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IEEE International Conference on Software Architecture Workshops (ICSAW)

作者： Maurício Moreira Neto Carlos Sérgio da S.Marinho Emanuel F. Coutinho Leonardo O. Moreira Javam de C. Machado José Neuman de Souza Master and Doctorate in Computer Science (MDCC) Federal University of Ceará (UFC) Fortaleza Ceará Brazil Graduate Program in Computer Science (PCOMP) Federal University of Ceará (UFC) Quixadá Ceará Brazil Virtual University Institute (UFC VIRTUAL) Federal University of Ceará (UFC) Fortaleza Ceará Brazil

ISBN: (数字)9781728174150

ISBN: (纸本)9781728174167

E-health applications are health-related computing solutions that use the internet to provide services to users. One of the main challenges of E-health applications is the data privacy and security of patients. E-health application need should provide security and privacy mechanisms due to sensitive user data such as medical exams, DNA sequences, and others. Blockchain technology has become a research focus on several sectors that require their inherent characteristics, especially, about the security and privacy of data. This paper aims to present research opportunities with the use of Blockchain technology in applications that manipulate DNA sequence data. For this purpose, we propose an architecture for general E-health applications with Blockchain and implement a Proof of Concept (POC) to analyze the use of Blockchain technology in E-health applications using DNA sequence data. We also listed a set of research opportunities that permeate this topic.

关键词： DNA Genomics Bioinformatics Peer-to-peer computing Data privacy

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Clustering Analysis of a Spatiotemporal Dataset with a Novel Kernel Density Estimator

Clustering Analysis of a Spatiotemporal Dataset with a Novel...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jen-Chien Yu Chun-Chieh Yang John Reuben Gilbert Rou-Jun Liu Yen-Jen Oyang Meng-Han Yang Department of Computer Science and Information Engineering National Kaohsiung University of Science and Technology Kaohsiung City Taiwan ROC Master Program in Statistics National Taiwan University Taipei Taiwan ROC Department of Computer Science & Information Engineering National Taiwan University Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University

A vast number of spatiotemporal datasets collected from a wide range of sources has motivated scientists to develop effective approaches to identify interesting patterns hidden in these datasets. In this respect, kernel density estimators, which belong to a class of non-parametric estimators in statistics, have been widely exploited in recent years. With this background, we have developed a novel kernel density estimator aiming to provide accurate analysis results. According to the evaluation with a real spatiotemporal dataset, which collected emergency medical service records in a county in the United States, the proposed kernel density estimator can approximate the probability density function significantly more accurately than a conventional kernel density estimator. Furthermore, we have exploited the proposed kernel density estimator to identify interesting patterns hidden in the real spatiotemporal dataset.

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Improving Land Cover Segmentation Using Multispectral Dataset

Improving Land Cover Segmentation Using Multispectral Datase...

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International Conference on Informatics and Computing (ICIC)

作者： Herlawati Herlawati Rahmadya Trias Handayanto Yaya Heryadi Edi Abdurachman Haryono Soeparno Edy Irwansyah Eka Miranda Informatics Universitas Bhayangkara Jakarta Raya Jakarta Indonesia Computer Engineering Universitas Islam 45 Bekasi Indonesia Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Trisakti Institute of Transportation and Logistic Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia

computer vision has been used in many areas such as medical, transportation, military, geography, etc. The fast development of sensor devices inside camera and satellite provides not only red-greed-blue (RGB) images but also multispectral dataset with some channels including RGB, infrared, short-wave, and thermal wave. Most of the dataset is panchromatic (black and white) and RGB, for example Google Map and other satellite-based map applications. This study examines the effects of multispectral dataset for semantic segmentation of land cover. The comparison between RGB with band 2 to band 7 of Landsat 8 Satellite shows an improvement of accuracy from 90.283 to 94.473 for U-Net and from 91.76 to 95.183 for DeepLabV3+. In addition, this research also compares two well-known semantic segmentation methods, namely U-Net and DeepLabV3+, that shown that DeepLabV3+ outperformed U-Net regarding to speed and accuracy. Testing was conducted in the Karawang Regency area, West Java, Indonesia.

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Ramadhan short-term electric load: A hybrid model of cycle spinning wavelet and group method data handling (CSW-GMDH)

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2019年第4期46卷 670页

作者： Caraka, Rezzy Eko Chen, Rung Ching Toharudin, Toni Pardamean, Bens Bakar, Sakhinah Abu Yasin, Hasbi College of Informatics Chaoyang University of Technology Taichung City41349 Taiwan Department of Statistics Padjadjaran University Bandung Indonesia College of Informatics Chaoyang University of Technology Taichung City41349 Indonesia Bioinformatics Data Science Research Center Bina Nusantara University Indonesia BINUS Graduate Program-Master of Computer Science Bina Nusantara University. Indonesia School of Mathematical Sciences FST The National University of Malaysia Malaysia Department of Statistics Diponegoro University Semarang Indonesia

In general, performing a nonlinearity time series analysis in the modeling of data can reach a robust and increase the quality of the results. Wavelet methods have successfully been applied in a great variety of applications for modeling also forecasting. Wavelet Transform divided into two categories. There is continuous wavelet (CWT) and a discrete wavelet transform (DWT). Cycle spinning unlike the discrete wavelet transform (DWT), is highly redundant, non-orthogonal, also defined naturally for all sample sizes. There is a Group Method of Data Handling (GMDH) algorithm, which is a multivariate analysis method can be used in modeling and identifying uncertainty on linear also nonlinearity systems. In this paper, we aim to explain the combination of A-Trous wavelet transforms applied on cycle spinning and group method of data handling (GMDH) in data of short-term electric load holy month of Ramadhan from 2014 to 2015. © 2019, International Association of Engineers.

关键词： Discrete wavelet transforms

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Game Development with Scrum methodology

Game Development with Scrum methodology

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International Congress on Applied Information Technology

作者： Dedy Prasetya Kristiadi Ferry Sudarto Dian Sugiarto Richard Sambera Harco Leslie Hendric Spits Warnars Kiyota Hashimoto Raharja University Tangerang Indonesia Fakultas Sains dan Teknologi Universitas Raharja Tangerang Indonesia School of Computer Science Bina Nusantara University Jakarta Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Technology and Environment Prince Songkla University Phuket Campus Thailand

ISBN: (数字)9781728158624

ISBN: (纸本)9781728158631

Many methodologies are being used in software development, not only software can follow the process, but now games could follow the cycle of processes. Starting from the traditional waterfall model to agile methodology, many game developers are trying to produce the methodologies that could solve their problem in game development. In this paper, the type of methodologies will be shown on current game development. Also, this paper would suggest agile methodologies especially scrum over others in game development, and the reason behind that will be explained. Besides that, there are proposed game development methodologies that could solve the problem of game development by involving three phases, including the preproduction phase, production phase, and post-production phase. In the production phase, the sub-steps will have four sub-steps such as design, development, testing and review and the sub-steps will cycle as long as a result are unsatisfied.

关键词： Games Unified modeling language Production Testing Companies Software Scrum (Software development)

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Critical Factors of Immersive Learning in Higher Education: A Systematic Literature Review

Critical Factors of Immersive Learning in Higher Education: ...

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International Conference on ICT For Smart Society (ICISS)

作者： Sunardi Meyliana Arief Ramadhan Yusep Rosmansyah Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Information System Departement School of information system Bina Nusantara University Jakarta Indonesia School of Computing Telkom University Bandung Indonesia School of electrical engineering and informatics Bandung Institute of Technology Bandung Indonesia

Immersive learning has gained significant attention with the rising trend of spatial computing, particularly in the after-pandemic era. Numerous research has explored the potential of immersive learning in higher education, primarily on the educational sector. However, prior research has frequently focused too narrowly on the effects of technology and neglected to address the crucial element influencing successful immersive learning in higher education. This study seeks to pinpoint the crucial element contributing to the development of immersive learning experiences. The methodology uses a systematic literature review (SLR) from 2018 up to 2023 to investigate the critical factors of immersive Learning in Higher Education. From the 728 papers initially retrieved, 274 were considered potential candidates, and ultimately, 86 articles were selected based on their relevance to the research question. The results reveal that the critical factors include learning design, technology, immersion, engagement, interactivity, and usability. Academic interests will benefit from this SLR's consequences as institutions create models for designing suitable immersive learning, especially within the context of higher education.

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Weather Prediction in Agriculture Yields with Transformer Model

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Procedia computer science 2024年 245卷 750-758页

作者： Yulyani Arifin Ilvico Sonata Maryani Elizabeth Paskahlia Gunawan Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta 11480 Indonesia Information System Department School of Information System Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta 11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jl. K.H. Syahdan No.9 Kemanggisan Palmerah Jakarta 11480 Indonesia

Agriculture has a lot of relations with SDG from United Nations especially in end hungers and sustainable agriculture. One of factor important in agriculture is weather. Weather prediction is very important in agriculture. Weather greatly influences agricultural yields and the types of crops to be planted. Weather predictions, especially temperature and humidity, can be done using time series data analysis. Current developments in deep learning enable more accurate predictions of temperature and humidity based on time series dataset. Some deep learning models can be used to predict data based on training using time series data. The deep programming models used include Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM). The Transformer deep learning model, which was first introduced in 2017, is a sequence-to-sequence model which is very suitable for predicting time series data. This paper will explain temperature and humidity prediction using the Transformer deep learning model. Experimental results show that the Transformer model can predict temperature and humidity based on training results using a time series dataset. The accuracy obtained by the Transformer deep learning model is better compared to the LSTM deep learning model as indicated by lower MAE, MSE and RMSE values compared to the LSTM model.

关键词： Forecast LSTM SDG Goals Time series Transformer Weather

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Fuzzy eco-DSM for treating medical waste

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IOP Conference Series: Earth and Environmental science 2018年第1期195卷

作者： Ditdit Nugeraha Utama Eri Rustamaji Amelia Fauziyah Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Information System UIN Syarif Hidayatullah Jakarta Indonesia

Decision support model (DSM) is familiarly applied in a lot of areas and issues. The model is commonly benefited by decision maker to solve semi / unstructured problems. One of them should be used to treat medical waste by considering six selected parameters and three decision alternatives. In this study, environmental issue is main concerned aspect that the constructed model consequently becomes ecological DSM (eco-DSM). Three main methods are operated to construct the model; they are fuzzy logic, Euclidean distance, and full-factorial optimization methods. The model is analysed and designed via object oriented method. Lastly, the study shows simulation results based on empirical data of medical waste from one class 'A' state hospital in Jakarta, Indonesia.

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Fuzzy eco-DSM for road traffic engineering

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IOP Conference Series: Earth and Environmental science 2018年第1期195卷

作者： Ditdit Nugeraha Utama Sofie Nurlatifani Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Information System UIN Syarif Hidayatullah Jakarta Indonesia

Numerous efforts have been reasonably done to eliminate the road traffic congestion, however it occurs every working day, particularly in metropolitan. This study positively proposed a model which is not only able to show the effect of road traffic congestion ecologically, but also can recommend the strategy for road traffic engineering with methodically elaborating the environmental attributes as a dominant aspects considered. It is called as ecological decision support model (eco-DSM). To construct the model, two main methods were operated and combined: fuzzy logic and water flow algorithm (WFA). The method fuzzy logic exploited to exterminate the bias facet on parameters, and the WFA utilised to model the road traffic congestion and vehicle flow and to optimize its velocity based on emission calculation. The constructed model itself was designed thru the method object oriented, and the empirical road traffic congestion data of the Juanda Street in Tangerang Selatan city were functioned. Finally, the model showed the simulation result for suggesting the best decision alternative for road traffic engineering.

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Personnel System Development with Integrated Military Education Information System (MEIS) in Supporting the Personnel Position and Career

Personnel System Development with Integrated Military Educat...

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International Conference on ICT For Smart Society (ICISS)

作者： Leli Setyaningrum Suhono H. Supangkat Harco Leslie Hendric Spits Warnars Juneman Abraham Edi Abdurachman Bina Nusantara University Jakata Barat Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Humanities Bina Nusantara University BINUS Jakarta Indonesia

ISBN: (数字)9781665404228

ISBN: (纸本)9781665404235

Personnel and education data very important for organizations, including the military. All data related to military personnel will give effect positions and careers in the military field. The integration of personnel and education data can assist in processing and decision making. An analysis is needed so that the developed system can be useful for the long term. Analysis with IT balanced scorecard and COBIT ® 2019, will be able to help and fill the gaps in the existing system based on the objectives of the military organization itself. It is shown that the domains BAI05 (Managed Organizational Change) and DSS02 (Managed Service Requests and Incidents) are still not being implemented well. The system developed will have the features and capabilities to support the organization in achieving its goals, including in the field of staffing and education. Besides, it provides convenience in making decisions in terms of positions related to personnel careers.

关键词： Personnel Education Organizations Task analysis Information technology Engineering profession computer science

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