address the challenges of real-world data, such as variability in the appearance of images that belong to the same class and class imbalance. The dataset used for this study is EYEPACS, which is widely used for training and testing models for detecting Diabetic Retinopathy. The Metrics that are used for measuring the performance of the proposed model are accuracy, precision, and F1-S core. This study obtains an accuracy of 95.4 percent.
In the modern manufacturing industry, collaborative architectures are growing in popularity. We propose an Industry 5.0 value-driven manufacturing process automation ecosystem in which each edge automation system is b...
In the modern manufacturing industry, collaborative architectures are growing in popularity. We propose an Industry 5.0 value-driven manufacturing process automation ecosystem in which each edge automation system is based on a local cloud and has a service-oriented architecture. Additionally, we integrate cloud-based collaborative learning (CCL) across building energy management, logistic robot management, production line management, and human worker Aide local clouds to facilitate shared learning and collaborate in generating manufacturing workflows. Consequently, the workflow management system generates the most effective and Industry 5.0-driven workflow recipes. In addition to managing energy for a sustainable climate and executing a cost-effective, optimized, and resilient manufacturing process, this work ensures the well-being of human workers. This work has significant implications for future work, as the ecosystem can be deployed and tested for any industrial use case.
Poetry writing and analysis are both qualitative subjects. To get over any possible biases of human perspective it is necessary to map these poetic features on a scale of real numbers. Free verse is a form of poetry t...
Poetry writing and analysis are both qualitative subjects. To get over any possible biases of human perspective it is necessary to map these poetic features on a scale of real numbers. Free verse is a form of poetry that is unrestricted by the requirements of metre and rhyme. This article is focused on free verse compositions viewed through the lens of rhetorical properties or figures of speech. The state-of-the-art model FoSCal cannot handle free verse compositions. On the other hand, FVRCal is a state-of-the-art tool for free verse that computes rhyme (not FoS) on a numerical scale. The proposed tool, FVFoSCal, covers a broader section of alankāra than the state-of-the-art model. It can measure the alankāra score for any free verse composition. The scores generated by the proffered tool form a dataset, FoSSset, which is later used to determinethestyleofthepoetusingsuitablestatistical tests. The statistical analysis performed in this experiment establishes commonality and diversity among the four renowned poets of Hindi literature, namely; Bachchan, Dushyant Kumar, Nirala, and Agyey.
In the realm of Decentralized Finance (DeFi), this manuscript introduces a Hybrid Cross-Chain Model. As DeFi architectures grapple with the complexities of monolithic single-chain platforms, our proposed model orchest...
详细信息
ISBN:
(数字)9798350391343
ISBN:
(纸本)9798350391350
In the realm of Decentralized Finance (DeFi), this manuscript introduces a Hybrid Cross-Chain Model. As DeFi architectures grapple with the complexities of monolithic single-chain platforms, our proposed model orchestrates a symphony of multiple chains to facilitate seamless cross-chain communication, offering a poised solution to scalability and transaction speed challenges. Incorporating modeling effects and simulations, our rigorous performance evaluation underscores the model's excellence and includes an in-dept. analysis of its performance, particularly focusing on robust security measures. The model is positioned as a cornerstone in an interconnected DeFi landscape by emphasizing stringent measures to ensure data integrity and uphold consensus mechanisms. User-centric enhancements promise swift transaction confirmations and reduced fees, improving the overall experience. The abstract culminates with a comparative analysis, positioning the Hybrid Cross-Chain Model as an innovative solution with profound implications for the future of DeFi. This manuscript advocates for ongoing research and development, heralding a new era of sophistication and resilience in decentralized finance.
In the game of football (soccer), evaluation of players for transfers, scouting, team building, and strategic planning are essential. Due to the huge pool of grassroots players, brief career span, varying performance ...
详细信息
Video content has been increasing at a very high pace, so the need for summarizing videos is of urgent need. Video summarization emphasizes on quick go-through of video content. In the last few decades, the field of v...
Video content has been increasing at a very high pace, so the need for summarizing videos is of urgent need. Video summarization emphasizes on quick go-through of video content. In the last few decades, the field of video summarization has inspired a lot of research. Many of the techniques have been proposed by different researchers, but most of them are not able to create summaries of general videos, i.e., they are generally suitable for a set of categories of videos. To overcome this problem, we have introduced a general framework for video summarization, where we have used a pre-trained VGG16 model for feature extraction, and based on the features, we found the frame level importance using a Long Short Term memory (LSTM) network. After that, we selected the frames with high frame-level scores and finally combined them to form the video summary. Experimenting with the different types of videos taken from the different datasets shows that the proposed methodology outperforms the existing state-of-the-art methods.
In the revolution of wireless communication system multi-user MIMO is one of the proliferation antenna technology in 5G currently being developed to meet the need for high data speed and better service quality for hig...
详细信息
Automatic license plate recognition system plays an essential role in real life applications, especially those related to security and traffic managements. It essentially extracts and recognizes number plate informati...
详细信息
暂无评论