Understanding the mechanistic interpretability of mutation effects in a protein can help predict the clinical implications of the genetic variants. Hence, computational variant effect predictions that involve protein ...
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This paper investigates the influence of local lag on the reaction forces in a networked virtual maze system incorporating haptic feedback by experiment. In the experiment, participants move a box from the starting po...
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ISBN:
(数字)9798350353624
ISBN:
(纸本)9798350353631
This paper investigates the influence of local lag on the reaction forces in a networked virtual maze system incorporating haptic feedback by experiment. In the experiment, participants move a box from the starting position to the target point by using Raising method with haptic device. We measure the average operation time and the average of average reaction force for three different moving velocities and three distinct local lags. Experimental results reveal that as the moving velocity increases and the local lag becomes higher, the two measures become larger. Thus, we illustrate that there exists a strong relationship among the average operation time, the average of average reaction force, moving velocity, and local lag, through multiple regression analysis.
The use of balanced medical datasets is essential to improve the precision and accuracy of machine learning models in the healthcare field. However, dataset imbalance often becomes an obstacle, especially in the diagn...
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ISBN:
(数字)9798350368970
ISBN:
(纸本)9798350368987
The use of balanced medical datasets is essential to improve the precision and accuracy of machine learning models in the healthcare field. However, dataset imbalance often becomes an obstacle, especially in the diagnosis of skin diseases. This research aims to develop a Generative Adversarial Networks (GAN) method that is more effective in generating synthetic skin datasets to overcome problems in integrating medical datasets. The methods used include developing and training a GAN model to produce realistic synthetic skin images, with a focus on improving the quality and diversity of the synthetic data produced. Important results from this research show that the developed GAN model is able to produce synthetic skin images that are not only realistic but also able to balance the original dataset. The implications of these findings include improving the accuracy and performance of machine learning models in the diagnosis of skin diseases, as well as the potential use of these methods in other medical fields that face similar problems with imbalanced datasets.
Post-CMP Cleaning phenomenon is considered as the detachment of the nanoparticle from the substrate surface to be cleaned, and the occasional reattachment of the nanoparticle to surface in nanoscale. However, residual...
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Tropical disease is one of the infectious diseases that affect Indonesia. Many people die because of tropical diseases, such as dengue hemorrhagic fever (DHF), chikungunya, leprosy, lymphatic, and filariasis. The Indo...
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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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In this paper, we detect Gram positive cossi in Gram stained smear images as object detection. As detectors, we adopt Faster R-CNN, RetinaNet and YOLOv5. Then, we give experimental results for detecting Gram positive ...
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In this paper, we classify Gram positive cocci and Gram negative bacilli in Gram stained smear images. We adopt pre-trained models of VGG16, VGG19, MobileNet and DenseNet by using ImageNet as learning models. Then, we...
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Clustering is a typical unsupervised learning method for classifying unsupervised data. One of the clustering meth-ods, even-sized clustering based on optimization (ECBO), is a clustering algorithm that imposes a cons...
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ISBN:
(数字)9798350373332
ISBN:
(纸本)9798350373349
Clustering is a typical unsupervised learning method for classifying unsupervised data. One of the clustering meth-ods, even-sized clustering based on optimization (ECBO), is a clustering algorithm that imposes a constraint to equalize the size of each cluster. ECBO has been suggested to be effective in delivery and other problems. However, it is limited to Euclidean space. On the other hand, spectral clustering with a wide range of applicability for partitioning graph data has been proposed. In this paper, we propose even-sized spectral clustering, which imposes a size-equal constraint on spectral clustering, and show that it is an extension of the graph partitioning problem. We also verify the validity of the results through numerical examples.
The process of using ICT to provide services to the public is known as the Indonesian e-Government system, or Sistem Pemerintahan Berbasis Elektronik (SPBE). The e-Government initiative in Jakarta Provincial Health Of...
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ISBN:
(数字)9798350390025
ISBN:
(纸本)9798350390032
The process of using ICT to provide services to the public is known as the Indonesian e-Government system, or Sistem Pemerintahan Berbasis Elektronik (SPBE). The e-Government initiative in Jakarta Provincial Health Office involves enhancing collaboration among public health entities for efficient data exchange and streamlined processes, especially between the Provincial and District Health Offices, public hospitals, government clinics, and primary health care centers (Puskesmas). Achieving interoperability requires standardized protocols and a well-defined architectural model to integrate data seamlessly. This study presents a provincial-level architectural model focused on improving electronic health records interoperability, aiming to promote the adoption of the national Fast Healthcare Interoperability Resources (FHIR) health information exchange platform and enhance the integrity of health data in Jakarta. The study methodology involves conducting literature reviews, observations, and discussions with representatives from healthcare facilities to develop the e-Government architecture model and prototype of the infrastructure layer aiming to facilitate the interoperability of Electronic Health Records (EHRs) across 93 healthcare facilities, all of which are part of the SPBE users.
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