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All Journal Sinergi Jurnal Ekonomi dan Studi Pembangunan (JESP)
Wing-Keung Wong
Asia University
Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Optimized Swarm Enabled Deep Learning Technique for Bone Tumor Detection using Histopathological Image Dama Anand; Osamah Ibrahim Khalaf; Fahima Hajjej; Wing-Keung Wong; Shin-Hung Pan; Gogineni Rajesh Chandra
SINERGI Vol 27, No 3 (2023)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/sinergi.2023.3.016

Abstract

Cancer subjugates a community that lacks proper care. It remains apparent that research studies enhance novel benchmarks in developing a computer-assisted tool for prognosis in radiology yet an indication of illness detection should be recognized by the pathologist. In bone cancer (BC), Identification of malignancy out of the BC’s histopathological image (HI) remains difficult because of the intricate structure of the bone tissue (BTe) specimen. This study proffers a new approach to diagnosing BC by feature extraction alongside classification employing deep learning frameworks. In this, the input is processed and segmented by Tsallis Entropy for noise elimination, image rescaling, and smoothening. The features are excerpted employing Efficient Net-based Convolutional Neural Network (CNN) Feature Extraction. ROI extraction will be employed to enhance the precise detection of atypical portions surrounding the affected area. Next, for classifying the accurate spotting and for grading the BTe as typical and a typical employing augmented XGBoost alongside Whale optimization (WOA). HIs gathering out of prevailing scales patients is acquired alongside texture characteristics of such images remaining employed for training and testing the Neural Network (NN). These classification outcomes exhibit that NN possesses a hit ratio of 99.48 percent while this occurs in BT classification.
The Role of Inequality in Indonesia: Does Fiscal Decentralization Matter? Nunung Zahrotul Hayat; Mahrus Lutfi Adi Kurniawan; Wing-Keung Wong
Jurnal Ekonomi dan Studi Pembangunan Vol 15, No 2 (2023)
Publisher : Universitas Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17977/um002v15i22023p111

Abstract

This research explores the role of inequality because inequality has long-term effects on social and economic conditions and has an impact on the decentralization process. There are two models developed in which inequality is the regressor of regional income and inequality is the regressor. The panel seemingly unrelated regression is applied to produce consistent coefficient parameters. The results of research on model 1 show that inequality has a negative effect on regional income and on model 2 shows that fiscal decentralization with government spending has a positive effect on inequality and special allocation funds have a negative effect on inequality. The implication of research is that fiscal decentralization can reduce the level of inequality if it is transferred and prioritizes poor or disadvantaged areas.
Co-Authors Dama Anand Fahima Hajjej Gogineni Rajesh Chandra Mahrus Lutfi Adi Kurniawan Nunung Zahrotul Hayat Osamah Ibrahim Khalaf Shin-Hung Pan