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IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)

作者： Ssu-Hsuan Wu Kai-Ting Wang Chia-Chen Chiang Hsin-Yu Chang Cheng-Yun Yeh Min-Chun Hu International Intercollegiate Ph.D.Program National Tsing Hua University Hsinchu Taiwan Master of Computer Science Program National Tsing Hua University Hsinchu Taiwan Interdisciplinary Program of Electrical Engineering and Computer Science National Tsing Hua University Hsinchu Taiwan Interdisciplinary Program of Technology and Art National Tsing Hua University Hsinchu Taiwan National Tsing Hua University Hsinchu Taiwan

This research aims to create a virtual reality-based practice system that simulates real-stage performance environments, assisting amateur dancers in overcoming stage fright and practicing group choreography that is difficult to achieve during individual practice. In this study, users can engage in performance simulations within the created system using the HTC VIVE virtual reality device. Within the system, we have developed a virtual stage space system that only requires a 2m x 3.5m physical area to simulate a large virtual stage experience. Users can also simulate choreographic positioning with virtual dance partners within this system, providing amateur dancers with group dance rehearsal practice opportunities that are not feasible during solo practice. Additionally, by creating three different audience modes, we aim to help users simulate various audience scenarios they may encounter during a performance. The system includes a recording feature that captures users' simulated performances, allowing them to review their actions and receive feedback after practice.

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Time-series Analysis of Correlation between Climatic Parameters and Dengue Fever in Indonesia

Time-series Analysis of Correlation between Climatic Paramet...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Rudi Nirwantono Joko Pebrianto Trinugroho Digdo Sudigyo Alam Ahmad Hidayat Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665473286

Dengue fever is mainly caused by female mosquitoes from the genus Aedes. It predominantly occurs in equatorial to sub-tropical regions. The weather factors play a significant role in the mosquito life cycle, so a study on the impact of climate parameters on dengue incidence is required. This study aimed to understand the statistical association between the annual fluctuation of dengue cases with climate factors in Indonesia. Climatic data, annual rainfall, and annual mean ambient temperature of Indonesia were obtained from *** from 2010 to 2020, while the data on the annual incidence of dengue fever in Indonesia were collected from the Indonesian Health Profile by the Ministry of Health of Indonesia from 2010 to 2020. The association between climatic factors with dengue cases was calculated with Spearman statistical test after the data was indicated as not normally distributed. In addition, we performed Poisson regression analysis to examine how the changes in climatic parameters affect the dengue cases. The rain precipitation was insignificantly correlated with the dengue incidence in Indonesia during the study time. In contrast, the ambient temperature statistically showed a strong association with the dengue cases. The association between climatic factors and the number of dengue cases suggests that the model would likely be prospectively applied to the dengue early warning system as a nationwide intervention to reduce the epidemic impact in Indonesia.

关键词： Epidemics Temperature distribution Rain Meteorological factors Multimedia systems Time series analysis Weather forecasting

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Enhancing Interoperability of Digital Twin in the Maintenance phase of Lifecycle

Enhancing Interoperability of Digital Twin in the Maintenanc...

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Dedy Ariansyah Bens Pardamean Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

In today's digitalization era, asset management has evolved following the rapid adoption of information systems and digital technologies. In the maintenance phase of the asset, Digital Twin (DT) emerges as an effective approach to improve failure recognition and structural damage prediction through DT-driven Prognostic and Health Monitoring (PHM). As a result, DT allows asset manager to proactively plan maintenance strategy to improve the availability of the assets. However, to reduce asset downtime in a cost-effective and time efficient manner, DT for maintenance phase needs to be integrated with other software systems that manage the provision of maintenance service and spare part such as computerized maintenance management system (CMMS) or Enterprise Resource Planning (ERP). Nevertheless, many of the developed DT in PHM were not equipped with semantic data model and hence, lacks interoperability with other systems (e.g., other DT or non-DT system) and limits the effective use of the DT. To qualify as an effective DT, it needs a semantical-enabled interface to connect with data and models from various domain to enable DT-driven decision-making. This paper leverages a rule-based ontology reasoning model to enhance DT interoperability with other maintenance software systems. The results depicts that the developed model paves a way for an effective use of DT-driven system in asset maintenance management.

关键词： Ontologies Software systems Data models Enterprise resource planning Digital twins Prognostics and health management Interoperability

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Disaster recovery plan implementation evaluation model at the corporation

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Procedia computer science 2024年 234卷 1658-1663页

作者： Wahyu Sardjono Widhilaga Gia Perdana Gustian Rama Putra Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Post Graduate Program of Management Science State University of Jakarta Jl. R.Mangun Muka Raya No.11 Jakarta Timur Jakarta 13220 Indonesia Computer Science Study Program Faculty of Mathematics & Natural Sciences Pakuan University Bogor Indonesia

The application of information technology in addition to making internal business processes more effective and efficient, is also to improve customer service. This role is important for companies to maintain the sustainability of information systems as a strategic tool for competitive advantage so system availability is absolutely essential. Research related to the Disaster Recovery Plan (DRP) needs to be carried out to see the readiness of a corporation to build a backup system in different places and locations. By using the method of factor analysis and regression analysis to form an evaluation model, it will obtain an overview of what factors must be considered and what the current conditions are. The results of the study show that there are Core Technical DRP, Organizational Preparation, and Costing factors which are the main variables in supporting DRP readiness. The conclusion from this study, through these three new factors a mathematical model can be built as a reference for improving DRP implementation in corporations.

关键词： disaster recovery planning factor analysis corporation evaluation model

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High-Performance and Resource-Efficient IoT-based Sleep Monitoring System 91

High-Performance and Resource-Efficient IoT-based Sleep Moni...

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91st IEEE Vehicular Technology Conference, VTC Spring 2020

作者： Surantha, Nico Utomo, Oei Kurniawan Isa, Sani Muhamad Binus Graduate Program-Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728152073

Recently, the number of people who have trouble sleeping is on the rise. It results in an increase in the number of car accidents, lower productivity and a higher risk of chronic disease. Advancing wearable and contactless health sensors offers the possibility of daily sleep quality monitoring that can be done on a regular basis by patients in their homes. The goal of this research is to propose the design of an Internet-of-Things (IoT) sleep quality monitoring system that can be integrated with a wearable or contactless sensor. The proposed platform architecture is based on micro-services and is event-driven. The simulation results show that the implementation of the IoT sleep quality monitoring system based on the proposed design decreases the response time by 55.85 per cent while increasing the throughput by 34.76 per cent compared to the traditional approach. On the other hand, the rate of increase in memory usage per instance replication for proposed method is lower than the traditional method. © 2020 IEEE.

关键词： Internet of things

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A Diversity Inventory Monitoring System of Riparian Vegetation 4

A Diversity Inventory Monitoring System of Riparian Vegetati...

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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Putra, Dian Pratama Nugraha, Nanda Satya Suparyanto, Teddy Hidayat, Alam Ahmad Sudigyo, Digdo Pardamean, Bens STIPER Agricultural Institute Faculty of Agricultural Technology Yogyakarta55282 Indonesia STIPER Agricultural Institute Yogyakarta Faculty of Agricultural Technology Faculty of Forestry Yogyakarta55282 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665453950

To strengthen conservation efforts for preserving biodiversity in a conservation area, forest inventory is important to understand the natural succession process in the area and to establish a monitoring strategy. Further, tree inventory aims to monitor the output yielded in the area. More specifically, the tree inventory in the watershed area plays a key role to achieve Sustainable Development Goals (SDG), especially in riparian zones which are also vital parts of green zones in forests. However, the traditional inventory approach is time-consuming and laborious therefore the development of an expert system to assist in inventory monitoring is required. In this study, we develop a monitoring system via a mobile application to collect, analyze and visualize tree inventory data. The application includes algorithms required to compute tree biodiversity, distribution, and richness for the given input of the data of all tree species in a conservation area. For the model validation stage, we compare the traditional inventory approach with our proposed application-based approach to compute diversity inventory in two riparian locations: Klaten Conservation Park and Wonosobo Conservation Park. After the three-day data collection in the areas, we obtain that the accuracy of reading data of our proposed system can achieve more than 90% in comparison with the manual approach. This demonstrates that the system can assist forestry workers to perform more efficient tree inventories in different locations. © 2022 IEEE.

关键词： Biodiversity

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Multilabel Machine Learning System for Predicting Gender and Age Group from Human Gait

Multilabel Machine Learning System for Predicting Gender and...

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Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), IEEE Conference on

作者： Nunung Nurul Qomariyah Ahmad Nurul Fajar Vincent Yono Dimitar Kazakov Computer Science Department School of Computing and Creative Arts Bina Nusantara University Jakarta Indonesia Information Systems Management Department Binus Graduate Program Master of Information System Management Bina Nusantara University Jakarta Indonesia Computer Science Department University of York United Kingdom

This paper explores the development of a multilabel machine learning system for predicting both gender and age from human gait patterns. Gait analysis, a non-intrusive method of identifying subtle nuances in human movement, has proven to be a rich source of information related to demographic characteristics. The research extends beyond traditional single-label classification approaches, adopting a multilabel framework to simultaneously predict gender and age *** study evaluates various multilabel machine learning algorithms, with the Random k-labeLsets (RAKEL) algorithm demonstrating superior performance in predicting gender and age labels from human gait datasets. The accuracy of the algorithm can reach up to 87%. We also compared the multilabel approach with several multiclass algorithms such as Decision Tree, Random Forest, Gradient Boosting, K-Neighbors and XGBoost. However, when we also considering the training time, Classifier Chain algorithm showed the best trade off with the accuracy of 86% and the training time is twice faster than the RAKEL algorithm.

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The Effectivity of Color For Chroma-Key Techniques

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Procedia computer science 2021年 179卷 281-288页

作者： Carolus Raditya Muhammad Rizky Sergio Mayranio Benfano Soewito Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

In this age where almost all facets of life are full of digital objects, because of technology is advancing more and more rapidly, included the fields of economy, the social field, the industrial field, labour, and the entertainment field especially the film industry. In film industry, the backgrounds that were once impossible such as foreign planets and the deep expanses of space are now possible, this is due to the technique known as Chroma Key as well as the usage of green screens and blue screens. In this research we wish to find out if only green screens and blue screens are the only viable colours to use or is there any other colours available to use to Chroma *** use or are other colours available to use to Chroma Key. The methods that we used to conduct research on this topic are case studies. We conduct a case study to see the level of efficiency and fatigue after using various colours as a background to the Chroma Key process. Experiments: We ourselves will try to conduct the Chroma Key process while using various colours as the background and making sure that other variables such as our lighting and spacing are constant on every case we conducted, to measure the efficiency and effectivity of the colours in the Chroma Key process.

关键词： colour chroma-key effectivity of colour background

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Implementation Graph Database Framework for Credit Card Fraud Detection

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Procedia computer science 2023年 227卷 326-335页

作者： Nurrahmi Mauliddiah Suharjito Computer Science Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Industrial Engineering Department BINUS Graduate Program – Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480

Credit card use is becoming more and more commonplace every day. Financial organizations and credit card customers lose a lot of money because of complicated illegal transactions. Fraudsters constantly stay on top of new technology to quickly perpetrate fraud against customer transaction patterns. We analyze credit card transaction networks and identify suspicious patterns, such as transactions connected to multiple accounts or unusual transaction patterns, transactions made at unusual times, and to monitor credit card transactions in real-time and quickly identify suspicious transactions. TigerGraph is used to analyze data, display results on a dashboard, and send notifications via email. One meth’\ Vc 1``13-od commonly used in anomaly detection is to compare data values against the standard deviation. In this research, we explain the use of TigerGraph as a platform for anomaly detection above the standard deviation, as well as the use of the Louvain algorithm in finding merchant communities used by fraudsters. The data used in this study comes from Sparkov simulation data obtained from Kaggle. Our results show that by using TigerGraph, we managed to achieve a very high accuracy rate of 99.77%, precision 82.84%, recall 72.38%, and f1-score 77,26% in predicting transaction fraud on Sparkov simulation data. This is much better than the results reported in a paper that uses the supervised machine learning method with the AdaBoost algorithm which achieves the highest accuracy of 77%.

关键词： Credit card fraud detection TigerGraph Dashboard Alert

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Adopting Centroid and Bandwidth to Shape Security Line

Adopting Centroid and Bandwidth to Shape Security Line

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International Conference of computer science and Information Technology

作者： Heni Ispur Pratiwi Iman Herwidiana Kartowisastro Benfano Soewito Widodo Budiharto Doctorate Program School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Doctorate Program of Computer Science Bina Nusantara University Jakarta Indonesia Computer Engineering Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia Computer Science BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798350399080

The voice patterns of gender and age have been used as speaker's identity and implied into sectors such as smart cards, healthcare, banking, and other security access controls. However, age, illness, and ambient noise factors exist challenging issues of voice changes in speech recognition systems to be resolved. This paper presents experiment results of observing those issues, and its goal was obtaining the elements of voice features to secure the speaker's identity. Mel-frequency Cepstral Coefficient (MFCC) was used to conduct observations on spectral centroid and bandwidth, it has effectively performed capturing features of individual speech signal. The experiment was conducted with data split into three groups: under 13, range 13 to 19, and above 19 years old for both male and female. The results showed that both gender under 13 have centroid voices reached to 98%, age of 13 to 19 remain with centroid reached 98% of bandwidth for male and passing over 100% for female, then above 19 for both genders speak lower with centroid 50% of bandwidth, and male above age of 19 remains to keep centroid about 50% and female changes to 95%. MFCC fits to expose the speech spectrum for the purpose of an analysis frame on specific local spectral properties of voices, and the finding is to form a security line or an individual profiling adoption.

关键词： computer science Smart cards Shape Bandwidth Speech recognition Medical services Banking

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