scholarly journals Image segmentation for vegetation types extraction using WorldView-2: a case study in parts of Dieng Plateau, Central Java

2019 ◽  
Author(s):  
Siti Martha Uly Sinaga ◽  
Muhammad Kamal
Keyword(s):  
Image Segmentation ◽  
Vegetation Types ◽  
Central Java ◽  
Plateau Central

THE CHANGING OF SANTRI’s PREFERENCE TOWARDS STUDIES AND PROFESSIONS: A Case Study at Pondok Pesantren Alhikmah 2 Brebes, Central Java

Al-Qalam ◽  
2017 ◽  
Vol 23 (2) ◽  
Author(s):  
Hayyadin Ode
Keyword(s):  
Subject Matter ◽  
Central Java ◽  
Religious Subject

<p>This research aimed to figure out the santri’s preference toward studies and professions in which conduct study at pesantren. Common perceived and stated also at Government Ordinancenumber 55, 2007, that pesantren purposes was to reproduce Islamic scholar (ulama). However, through this study, it proved that not all santri wanted to be ulama, most of them wanted to be a scientist. This study was a case study, conducted in 2015 at Pesantren Alhikmah2 Brebes. Data collected using questionnaire, interview, and document. Those all derived from santris, Kyais, and teachers (asatidz). The research concluded as showed from questionnaire that santri’s  preferences toward study has gotten  changing to general subject matters instead of religious subject matters; and the santri’s professions and jobspreference has gotten changing to the jobs and professions that based on general subject matter, instead of choose to be ulama (Islamic scholar) most of santri wanted to be scientists, or researchers, or doctors as well as athlete.</p>

scholarly journals Boundary Loss-Based 2.5D Fully Convolutional Neural Networks Approach for Segmentation: A Case Study of the Liver and Tumor on Computed Tomography

Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 144
Author(s):  
Yuexing Han ◽  
Xiaolong Li ◽  
Bing Wang ◽  
Lu Wang
Keyword(s):  
Image Segmentation ◽  
Spatial Information ◽  
Medical Images ◽  
Tumor Segmentation ◽  
Convolutional Networks ◽  
Learning Framework ◽  
Fully Convolutional Networks ◽  
Segmentation Accuracy ◽  
Boundary Information

Image segmentation plays an important role in the field of image processing, helping to understand images and recognize objects. However, most existing methods are often unable to effectively explore the spatial information in 3D image segmentation, and they neglect the information from the contours and boundaries of the observed objects. In addition, shape boundaries can help to locate the positions of the observed objects, but most of the existing loss functions neglect the information from the boundaries. To overcome these shortcomings, this paper presents a new cascaded 2.5D fully convolutional networks (FCNs) learning framework to segment 3D medical images. A new boundary loss that incorporates distance, area, and boundary information is also proposed for the cascaded FCNs to learning more boundary and contour features from the 3D medical images. Moreover, an effective post-processing method is developed to further improve the segmentation accuracy. We verified the proposed method on LITS and 3DIRCADb datasets that include the liver and tumors. The experimental results show that the performance of the proposed method is better than existing methods with a Dice Per Case score of 74.5% for tumor segmentation, indicating the effectiveness of the proposed method.

scholarly journals Female Candidates, Islamic Women’s Organisations, and Clientelism in the 2019 Indonesian Elections

2021 ◽  
Vol 40 (1) ◽  
pp. 73-92
Author(s):  
Muhammad Mahsun ◽  
Misbah Zulfa Elizabeth ◽  
Solkhah Mufrikhah
Keyword(s):  
Structural Barriers ◽  
Women Candidates ◽  
Electoral Success ◽  
Female Candidates ◽  
Central Java ◽  
Grassroots Support ◽  
Nahdlatul Ulama ◽  
And Gender ◽  
Women's Networks

This article analyses the factors leading to the success of women candidates in the 2019 elections in Central Java. Recent scholarship on women’s representation in Indonesia has highlighted the role that dynastic ties and relationships with local political elites play in getting women elected in an environment increasingly dominated by money politics and clientelism. Our case study of women candidates in Central Java belonging to the elite of the Nahdlatul Ulama (NU)-affiliated women’s religious organisations Muslimat and Fatayat shows that strong women candidates with grassroots support can nonetheless win office. Using the concepts of social capital and gender issue ownership, and clientelism, we argue that women candidates can gain a strategic advantage when they “run as women.” By harnessing women’s networks and focusing on gender issues to target women voters, they are able to overcome cultural, institutional, and structural barriers to achieve electoral success even though they lack resources and political connections.

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