datascience-based techniques have been widely applied in studies related to COVID-19 spread prediction. In these studies, different modeling techniques have been deployed to estimate the current and future trajectori...
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The economy is one of the determinants of how a person can live their life. In this current economic situation, inflation occurs everywhere, causing the prices of necessities to rise. In order to have a decent life, p...
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The economy is one of the determinants of how a person can live their life. In this current economic situation, inflation occurs everywhere, causing the prices of necessities to rise. In order to have a decent life, people must find a job with the highest possible salary to fulfill their needs. Various job industries have their salary range. Obtaining the information of salary level for the respective job is helpful for employers and employees to estimate the expected salary. This work aims to classify the salary level of jobs available in Indonesia and determine whether those salaries are decent enough. The learning methods are logistic regression, decision tree, k-nearest neighbor, support vector machine, voting classifier, bagging classifier, random forest, and boosting classifier. Random Forest achieved the best result with an accuracy rate of 72%. Based on the analysis result, factors such as job field, educational background, working experience, working hours, and job location influence salary.
Thyroid disease is a broad term for any medical disorder that impairs the thyroid gland's ability to generate enough hormones. It is not limited to any particular age group;it can strike anyone at any time. Detect...
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A network with no infrastructure, multiple hops, and dispersed nodes called a MANET. Nodes can communicate directly or through intermediaries without the need for permanent infrastructure. In dynamic networks like MAN...
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Pulmonary nodule quantification is essential in forecasting and diagnosing potential malignant nodules, providing critical information for early intervention and treatment planning. However, most existing assistant di...
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Musculoskeletal conditions encompass 150 varying conditions and approximately affect 1.71 billion people worldwide, according to the World Health Organization. Bone fractures are among the musculoskeletal conditions t...
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ISBN:
(数字)9798331513320
ISBN:
(纸本)9798331513337
Musculoskeletal conditions encompass 150 varying conditions and approximately affect 1.71 billion people worldwide, according to the World Health Organization. Bone fractures are among the musculoskeletal conditions that significantly impact individuals, families, societies, and healthcare systems, as they can lead to work absences, decreased productivity, disability, and a host of other life-limiting conditions. This study aims to evaluate the performance of superior-performing machine learning (ML) models that are fed with histograms of oriented gradients (HOG). The bestperforming ML models were chosen and implemented toward ensemble models in aims to reduce overfitting and address resource-limited settings. The results indicate that by using KNearest Neighbors (KNN), Decision Tree (DT), and Random Forest (RF), which yield the highest scores, the proposed ensemble models were able to increase the score, with the stacking ensemble model achieving accuracy score of 99.30%. Future research could focus on integrating advanced machine learning techniques, hybrid feature extraction methods, and larger datasets to enhance diagnostic accuracy and applicability in clinical environments.
Given a query patch from a novel class,one-shot object detection aims to detect all instances of this class in a target image through the semantic similarity ***,due to the extremely limited guidance in the novel clas...
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Given a query patch from a novel class,one-shot object detection aims to detect all instances of this class in a target image through the semantic similarity ***,due to the extremely limited guidance in the novel class as well as the unseen appearance difference between the query and target instances,it is difficult to appropriately exploit their semantic similarity and generalize *** mitigate this problem,we present a universal Cross-Attention Transformer(CAT)module for accurate and efficient semantic similarity comparison in one-shot object *** proposed CAT utilizes the transformer mechanism to comprehensively capture bi-directional correspondence between any paired pixels from the query and the target image,which empowers us to sufficiently exploit their semantic characteristics for accurate similarity *** addition,the proposed CAT enables feature dimensionality compression for inference speedup without performance *** experiments on three object detection datasets MS-COCO,PASCAL VOC and FSOD under the one-shot setting demonstrate the effectiveness and efficiency of our model,e.g.,it surpasses CoAE,a major baseline in this task,by 1.0%in average precision(AP)on MS-COCO and runs nearly 2.5 times faster.
Our interest is in paths between pairs of vertices that go through at least one of a subset of the vertices known as beer vertices. Such a path is called a beer path, and the beer distance between two vertices is the ...
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Children's physical, mental and emotional development depends heavily on sleep, with age-specific sleep needs fluctuating. Malnutrition may result from eating too little, absorbing nutrients poorly, being unwell, ...
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Sentiment analysis is widely used as a tool to find valuable insight from texts without explicitly expressed. Lots of techniques have already been used to get it but there still have shortcomings in data source or the...
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ISBN:
(数字)9798331519643
ISBN:
(纸本)9798331519650
Sentiment analysis is widely used as a tool to find valuable insight from texts without explicitly expressed. Lots of techniques have already been used to get it but there still have shortcomings in data source or the model strategy itself. Indonesian language approximately has 199 million speakers across the world where 44 million speakers natively. Even with that great number, the resources for the Indonesian language's natural language processing are still limited, and hard to find the perfect way to define sentiment analysis in the Indonesian language. The state-of-the-art sentiment analysis method uses LSTM on a small corpus while the best in town is Transformer where it's easy to transfer learning from the Transformer pre-trained model into specific tasks. From this potential, combining the Transformer pre-trained model with LSTM can be an innovative strategy. This research compared the hybrid model of Transformer-LSTM build using three Indonesian languages’ Transformer-based pre-trained model on sentiment analysis task which can surpass the Transformer model with the highest increased 2.40% accuracy and 3.02% on F1 score.
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