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6th International Conference on Information Technology, computer and Electrical Engineering, ICITACEE 2019

作者： Kusuma, Gede Putra Harjono, Kristopher David Dwi Putra, Muhammad Taufik Bina Nusantara University BINUS Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728126890

Weighted Longest Increasing Subsequence (WLIS) and its improvement, Best Increasing Subsequence (BIS) are two methods that has been proposed for pair verification in object instance recognition using local features. Tested on the Stanford Mobile Visual Dataset (SMVS), the BIS achieves better performance than WLIS on most categories, except for the 'video frames' category. In this paper we propose several modifications to BIS which resulted in a better overall performance compared to the WLIS and the basic BIS approaches. On average, the proposed Best Score Increasing Subsequence (BSIS) performs 4.53% better than the BIS and 9.43% better than the WLIS. © 2019 IEEE.

关键词： Object recognition

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Prediction Diabetes Mellitus Using Decision Tree Models

Prediction Diabetes Mellitus Using Decision Tree Models

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2019 International Congress on Applied Information Technology, AIT 2019

作者： Sunge, Aswan Supriyadi Warnar, Harco Leslie Hendric S. Heryadi, Yaya Abdurachman, Edi Soewito, Benfano Gaol, Ford Lumban BINUS Graduate Program-Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728158624

Health is an essential thing in human life, but Indonesian people are still far from the word healthy lifestyle. One disease that can be caused by an unhealthy lifestyle is diabetes mellitus that can cause many deaths. So far, there are many data in the hospital, but the data can not be maximized well even if it can be used to predict diabetes. The need for accuracy to produce better results. In conducting this test, the results obtained using C 4.5 only algorithm is 72.08%. © 2019 IEEE.

关键词： Data mining

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Scoring Urban Sustainability as a Guidance and Self-Learning for City Planners

Scoring Urban Sustainability as a Guidance and Self-Learning...

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2019 International Congress on Applied Information Technology, AIT 2019

作者： Herlawati, H. Heryadi, Yaya Trisetyarso, Agung Suparta, Wayan Kang, Chul Ho Abbas, Bahtiar Saleh BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728158624

City planners worldwide have tried to develop their cities following the concept of sustainable development. To allocate land use properly, the zoning method has been widely used, especially in densely populated cities, namely a kind of sustainable urban form with considers the mix of use/diversity of land use to minimize travel distance. This study proposes a method for calculating how much a city meets the sustainable urban forms based on compact city criteria, i.e. compatibility, dependency, and compactness. After the survey filling in compatibility and dependency scores for each land use, and compactness was calculated for each sub-district. Fuzzy C-Means clustering was used to cluster the result to classify other areas. In addition, this method can be used by planners to check whether their plans meet the concept of sustainable development or not. © 2019 IEEE.

关键词： Land use

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Bhandarkar, Vishakha D. Rongali, Aruna Sri Shamout, Mohamed Dawood Pund, Sachin Nama, Gigih Forda Patil, Shrishailappa Yeshwantrao Chavan College of Engineering Applied Mathematics and Humanities India University of the Cumberlands Graduate Doctoral Information Technology Information Technology Emphasis/Information Technology United States College of Business Administration University of Sharjah Department of Management Sharjah United Arab Emirates Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Doctoral Program of Environtmental Science University of Lampung Department of Informatics Bandar Lampung Indonesia Vishwakarma Institute of Technology Computer Engineering Pune India

ISBN: (纸本)9798350357769

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way.. © 2023 IEEE.

关键词： adjustments an a lytics automated preserves statistics

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Vision-based Semantic Communications for Metaverse Services: A Contest Theoretic Approach

Vision-based Semantic Communications for Metaverse Services:...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Guangyuan Liu Hongyang Du Dusit Niyato Jiawen Kang Zehui Xiong Boon Hee Soong Energy Research Institute@NTU Interdisciplinary Graduate Program School of Computer Science and Engineering Nanyang Technological University Singapore School of Computer Science and Engineering Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Department of Electrical and Electronic Engineering Nanyang Technological University Singapore

The popularity of Metaverse as an entertainment, social, and work platform has led to a great need for seamless avatar integration in the virtual world. In Metaverse, avatars must be updated and rendered to reflect users' behaviour. Achieving real-time synchronization between the virtual bilocation and the user is complex, placing high demands on the Metaverse Service Provider (MSP)'s rendering resource allocation scheme. To tackle this issue, we propose a semantic communication framework that leverages contest theory to model the interactions between users and MSPs and determine optimal resource allocation for each user. To reduce the consumption of network resources in wireless transmission, we use the semantic communication technique to reduce the amount of data to be transmitted. Under our simulation settings, the encoded semantic data only contains 51 bytes of skeleton coordinates instead of the image size of 8.243 megabytes. Moreover, we implement Deep Q-Network to optimize reward settings for maximum performance and efficient resource allocation. With the optimal reward setting, users are incentivized to select their respective suitable uploading frequency, reducing down-sampling loss due to rendering resource constraints by 66.076% compared with the traditional average distribution method. The framework provides a novel solution to resource allocation for avatar association in VR environments, ensuring a smooth and immersive experience for all users.

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Meteorological parameters for PV installations in Indonesia

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AIP Conference Proceedings 2024年第1期3026卷

作者： Joko Pebrianto Trinugroho Alam Ahmad Hidayat Reza Rahutomo Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Many countries are still dependent on fossil fuels as their primary energy supply. However, there is a growing concern about the sustainability and the environmental issue of fossil fuels. Therefore, it is important to utilize renewable resources as the energy supply, such as solar energy. As a country with a tropical climate, Indonesia has a great potential to use solar energy, due to the abundance of sunlight exposure. The present study aims to analyze several meteorological parameters for the installation of photovoltaic (PV) technology in Jakarta, Indonesia. The meteorological data provided by the Ministry of Environment and Forestry, Indonesia from 2008-2021 were used at three different locations in Jakarta. Data visualizations were used to show the difference between each variable in different locations. In addition, the statistical difference between the variables in the three locations was also examined using the Mann-Whitney U test. The test shows that all parameters are evenly distributed in the three locations except for a moderate difference in air temperature in the two locations. Furthermore, the monthly analysis of the parameters also indicates that the dry season, especially from August to September, would be the optimal time to utilize PV technology. Hence, this study would be useful to give preliminary insight regarding a site-specified assessment of PV plants in Jakarta based on local meteorological data.

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Six Sigma Based Performance Measurement of Tax Return Processing Improvement (Case Study: Directorate General of Taxes for Republic of Indonesia) 6

Six Sigma Based Performance Measurement of Tax Return Proces...

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Joint Conference of the 6th Annual Conference of Industrial and System Engineering 2019, ACISE 2019 and 1st International Conference on Risk Management as an Interdisciplinary Approach 2019, ICRMIA 2019

作者： Yuliyono, A.D. Baehaki Luqman, D. Utama, D.N. Wibowo, A. Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Directorate General of Taxes for Republic of Indonesia has an internal unit named data processing centre (DPC) that has main duty to process paper tax return delivered from tax office. DPC practically implemented new tax return processing system to replace the old system, however the performance of the new system was not on a par with the old one, at the beginning. Then, DPC made several improvements to increase new system's performance. This study aims to measure the improvements made by DPC by using Six Sigma approach. The approach is functioned to assess data processing performance through DMAIC concept: i.e. define, measure, analyse, improve, and control. With the DMAIC concept, improvement exposes better result, the average value of six sigma significantly escalated by 0.97 to 2.56. © Published under licence by IOP Publishing Ltd.

关键词： Six sigma

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Learning Universal and Robust 3D Molecular Representations with Graph Convolutional Networks

arXiv

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arXiv 2023年

作者： Zhang, Shuo Liu, Yang Xie, Li Xie, Lei Ph.D. Program in Computer Science The Graduate Center The City University of New York United States Department of Computer Science Hunter College The City University of New York United States Helen & Robert Appel Alzheimer’s Disease Research Institute Feil Family Brain & Mind Research Institute Weill Cornell Medicine Cornell University United States

To learn accurate representations of molecules, it is essential to consider both chemical and geometric features. To encode geometric information, many descriptors have been proposed in constrained circumstances for specific types of molecules and do not have the properties to be "robust": 1. Invariant to rotations and translations;2. Injective when embedding molecular structures. In this work, we propose a universal and robust Directional Node Pair (DNP) descriptor based on the graph-representations of 3D molecules. Our DNP descriptor is robust compared to previous ones and can be applied to multiple molecular types. To combine the DNP descriptor and chemical features in molecules, we construct the Robust Molecular Graph Convolutional Network (RoM-GCN) which is capable to take both node and edge features into consideration when generating molecule representations. We evaluate our model on protein and small molecule datasets. Our results validate the superiority of the DNP descriptor in incorporating 3D geometric information of molecules. RoM-GCN outperforms all compared baselines. Copyright © 2023, The Authors. All rights reserved.

关键词： Molecules

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Extrinsic LiDAR-Robot And LiDAR-Camera Calibration For Multi-sensor Fusion*

Extrinsic LiDAR-Robot And LiDAR-Camera Calibration For Multi...

引用

IEEE Latin American Robotics Symposium, LARS

作者： Gilmar Pereira Da Cruz Hector Azpúrua Fernando Lizarralde Gustavo Medeiros Freitas Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627 Belo Horizonte MG Brazil Department of Computer Science Universidade Federal de Minas Gerais MG Brasil Electrical Engineering Program - COPPE Universidade Federal do Rio de Janeiro RJ Brasil

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

In mobile robotics, an essential requirement for the fusion of different sensors is that measurements are expressed with respect to the same reference. In this sense, the transformation between sensors and robot is necessary to ensure better sensor fusion. Therefore, this article proposes an extrinsic sensor calibration based on markers and associated to three orthogonal planes. This technique is applied to two calibration approaches, LiDAR-Robot and LiDAR-Camera. The first one calculates the transformation between a 3D LiDAR sensor and a robot, and the second system calculates the transformation between a 3D LiDAR and an embedded RGB camera. To demonstrate the efficiency of our method, we performed simulations on the CoppeliaSim simulator and experiments in the laboratory. Then, the results show that it is possible to calibrate the sensors with the methodologies.

关键词： Visualization Laser radar Three-dimensional displays Robot vision systems Sensor fusion Cameras Sensor systems Sensors Calibration Registers

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Protein Language Model-Powered 3D Ligand Binding Site Prediction from Protein Sequence

arXiv

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arXiv 2023年

作者： Zhang, Shuo Xie, Lei Department of Computer Science Hunter College City University of New York United States Ph.D. Program in Computer Science Graduate Center City University of New York United States Helen & Robert Appel Alzheimer’s Disease Research Institute Feil Family Brain & Mind Research Institute Weill Cornell Medicine Cornell University United States

Prediction of ligand binding sites of proteins is a fundamental and important task for understanding the function of proteins and screening potential drugs. Most existing methods require experimentally determined protein holo-structures as input. However, such structures can be unavailable on novel or less-studied proteins. To tackle this limitation, we propose LaMPSite, which only takes protein sequences and ligand molecular graphs as input for ligand binding site predictions. The protein sequences are used to retrieve residue-level embeddings and contact maps from the pre-trained ESM-2 protein language model. The ligand molecular graphs are fed into a graph neural network to compute atom-level embeddings. Then we compute and update the protein-ligand interaction embedding based on the protein residue-level embeddings and ligand atom-level embeddings, and the geometric constraints in the inferred protein contact map and ligand distance map. A final pooling on protein-ligand interaction embedding would indicate which residues belong to the binding sites. Without any 3D coordinate information of proteins, our proposed model achieves competitive performance compared to baseline methods that require 3D protein structures when predicting binding sites. Given that less than 50% of proteins have reliable structure information in the current stage, LaMPSite will provide new opportunities for drug discovery. Copyright © 2023, The Authors. All rights reserved.

关键词： Proteins

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