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GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Hongyang Du Dusit Niyato Chunyan Miao Jiawen Kang Dong In Kim Interdisciplinary Graduate Program School of Computer Science and Engineering the Energy Research Institute @ NTU Nanyang Technological University Singapore School of Computer Science and Engineering Nanyang Technological University Singapore School of of Automation Guangdong University of Technology China Department of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea

ISBN: (纸本)9781665435413

Recently, Metaverse has attracted increasing attention from both industry and academia, because of the significant potential to integrate real and digital worlds ever more seam-lessly. By combining advanced wireless communications, edge computing and virtual reality (VR) technologies into Metaverse, a multidimensional, intelligent and powerful wireless edge Meta-verse is created for future human society. In this paper, we design a privacy preserving targeted advertising strategy for the wireless edge Metaverse. Specifically, a Metaverse service provider (MSP) allocates bandwidth to the VR users so that the users can access Metaverse from edge access points. To protect users' privacy, the covert communication technique is used in the downlink. Then, the MSP can offer high-quality access services to earn more profits. Motivated by the concept of “covert”, targeted advertising is used to promote the sale of bandwidth and ensure that the advertising strategy cannot be detected by competitors who may make counter-offer and by attackers who want to disrupt the services. We derive the best advertising strategy in terms of budget input, with the help of the Vidale-Wolfe model and Hamiltonian function. Furthermore, we propose a novel metric named Meta-Immersion to represent the user's experience feelings. The performance evaluation shows that the MSP can boost its revenue with an optimal targeted advertising strategy, especially compared with that without the advertising.

关键词： Wireless communication Privacy Metaverse Bandwidth Virtual reality Downlink User experience

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Fingermath - Arithmetic Hand Gesture Game to Improve Early Childhood Mathematics Learning 4

Fingermath - Arithmetic Hand Gesture Game to Improve Early C...

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4th International Conference on Information Management and Technology, ICIMTech 2019

作者： Yuliana, Dewi Suharjito Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781728133331

Teaching mathematics has received priority in schools, because mathematics is the basis for development in understanding mathematics as a whole at school. computer technology used in teaching and learning can help improve children's preferences and abilities to learn mathematics in class, and can change attitudes of early childhood who are more critical, creative, and innovative. Jarimagic method is one method for learning to count on the fingers, where early childhood often communicate with fingers in learning mathematics in the classroom. For this reason, research attempts learning methods with interactive games with hand movements using the Jarimajic method and tools scratch 2.0. In this study, evaluation of data obtained through 20 child respondents was carried out by testing before using the game and after using the game, using Pre-Test and Post-Test analysis, which was divided into 2 results based on the preferences and abilities of early childhood learning mathematics in the classroom. From the study, the game development was carried out using the System Development Life Cycle (SDLC) method by taking the model of implementation the waterfall model. then a game is designed to overcome this problem. After the game is made, the game will be tested again for early childhood, with T-Test statistical analysis as the final data obtained from research that shows whether early childhood likes and increases ability to learn mathematics after the game is implemented. The results of this study are the realization of interactive game-based learning methods for early childhood in learning to count mathematics. especially in learning additions and collection using the jarimajic method so that children have the ability and preference in learning mathematics. © 2019 IEEE.

关键词： Learning systems

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Demonstration of a Polarization-Agnostic Geometric Phase in Nonlocal Metasurfaces

arXiv

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arXiv 2023年

作者： Overvig, Adam Kasahara, Yoshiaki Xu, Gengyu Alù, Andrea Photonics Initiative Advanced Science Research Center Graduate Center of the City University of New York United States Department of Electrical and Computer Engineering The University of Texas Austin United States Physics Program Graduate Center City University of New York United States

Symmetry-driven phenomena arising in nonlocal metasurfaces supporting quasi-bound states in the continuum (q-BICs) have been opening new avenues to tailor enhanced light-matter interactions via perturbative design principles. Geometric phase concepts—observed in many physical systems—are particularly useful in nonlocal metasurfaces, as they enable to locally pattern the q-BIC scattering rate and phase across the metasurface aperture without affecting the delocalized nature of the q-BIC resonance. However, this control typically comes with stringent limitations in terms of efficiency and/or of polarization operation. Here, we unveil a new form of geometric phase control, accumulated along a continuous contour of geometric perturbations that parametrically encircle a singularity associated with a bound state. This response is obtained regardless of the chosen polarization state, which can be rationally specified by a judicious choice of the perturbation geometry. Our findings extend geometric phase concepts to arbitrary polarizations, including linear and elliptical states, with near-unity scattering efficiency. This polarization-agnostic geometric phase offers new opportunities for wavefront manipulation, multifunctional operation and light emission, with applications in augmented reality, secure communications, wireless systems, imaging, lasing, nonlinear and quantum optics. © 2023, CC BY.

关键词： Polarization

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Geometric verification method of best score increasing subsequence for object instance recognition 6

Geometric verification method of best score increasing subse...

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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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Business Intelligent in an E-Commerce Industry 6

Business Intelligent in an E-Commerce Industry

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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： Purnamasari, A.M. Pah, C.E.A. Yoga, M.D.I. Girsang, A.S. Isa, S.M. Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Usantara University Jakarta11480 Indonesia

According to a survey from *** about in 2017, retail e-commerce sales worldwide amounted to 2.3 trillion US dollars and e-retail revenues are projected to grow to 4.88 trillion US dollars in 2021. Each year, e-commerce business increasingly popular. Some retail companies finally decided to focus on internet-based sales to get more customers. Along with transactions that continue to be carried out from year to year, transaction data continues to be stored and stacked and of course space consuming. So after years, Business Intelligence is finally appeared and offer great data processing. Without a business intelligence, these stacked big data are useless and wait to be removed because of poor knowledge. Business intelligence turns on the poor knowledge data into rich knowledge data visualization. This paper proposed a data warehouse that can be used to build a business intelligent with utilize information obtained from the history of transactions. To build up this business intelligent, authors uses methodology steps by Kimball which consists 4 steps of dimensional design process. Furthermore, data analysis will be presented in a dashboard using Power BI. © Published under licence by IOP Publishing Ltd.

关键词： Sales

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Extended-RSA for Encryption Process to Improve Application Server Availability 6

Extended-RSA for Encryption Process to Improve Application S...

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作者： Susanto, A. Herman Putranto, M.I. Utama, D.N. Wibowo, A. Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Every enterprise stores and operates its transactions confidentially, therefore it has to encrypt the transaction to protect it from data intruders. Technically, most encryption processes are ranging from hundreds of milliseconds. If there is a lot of encrypting process, then the performance will be getting bottleneck and the transaction's speed is being slowed down. In this paper, a promising scheme by adding GZIP compression on the former RSA encryption method to increase speed is proposed;thus every transaction is going to require less times, therefore the number of failed transactions or requests will be reduced. Hence, this way makes the transaction easier for customers to do. The result of little experimental test shows that using XOR to stream cipher-text to replace the absent of padding into specific bytes shows a lot of performance increase resulting other factors such as availability also affected without sacrificing the security level. © Published under licence by IOP Publishing Ltd.

关键词： Cryptography

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Deep learning performance in sentiment analysis 4

Deep learning performance in sentiment analysis

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4th International Conference on Electrical, Telecommunication and computer Engineering, ELTICOM 2020

作者： Manalu, Boy Utomo Tulus Efendi, Syahril Graduate Program of Computer Science Universitas Sumatera Utara Medan Indonesia Universitas Sumatera Utara Department of Mathematics Medan Indonesia Universitas Sumatera Utara Department of Computer Science Medan Indonesia

ISBN: (纸本)9781728188706

A problem of sentiment analysis is the text representation, that encodes text into a continuous vector by arranging projections from semantics to the points in high dimensional space. Deep learning methods have been widely used to solve various sentiment analysis problems. To improve the performance of deep learning in sentiment analysis requires a good method of text representation to be used as an embedding layer. In this study, we analyzed deep learning with the Recurrent Neural Network (RNN) method with Long Short-Term Memory (LSTM) variants in sentiment classification. We compare the performance of the LSTM network with Word2Vec to the network without Word2Vec as word embedding. Sentiment data used is derived from user-provided reviews of the applications in Google Play. The training process involves the Dropout layer and Early Stopping points to prevent overfitting. The results showed that the LSTM network using a word embedding Word2Vec is better than without Word2Vec. LSTM with Word2Vec 300 words dimension got a low error value of 0.3287 with an accuracy of 86.76%. While the LSTM testing results without Word2Vec get the lowest error of 0.3751 with an accuracy of 84.14%. © 2020 IEEE.

关键词： Long short-term memory

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Improved LSTM hyperparameters alongside sentiment walk-forward validation for time series prediction

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Journal of Open Innovation: Technology, Market, and Complexity 2025年第1期11卷

作者： Wahyuddin, Eko Putra Caraka, Rezzy Eko Kurniawan, Robert Caesarendra, Wahyu Gio, Prana Ugiana Pardamean, Bens Department of Statistical Computing Politeknik Statistika STIS Jakarta 13330 Indonesia Statistics Indonesia (BPS) Jl. Dr Sutomo 6-8 Jakarta Indonesia School of Economics and Business Telkom University Bandung 40257 Indonesia Research Center for Data and Information Sciences Research Organization for Electronics and Informatics National Research and Innovation Agency (BRIN) Bandung 40135 Indonesia Faculty of Integrated Technologies Universiti Brunei Darussalam Gadong BE1410 Brunei Darussalam Department of Mathematics Universitas Sumatera Utara Medan 20155 Indonesia Bioinformatics and Data Science Research Centre Bina Nusantara University DKI Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University DKI Jakarta 11480 Indonesia

This study aims to address the common issue of biased estimation errors in time series modeling by analyzing the error in locating ideal hyperparameters and defining appropriate validation methods. Specifically, it focuses on predicting the stock price of Bank Rakyat Indonesia using a combination of historical stock prices, technical indicators, exchange rates, and news sentiment data, while determining the optimal variables for deep learning models. Employing a deep learning-based Long-Short Term Memory (LSTM) model, the study optimizes hyperparameters alongside walk-forward validation for time series prediction. It explores different combinations of variables and adapts the sliding window approach to the context of the data. The results highlight the importance of optimizing hyperparameters and utilizing walk-forward validation for accurate time series prediction. The model incorporating historical stock prices and sentiment scores outperforms others, achieving an RMSE of 96.61 and MAE of 86.97. Incorporating sentiment scores reduces RMSE by 39.55 % compared to models using only historical stock prices, while adding technical indicators does not yield improvement. This study contributes to the field by addressing the issue of biased estimation errors in time series modeling, offering insights into the optimization of hyperparameters and validation methods for accurate predictions. It also underscores the significance of incorporating sentiment analysis alongside historical stock prices for improved forecasting accuracy. © 2024 The Authors

关键词： LSTM Sentiment analysis Stock price prediction Time series modeling Validation methods

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Reporting and Decision Support Using Data Warehouse for E-Commerce top-up Cell-phone Credit Transaction 7

Reporting and Decision Support Using Data Warehouse for E-Co...

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7th International Conference on Cyber and IT Service Management, CITSM 2019

作者： Vincentdo, Vito Pratama, Andhika Rizky Girsang, Abba Suganda Suwandi, Rizaldi Andrean, Yosefina Pricilia BINUS Graduate Program-Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781728129099

As e-commerce that covered all Indonesia, needs a fast reporting system to analyze the business to make the best decision. This paper provides methods to fasten the reporting process by making a data warehouse using Kimball and ross method. Data warehouse consists of 9 step methodology designed by Kimball and Ross. This paper devoted for business processes in e-commerce especially for online cellphone balance top-up transactions. Furthermore, data can be displayed in a form such as a dashboard, and also in a simple, informative and effective report. © 2019 IEEE.

关键词： Data warehouses

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CELL-E 2: translating proteins to pictures and back with a bidirectional text-to-image transformer 23

CELL-E 2: translating proteins to pictures and back with a b...

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Emaad Khwaja Yun S. Songt Aaron Agarunov Bo Huang UC Berkeley - UCSF Joint Bioengineering Graduate Program and Computer Science Division UC Berkeley CA Department of Statistics UC Berkeley CA and Computer Science Division UC Berkeley CA Department of Pathology Memorial Sloan Kettering Cancer Center Department of Pharmaceutical Chemistry UCSF San Francisco CA and Department of Biochemistry and Biophysics UCSF San Francisco CA and Chan Zuckerberg Biohub - San Francisco San Francisco CA

We present CELL-E 2, a novel bidirectional transformer that can generate images depicting protein subcellular localization from the amino acid sequences (and vice versa). Protein localization is a challenging problem that requires integrating sequence and image information, which most existing methods ignore. CELL-E 2 extends the work of CELL-E, not only capturing the spatial complexity of protein localization and produce probability estimates of localization atop a nucleus image, but also being able to generate sequences from images, enabling de novo protein design. We train and finetune CELL-E 2 on two large-scale datasets of human proteins. We also demonstrate how to use CELL-E 2 to create hundreds of novel nuclear localization signals (NLS). Results and interactive demos are featured at https://***/CELL-E_2/.

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