A UNIFIED ENERGY APPROACH FOR B-SPLINE SNAKE IN MEDICAL IMAGE SEGMENTATION

 The parametric snake is one of the preferred approaches in feature extraction from images because of their simplicity and efficiency. However the method has also limitations. In this paper an explicit snake that represented using BSpline applied for image segmentation is considered. In this paper, we identify some of these problems and propose efficient solutions to get around them. The proposed method is inspired by classical snake from Kass with some adaption for parametric curve. The paper also proposes new definitions of energy terms in the model to bring the snake performance more robust and efficient for image segmentation. This energy term unify the edge based and region based energy derived from the image data. The main objective of developed work is to develop an automatic method to segment the anatomical organs from medical images which is very hard and tedious to be performed manually. After this segmentation, the anatomical object can be further measured and analyzed to diagnose the anomaly in that organ. The results have shown that the proposed method has been proven qualitatively successful in segmenting different types of medical images.

DEVELOPMENT OF MOBILE DEVICE FOR GAMMA RADIATION MEASUREMENT UTILIZING LORA AS THE COMMUNICATION MEANS

Public protection is one of important issues when operating nuclear facility. In case of accident occurs, the facility owner and related organizations shall make decision whether to evacuate people or not, based on the level of the accident and radiation dose rate released to the environment. In this study, as part of the decision support system for nuclear emergency response, a prototype of mobile radiation measurement system has been developed. The device consists of Geiger-Muller (GM)-based radiation measurement board, Global Positioning System (GPS) module, microcontroller board, and low power LoRa module for communication. Radiation dose rate along with its geoposition were recorded and sent to base station equipped with LoRa gateway for connecting LoRa network to TCP/IP-based network. The measurement data is then published to storage server using Message Queuing Telemetry Transport (MQTT) protocol. Power consumption, measurement of counter/timer accuracy, communication ranges testing, and radiation dose rate measurement were performed around Puspiptek area to demonstrate the functionality of the system.Keywords: Radiation monitoring, Decision Support System, Mobile, LoRa, GP

Deep Learning Approaches with Optimum Alpha for Energy Usage Forecasting

Energy use is an essential aspect of many human activities, from individual to industrial scale. However, increasing global energy demand and the challenges posed by environmental change make understanding energy use patterns crucial. Accurate predictions of future energy consumption can greatly influence decision-making, supply-demand stability and energy efficiency. Energy use data often exhibits time-series patterns, which creates complexity in forecasting. To address this complexity, this research utilizes Deep Learning (DL), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Long Short-term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Gated Recurrent Unit (GRU) models. The main objective is to improve the accuracy of energy usage forecasting by optimizing the alpha value in exponential smoothing, thereby improving forecasting accuracy. The results showed that all DL methods experienced improved accuracy when using optimum alpha. LSTM has the most optimal MAPE, RMSE, and R2 values compared to other methods. This research promotes energy management, decision-making, and efficiency by providing an innovative framework for accurate forecasting of energy use, thus contributing to a sustainable and efficient energy system

Peningkatan Keterampilan ICT untuk Guru melalui Pelatihan Konten Digital Pembelajaran Berbasis Sumber Terbuka (Open Sources)

ABSTRAK Pemanfaatan dan pengembangan konten digital adalah persyaratan yang harus terpenuhi untuk menjadi guru profesional Abad 21. Hal ini yang kemudian membuat adanya kebutuhan mendesak dikalangan guru yang sudah lama berkecimpung dalam profesi pendidikan. Berdasarkan survey yang dilakukan melalui kuesioner online (Google Form), responden (n=83) dari beberapa sekolah dan beberapa mata pelajaran mengayatakan bahwa kebutuhan keterampilan pembuatan konten digital pembelajaran merupakan prioritas utama (n=42) dan diikuti kebutuhan pembuatan online classroom and mobile learning (n=38). Artikel ini bertujuan untuk menyampaikan identifikasi masalah, analisa kurikulum, implementasi solusi, dan evaluasi hasi dari kegiatan pengabdian pada masyarakat dalam bentuk pelatihan pengembangan konten digital pembelajaran untuk guru di Kota Tangerang. Kata Kunci: konten digital; pembelajaran informatika; sumber terbuka.ABSTRACT Digital content development and utilization are considered as high requirements that must be mastered by qualified teachers in this 21st century learning. The needs eventually create gaps between prior teachers’ competencies and the requirements for further qualifications. An online survey delivered through Google form was conducted to validate this hypothesis. The survey found that respondents (n=83) who were school teachers from different learning subjects expressed that they demanded new skills on digital content development and utilization. It was considered as the highest priority (n=42) among any others skills related technology enhanced learning, such as online classroom or mobile learning (n=38). This article is aimed to describe the process of problem identification, curriculum analysis, the implementation of solution, and program evaluation of a community service activities entitled ‘Training of Digital Content Development for School Teachers’. Keywords: computer science education; digital content; open sources.

Geographic Information System for Higher Education via Data Scrapping

This paper aims to build a database that can be used as the most important part of a geographic information system by using data from reliable sources. Data collection is done through process scrapping on some official website of Indonesia government. In addition to collecting quantitative data of higher education, this paper also mapping geographically from the high level of existing in Indonesia. It is expected that this data will be able to help the community and government in observing and analyzing the quantity and distribution of universities. The result of this research is one database that is ready to be integrated in more complex geographic information system. In addition, the scrapping method used allows us to perform the upgrade of data that has been obtained previously

Intégration de données ultrasonores per-opératoires dans le geste de chirurgie orthopédique assisté par ordinateur

This work addresses the problem of the integration of ultrasound imaging for intraoperative data acquisition in computer assisted orthopaedic surgery, in particular for hip surgery applications. The point is to improve the quality of the surgery using a minimally invasive, real time, and highly available imaging device. The method we propose uses a featurebased registration between ultrasound images and a pre-operative CT scan volume. We present an ultrasound image segmentation method based on a deformable model with the integration of a regional energy term to detect the local characteristics of ultrasound images. The feature-based registration is a variant of the ICP algorithm that uses a pre-calculated distance map with a Lavenberg-Marquardt optimization. We also propose a protocol for the pre- and intra-operative data acquisition. The real operating room constraint are taken into account for the design of this protocol while trying to provide the necessary ergonomy for the surgeon. A large validation has been conducted on phantoms and a cadaver and is presented in this thesis. From this validation we assess the performances of the data acquisition protocol, as well as the precision of the segmentation and the robustness and precision of the registration. Performances are measured quantitatively and qualitatively. Finally we propose some possible improvements to the segmentation and registration.AIX-MARSEILLE2-BU Sci.Luminy (130552106) / SudocSudocFranceF

PENGARUH FUNDAMENTAL PERUSAHAAN DAN REAKSI PASAR MODAL SELAMA TERJADINYA PANDEMI COVID-19 TERHADAP RETURN SAHAM (Studi Empiris 35 Perusahaan Marketkapital Terbesar Indeks Saham Syariah Indonesia Periode 2019–2022)

This study aims to analyze the influence of company fundamentals and capital market reactions during the Covid-19 pandemic on the stock returns of companies with the largest market capitalization included in the Indonesia Sharia stock index for the 2019-2022 period. This study is quantitative research with a purposive sampling technique and a total sample of 35 companies that meet the criteria. This study uses secondary data, namely data from financial reports for the period 2019 to 2022 obtained from the official website of the Indonesia Stock Exchange. The test results using multiple linear regression analysis show that return on equity has a significant effect on stock returns, price to book value has a significant effect on stock returns, earnings per share has no significant effect on stock returns, and there is no significant difference from the abnormal return before and after the announcement of covid-19. This study aims to analyze the influence of company fundamentals and capital market reactions during the Covid-19 pandemic on the stock returns of companies with the largest market capitalization included in the Indonesia Sharia stock index for the 2019-2022 period. This study is quantitative research with a purposive sampling technique and a total sample of 35 companies that meet the criteria. This study uses secondary data, namely data from financial reports for the period 2019 to 2022 obtained from the official website of the Indonesia Stock Exchange. The test results using multiple linear regression analysis show that return on equity has a significant effect on stock returns, price to book value has a significant effect on stock returns, earnings per share has no significant effect on stock returns, and there is no significant difference from the abnormal return before and after the announcement of covid-19