Competitive programming (CP) is a mind sports activity where people solve problems using command-line computerprograms to provide correct output for the given test cases. Competitors need to practice problem-solving ...
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Competitive programming (CP) is a mind sports activity where people solve problems using command-line computerprograms to provide correct output for the given test cases. Competitors need to practice problem-solving and mathematics as well as study algorithms and data structures to perform well in CP. This study aims to provide an original way to perform a trend analysis in CP, distinguishing topics frequently used in CP contests. To fulfill our goal, we create topic models based on previous topic modeling works to do natural language processing tasks using Latent Dirichlet Allocation (LDA) and Biterm Topic Model (BTM). For our dataset, we constructed a corpus from Codeforces blog posts, a popular website for competitive programmers, by extracting its content and user comments. Our results indicate that BTM is powerful enough to do trend analysis in CP. The trend analysis recognized that dynamic programming and complexity analysis have been the most prominent topics for the last ten years. data structures and string algorithms are runners-up that may have potential trends in the future. This study opens up further research on other methods to perform trend analysis using better topic models and corpora.
Rapid advancements in research in the field of DNA sequence discovery has led to a vast range of compression algorithms. The number of bits required for storing four bases of any DNA sequence is two, but efficient alg...
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This paper presents a systematic literature review of agile software development at decision making method for requirement engineering. Presently, agile software development method is operated to cope with requirement...
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This paper presents a systematic literature review of agile software development at decision making method for requirement engineering. Presently, agile software development method is operated to cope with requirements that changes dynamically. This study seeks to find out and discuss what types of method that have been exploited for decision making on managing feasible requirements and challenges of decision making in agile software development. Papers reviewed in this study are published from 2017 to present. Resulting 8 papers that have been identified of presenting decision making methods. Using these papers, 11 methods and 7 challenges of decision making identified. This study contributes a review of requirement management and engineering by providing decision making methods on agile software development and the challenges of decision making for requirement engineering.
Dengue fever is mainly caused by female mosquitoes from the genus Aedes. It predominantly occurs in equatorial to sub-tropical regions. The weather factors play a significant role in the mosquito life cycle, so a stud...
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ISBN:
(纸本)9781665473286
Dengue fever is mainly caused by female mosquitoes from the genus Aedes. It predominantly occurs in equatorial to sub-tropical regions. The weather factors play a significant role in the mosquito life cycle, so a study on the impact of climate parameters on dengue incidence is required. This study aimed to understand the statistical association between the annual fluctuation of dengue cases with climate factors in Indonesia. Climatic data, annual rainfall, and annual mean ambient temperature of Indonesia were obtained from *** from 2010 to 2020, while the data on the annual incidence of dengue fever in Indonesia were collected from the Indonesian Health Profile by the Ministry of Health of Indonesia from 2010 to 2020. The association between climatic factors with dengue cases was calculated with Spearman statistical test after the data was indicated as not normally distributed. In addition, we performed Poisson regression analysis to examine how the changes in climatic parameters affect the dengue cases. The rain precipitation was insignificantly correlated with the dengue incidence in Indonesia during the study time. In contrast, the ambient temperature statistically showed a strong association with the dengue cases. The association between climatic factors and the number of dengue cases suggests that the model would likely be prospectively applied to the dengue early warning system as a nationwide intervention to reduce the epidemic impact in Indonesia.
Capacitated Vehicle Routing Problem (CVRP) is the vehicle routing problem in which vehicles with limited space have to drop off items at different places. This item consists of certain amounts, weight or volume, and t...
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In carrying out drilling projects at PT China Oilfields Services Limited ( COSL) Indo, especially Project 1 to Project 4, there were a mismatch between the initial plan of the project and the actualisation in the fiel...
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The inference of mitochondrial haplogroups is an important step in forensic analysis of DNA samples collected at a crime scene. In this paper we introduced efficient inference algorithms based on Jaccard similarity be...
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With the increase of interest in Facial Expression Recognition (FER) in the past few decades. Several challenges surfaced with the invention of many different FER models which are often based on Convolution Neural Net...
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With the increase of interest in Facial Expression Recognition (FER) in the past few decades. Several challenges surfaced with the invention of many different FER models which are often based on Convolution Neural Network (CNN) architectures. Recently, an attention-based transformer model has been presented to address FER. One of the major issues with Transformers is the need for a large data quantity for training. Therefore, in this paper, we propose to learn how to fine-tune a vision transformer-based (ViT) model using a limited dataset. We will be using the JAFFE dataset, which consists of only 213 images containing seven different emotions. The proposed method is evaluated using several fine-tuning methods, such as adding dropout, data augmentation, and layer freezing. We compared the models implemented with 5% dropout regularization, augmented dataset (up to 5000 images), and freezing the initial model's layers, fine-tuning around a fourth of the last layers. The best model was achieved by fine-tuning ViT L-16 with 96.06% accuracy, trained with 5% dropout in the augmented dataset, and freezing the initial 21st layers. We also compared our model to the other previous work model and the results showed that our model reached the state-of-the art for the JAFFE dataset.
Weeds compete for natural resources both in forest areas, harming the development of native vegetation, and in agricultural areas, affecting crop quality. The need then arises to classify these species, so that mechan...
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Social media is an online media that functions as a platform for users to participate, share, create, and exchange information through various forums and social networks. The rapid increase in social media activity ca...
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Social media is an online media that functions as a platform for users to participate, share, create, and exchange information through various forums and social networks. The rapid increase in social media activity causes an increase in the number of comments on social media. This is prone to triggering debate due to the easy formation of open discussions between social media users. However, the debate often triggers the emergence of negative things, causing great fights on social media. Social media users often use comments containing toxic words to argue and corner a party or group. This study conducted an experiment to detect comments containing toxic sentences on social media in Indonesia using a Pre-Trained Model that was trained for Indonesian. This study performed a multilabel classification and evaluated the classification results generated by the Multilingual BERT (MBERT), IndoBERT, and Indo Roberta Small models. The optimal result of this study is to use the IndoBERT model with an F1 Score of 0.8897.
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