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2024 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2024

作者： De Jesus, Mervin Jommel T. Ballera, Melvin A. Graduate Program Technological Institute of the Philippines Manila Philippines Department of Computer Science Technological Institute of the Philippines Manila Philippines

ISBN: (纸本)9798331521219

Making decisions requires different information, especially when it is crucial. The traditional Analytic Hierarchy Process (AHP) is a great algorithm that will help make these decisions more quickly because it organizes the choices in a hierarchy. However, this algorithm has trouble with big datasets and changing decision settings because they depend on pairwise comparisons and subjective judgments when making decisions. Additionally, fuzzy and stochastic AHP algorithms were developed to improve the traditional ones. However, these algorithms are complex to use on a large scale and require many computers. This study presents a novel algorithm (Top-TC AHP) that integrates Support Vector Machine (SVM) and Top-K algorithms into the traditional AHP to help people make decisions faster and better. It uses SVM to sort data and get the probabilities of the criteria for the alternatives and Top-K to choose the top options. Time complexity, consistency ratio, and throughput were the metrics used to gauge the performance of the novel algorithm. As a result, when comparing Top-TC AHP to other ways, it gets better consistency, makes computing more manageable, and speeds things up. Because of this, it is beneficial for dealing with large amounts of data and situations that change quickly. In addition, the Top-TC AHP algorithm can help people make smart decisions in many areas, such as business and school planning. ©2024 IEEE.

关键词： Stochastic systems

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QoE Comparison between Multi-User OFDMA and Reliable Groupcast for Wireless LAN Audiovisual Transmission

QoE Comparison between Multi-User OFDMA and Reliable Groupca...

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2024 IEEE Region 10 Symposium, TENSYMP 2024

作者： Deguchi, Daiki Nunome, Toshiro Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350364866

This paper compares video and audio QoE of OFDMA multi-user transmission and reliable groupcast over wireless LAN. We assume video and audio transmission to several terminals simultaneously. As a reliable groupcast method, we employ Unsolicited Retry, a technique of IEEE 802.11aa GroupCast with Retries. We utilize IEEE 802.11ax for OFDMA transmission. We evaluate application-level QoS by computer simulation. We then assess QoE through a subjective experiment with video and audio streams generated by the output timing obtained from the simulation. We notice that each method has a situation to be applied appropriately. © 2024 IEEE.

关键词： Orthogonal frequency division multiplexing

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An innovative artificial intelligence-based visualization and rendering for e-commerce startup booth design 9th

An innovative artificial intelligence-based visualization an...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Kalleya, Calista Pramono, Andi Angelina, Chelsea Putri Cuarista, Wilbert Alvin Prabowo, Riefky Maulana, Fairuz Iqbal Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Indonesia Interior Design Department School of Design Bina Nusantara University Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Marketplace development is increasing, as is the number of people with active internet access. Unive is a startup that runs an e-commerce platform connecting Student Activity Units with consumers. Focuses on fostering student entrepreneurship through practical business experience. For its development, this startup needs an interior for business escalation. Designers need software integrated with artificial intelligence (AI) in interior design. This study explores the integration of AI-powered rendering tools in the design of e-commerce platforms, focusing on how these tools enhance the user experience and satisfaction. The research employs a mixed-method approach, combining qualitative and quantitative analyses. The author collected data through user surveys, expert interviews, and performance metrics of AI rendering tools. The author based the evaluation criteria on adherence to interior design principles and the quality of rendering results. Findings indicate that selecting furniture and supporting components that adhere to interior design principles results in optimal rendering outcomes. These outcomes are close to user expectations, significantly improving user engagement and satisfaction. Detailed analysis shows the effectiveness of AI rendering in various design scenarios. The discussion highlights the implications of integrating AI rendering tools in e-commerce platforms. It addresses the potential of these tools to revolutionize user interaction and provides insights into future developments and applications in the field. This study demonstrates the value of AI-powered rendering tools in enhancing e-commerce platform design. By adhering to interior design principles, these tools can achieve rendering results that meet user expectations, ultimately leading to improved user experiences. © 2024 The Authors.

关键词： Marketplaces

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MPEG-DASH Multi-View Video and Audio Transmission QoE Over HTTP/2 Stream

MPEG-DASH Multi-View Video and Audio Transmission QoE Over H...

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2024 International Conference on Advanced Technologies for Communications, ATC 2024

作者： Wakayama, Yamato Nunome, Toshiro Graduate School of Engineering Nagoya Institute of Technology Computer Science Program Department of Engineering Nagoya466-8555 Japan

ISBN: (纸本)9798350353983

In this paper, we consider multi-view video and audio streaming using MPEG-DASH, which enables to transmit video tailored to the network conditions over HTTP communication. This paper uses HTTP/2 instead of HTTP/1.1, which the authors previously used. HTTP/2 manages a series of request-response exchanges called a stream, which is assigned a unique stream ID. We perform a subjective experiment under various network conditions to evaluate application-level QoS and QoE. From the evaluation results, we investigate the effect of the HTTP/2 stream on the video and audio quality of the users in the multi-view video transmission scenario. © 2024 IEEE.

关键词： Audio streaming

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Implementation of Dynamic Image for Facial Expression Recognition on Indonesian Facial Expression Dataset

Implementation of Dynamic Image for Facial Expression Recogn...

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IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)

作者： Irene Anindaputri Iswanto Andry Chowanda Haryono Soeparno Widodo Budiharto Computer Science Department BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350389692

ISBN: (纸本)9798350389708

In recent times, there has been considerable attention directed towards Facial Expression Recognition (FER) due to its extensive utility across diverse domains. However, the universality of facial expressions has been challenged by studies suggesting that cultural backgrounds significantly influence the perception and recognition of emotions. This paper addresses the need for culturally specific datasets in FER tasks, particularly in underrepresented regions like Indonesia. The study introduces dynamic images as an alternative input representation for facial expression recognition tasks, aiming to assess their efficacy using the Indonesian Mixed Emotions Dataset (IMED). Through experimentation using EfficientNet model, the performance of dynamic images is compared with static image and video inputs. Results indicate that dynamic images exhibit promising performance, with an accuracy of 94.28%. These results outperform static image datasets and nearly match the performance of video-based models, which achieved an accuracy of 97.93 %, despite using fewer data. Nonetheless, challenges such as data imbalance and the quality of generated dynamic images persist, suggesting avenues for further research and model refinement. This study provides valuable insights into methodological advancements in FER, particularly in limited dataset conditions, laying the groundwork for future developments in dynamic image-based facial expression recognition algorithms.

关键词： Emotion recognition Image recognition Accuracy Face recognition Heuristic algorithms Data models Cultural differences Artificial intelligence

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A Bayesian-based approach for extracting the pion charge radius from electron-electron scattering data

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Chinese Physics C 2021年第8期45卷 12-27页

作者： Alam A Hidayat Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara UniversityJakarta 11480Indonesia Computer Science Department BINUS Graduate Program-Master of Computer ScienceBina Nusantara UniversityJakarta 11480Indonesia

In this study,we utilize a potentially versatile Bayesian parameter approach to compute the value of the pion charge radius and quantify its uncertainty from several experimental e^(+)e^(-) datasets for the pion vector form *** employ dispersion relations to model the pion vector form factor to extract the *** model selection is used to determine the order of polynomial appearing in the form factor formulation that can be supported by the data,adapting the computation of Bayes evidence and Bayesian effective complexity based on Occam's *** findings indicate that five out of six used datasets favor the nine-parameter model for radius extraction,and accordingly,we average the radii from the *** some inconsistencies with the most updated radius values,our approach may serve as a more intuitive method of addressing parameter estimations in dispersion theory.

关键词： Bayesian complexity dispersion hadron pion

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An IoT-Driven Fuzzy Decision Model for Determining Room Comfort

An IoT-Driven Fuzzy Decision Model for Determining Room Comf...

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Informatics International Conference (BTS-I2C), Beyond Technology Summit on

作者： Ditdit Nugeraha Utama John Reigton Hartono Johan Muliadi Kerta Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia Bina Nusantara University School of Computer Science Computer Science Bandung Indonesia

ISBN: (数字)9798331508579

ISBN: (纸本)9798331508586

The use of the Internet of Things (IoT) has been widely adopted for a lot of purposes. Business process automation is one type of implementation that has been carried out. In addition, the data successfully captured by the IoT ecosystem can be utilized for various computer modeling needs, including the decision model construction in assessing room quality. The decision model itself is a computer model supporting the decision maker in decision making process. This research, via four simple research stages, aims to develop an IoT-based decision model to evaluate room quality based on two parameters: temperature and humidity. The design of the IoT environment and the implementation of temperature and humidity data readings in a room are used as input data for a decision model to assess the comfort level of the room. In this study, the primary method used to design the model is object-oriented, while fuzzy logic is employed to build the model. The developed decision model can simulate data captured from the designed IoT ecosystem, successfully assessing the comfort level of a room. From the simulation results using 18 data points (from 9 days of data capturing) captured by temperature and humidity sensors, the average comfort level of the room was found to be 19.7873.

关键词： Temperature sensors Fuzzy logic Temperature distribution Object oriented modeling Computational modeling Simulation Ecosystems Humidity Data models Internet of Things

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Random Number Generator for Securing Data Exchange in Smart Factory: Recent Trends and Best Practices

Random Number Generator for Securing Data Exchange in Smart ...

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computer Technologies (ICCTech), International Conference on

作者： Andi Sama Meyliana Yaya Heryadi Taufik Roni Sahroni Computer Science Department Binus Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia Information System Department School of Information System Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta Jakarta Indonesia Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350395419

ISBN: (纸本)9798350395426

IT/OT convergence in the form of a Cyber-Physical System (CPS) presents an opportunity to apply recent Information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption.

关键词： Industries Systematics Market research Data transfer Control systems Generators Encryption

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Semi-automated meningioma segmentation with bounding boxes

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Procedia computer science 2024年 245卷 583-590页

作者： Nur Adhianti Heryanto Mahmud Isnan Matthew Martianus Henry Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Segmentation is manually performed by physicians, which takes considerable time and may be subject to observers. Automating this task can increase efficiency and consistency. Existing studies on meningioma segmentation used data from limited study centers, indicating the need for research on multi-center data to assess generalizability. In this work, two semi-automated methods with bounding box priors, LiteMedSAM and BBU-Net, are evaluated on the brain tumor segmentation (BraTS) 2023 meningioma dataset collected from five study-centers. Preprocessing included exclusion of small tumors, z-score normalization, and extraction of slices that contain tumors, generating 25,602 2D axial magnetic resonance imaging (MRI) scans. A fine-tuning strategy is adopted for LiteMedSAM while BBU-Net is trained from scratch. The models are evaluated using a five-fold cross-validation, with data split at the case level. Results show that while U-Net models can achieve performance close to LiteMedSAM, the foundation model has overall better performance, with more than 90% in all evaluation scores.

关键词： Bounding boxes Meningioma Semi-automated segmentation

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Offensive Language Detection Using Soft Voting Ensemble Model

Mendel

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Mendel 2023年第1期29卷 1-6页

作者： Fieri, Brillian Suhartono, Derwin Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Offensive language is one of the problems that have become increasingly severe along with the rise of the internet and social media usage. This language can be used to attack a person or specific groups. Automatic moderation, such as the usage of machine learning, can help detect and filter this particular language for someone who needs it. This study focuses on improving the performance of the soft voting classifier to detect offensive language by experimenting with the combinations of the soft voting estimators. The model was applied to a Twitter dataset that was augmented using several augmentation techniques. The features were extracted using Term Frequency-Inverse Document Frequency, sentiment analysis, and GloVe embedding. In this study, there were two types of soft voting models: machine learning-based, with the estimators of Random Forest, Decision Tree, Logistic Regression, Naïve Bayes, and AdaBoost as the best combination, and deep learning-based, with the best estimator combination of Convolutional Neural Network, Bidirectional Long Short-Term Memory, and Bidirectional Gated Recurrent Unit. The results of this study show that the soft voting classifier was better in performance compared to classic machine learning and deep learning models on both original and augmented datasets. © 2023, Brno University of Technology. All rights reserved.

关键词： Sentiment analysis

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