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21st International Symposium on Communications and Information Technologies, ISCIT 2022

作者： Ogita, Tadahiro Morimoto, Tomoyuki Onogi, Shunsuke Kawamata, Ryota Wang, Ziming Tsutsumi, Toshiyuki Graduate School of Science and Technology Meiji University Computer Science Program Kanagawa Japan School of Science and Technology Meiji University Department of Computer Science Kanagawa Japan

ISBN: (数字)9781665498517

ISBN: (纸本)9781665498517

We have been developing MEIMAT, meiji micro-processor (MPU) architecture design tools. Our MEIMAT has a feature to implement arbitrary instructions. However, the MEIMAT does not have a function to simulate those instructions. Therefore, we have newly developed a function of simulation to dynamically execute the designed instructions. The result of this dynamic simulation can be measured by the developed module viewers. It is also demonstrated that a higher performance MPU can be designed by our improved MEIMAT. © 2022 IEEE.

关键词： Memory architecture

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Fuzzy Decision Support Model on Virtual Plant Computational Model of Water Spinach (Ipomoea aquatica. Forssk) in Farming Business 6

Fuzzy Decision Support Model on Virtual Plant Computational ...

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6th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2022

作者： Utama, Ditdit Nugeraha Agustia Rachmawati, Ika Diah Purwantono, Heraldo Yusron Bina Nusantara University Binus Graduate Program - Master of Computer Science Computer Science Department Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9798350399615

Using soil as a planting medium (conventional system) raises several problems, such as the need for large agricultural land, but the available land is limited. This problem is triggered by an increase in demand for nutrients needed by the body to support daily activities, one of which can be met by consuming green vegetables, such as Water Spinach. To solve this problem, a hydroponic wick system or a wick system can use that is simple and easy to care for. Water Spinach (Ipomoea aquatica. Forssk) vegetables are easy to grow and care for. Nutrients contained in 100 grams of Water Spinach, energy: 29 kcal, protein: 3 grams, Fat: 0.3 grams, carbohydrates: 5.4 grams, calcium: 73 mg, phosphorus: 50 mg, iron: 3 mg, vitamin A: 6300IU,vitamin B1: 0.07 mg, vitamin C: 32 mg. In addition, a combination of disciplines such as mathematics, computer science, plant science, biology, and statistics can be used. This combination of knowledge is known as Plant Computational Modeling (PCM), which uses the Growth Grammar Interactive Modeling Platform (GroIMP) with the Functional Structural Plant Modeling (FSPM) method. The virtual plant model was successfully built, the results were divided into two parts, such as single plant and multi-plant. Plant computational modeling and DSM can help deal with agricultural problems. By using a plant dataset, the GroIMP-FSPM platform, and fuzzy logic, the model could help researchers in making a better decision based on BEP evaluation. The minimum numbers of plants cultivated were 650 plants in one harvest period in order to gain a desirable profit. We recommend to cultivate even more plants in one harvest period to gain even higher profits. © 2022 IEEE.

关键词： Decision Support Model Functional Structural Plant Modelling Fuzzy Logic Growth-Grammar Interactive Modelling Platform Ipomoea aquatica Forssk Plant Computational Modelling

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Learning the Jawa Culture by using Android Smartphone 2

Learning the Jawa Culture by using Android Smartphone

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Antonio, Andrew Kezyanto, Julio Warnars, Harco Leslie Hendric Spits Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665400527

Javanese culture is a culture that the Javanese own, and the Javanese have started to exist with their culture since before the era of the Majapahit kingdom, and the Javanese are famous for their ability to sail the oceans. In addition, the many temples built, which are currently historical sites, prove that the Javanese are a large ethnic group that inhabits the island of Java. Other Javanese cultures include Javanese handicrafts such as kris, Javanese dance, Javanese batik art, Javanese wayang art, Javanese carving art, Javanese songs, and Javanese writings. All these cultures are part of the wealth of the unitary state of the Republic of Indonesia that must be preserved and passed down from one generation to another, and current technological developments tend to make the current generation less aware of preserving the culture of their ancestors. Therefore, we use technology to create an application for learning Javanese culture by applying game elements as entertainment elements. The business process of this application is modeled using use case diagrams and class diagrams to describe the database relationships. This mobile application is built using android studio and uses a MySQL database. © 2022 IEEE.

关键词： Android (operating system)

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A Systematic Literature Review of Deep Learning Application in Multiclass Anomaly Detection for Chest Medical Imaging 6

A Systematic Literature Review of Deep Learning Application ...

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6th International Conference on computer and Informatics Engineering, IC2IE 2023

作者： Philips Pardamean, Bens Elwirehardja, Gregorius Natanael Isnan, Mahmud Bina Nusantara University Binus Graduate Program - Master of Compuer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta Indonesia

ISBN: (纸本)9798350345162

Medical imaging abnormality detection is challenging, but deep learning approaches have shown promise. This paper reviews the current state of the art in deep learning approaches for detecting abnormalities in chest medical imaging. To discover the trends, opportunities, and challenges associated with this field, 18 studies were selected from Google Scholar based on their titles, abstracts, and contents for extensive review to answer two research questions. The study found that the National Institutes of Health (NIH) Chest X-ray 14 dataset is the most used dataset for this task. Most research uses a single-modal approach, considering only image data as input, with X-ray being the more popular instrument. There are 8 out of 18 studies leverage the transfer learning approach, with ResN et50 being the most popular network. MobileNetV2 has demonstrated competitive results compared to more robust networks. Preprocessing techniques such as image enhancement and data augmentation are leveraged by 61.1 % of the reviewed studies and are shown to improve model performance. © 2023 IEEE.

关键词： abnormality detection attention mechanisms chest x-ray CT images deep learning transfer learning

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Visualization Tool of Microprocessor Instruction for Designing New Architecture with Meta-Instructions 21

Visualization Tool of Microprocessor Instruction for Designi...

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21st International Symposium on Communications and Information Technologies, ISCIT 2022

作者： Morimoto, Tomoyuki Onogi, Shunsuke Ogita, Tadahiro Kawamata, Ryota Wang, Ziming Tsutsumi, Toshiyuki Department of Computer Science School of Science and Technology Meiji University Kanagawa Japan Computer Science Program Graduate School of Science and Technology Meiji University Kanagawa Japan

ISBN: (数字)9781665498517

ISBN: (纸本)9781665498517

When making a new microprocessor (MPU), the instruction set architecture is considered. It is also necessary to design how to work the instructions in hardware circuits of the MPU. As a solution to these, we previously proposed a method of expressing the instruction in two ways of semantic expression and functional expression. We also developed a tool that can visualize the instruction. In this paper, we have improved this method by extending a usual MPU to a meta-instruction for any MPU. We have also developed a conversion method for the meta-instruction using a relationship between the semantic and the functional expressions. Then we verified how well our meta-instruction can represent the usual instructions. It is confirmed that most of them can be represented by the meta-instruction. Since our developed tool user can design the meta-instructions from either semantic or functional expression and both expressions can be automatically converted to each other, they can design the instruction of a new MPU and can understand hardware circuits for the MPU instruction by the functional expression. © 2022 IEEE.

关键词： Semantics

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Variational quantum neural network with optimized ansatz for predicting malignant ventricular arrhythmias

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Procedia computer science 2024年 245卷 109-116页

作者： Nicholas Dominic Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia

Preventive strategies should be the utmost priority when dealing with diverse patients suffering from malignant ventricular arrhythmia (MVA) that can lead to sudden cardiac death (SCD). Electrocardiogram (ECG) data is commonly used as a predictor for MVA predictive models. In this study, all ECG signals from MIT-BIH databases were fragmented into five-minute durations with a frequency sampling of 128 Hz. To solve the absence of hybrid optimizations in Machine Learning (ML) models, a novel Variational Quantum Neural Network (VQNN) was invented. Empowered by deep learning capabilities and optimized quantum circuits design, VQNN achieved remarkable performances designated by an accuracy of up to 95.1%, a perfect 100% recall, and a 95.2% score of the area under the Receiver Operating Characteristic curve (AUC ROC) with Conjugate Gradient as an optimizer and EfficientSU2 as a quantum ansatz. Despite the susceptibility to quantum noise, this research settles a new trajectory of utilizing quantum variational algorithms to predict and expand its applicability for MVA cases.

关键词： Malignant Ventricular Arrhythmia Sudden Cardiac Death Variational Quantum Algorithm Quantum Computing Neural Network

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Efficient Hyperparameter Optimization Using Deep Q-Network and BRKGA 13

Efficient Hyperparameter Optimization Using Deep Q-Network a...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Kobayashi, Kosei Aritsugi, Masayoshi González, Pedro Henrique Mendonça, Israel Graduate School of Science and Technology Kumamoto University Kumamoto Japan Faculty of Advanced Science and Technology Kumamoto University Kumamoto Japan System Engineering and Computer Science Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9798350308365

Hyperparameter optimization (HPO) is paragon to maximize performance when designing machine learning models. Among different HPO methods, Genetic Algorithm (GA) based optimization is considered effective because it allows a wide and diverse range of solutions to be explored. However, GA's exploratory nature makes this type of algorithm to evaluate many solutions that do not improve the overall performance. This is specially costly when the objective function to be evaluated is time-consuming, like in the HPO field. In this paper, we propose an efficient hybrid algorithm that is able to reduce computational cost by combining deep reinforcement learning with the Biased Random Key Genetic Algorithm (BRKGA), a variant of genetic algorithms. Our reinforcement learning agent has a decision-making role during the population's fitness calculation, in which it filters out chromosomes that would not improve the overall fitness of the population. The agent uses small amounts of pre-trained data to identify trends in potentially good solutions, and carry out its decision process. We conduct experiments on eight different datasets to assess the effectiveness of the proposed method, and the results show that the proposed method can significantly reduce the computation time of hyperparameter search using BRKGA (up to 44% reduction in computational time) without compromising the quality of the solution (no statistically difference in results). © 2024 IEEE.

关键词： Genetic algorithms

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Smart Tourism Destinations Research Trend: A Systematic Literature Review 9

Smart Tourism Destinations Research Trend: A Systematic Lite...

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9th International Conference on ICT for Smart Society, ICISS 2022

作者： Elda Hiererra, Siti Meyliana Ramadhan, Arief Purnomo, Fredy Graduate Program Computer Science School of Information Systems Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781665471350

ISBN: (纸本)9781665471350

Purpose - This study aims to identify and analyze the main themes, the countries, the destination category, and the current trend regarding Smart Tourism research through a systematic literature review (SLR). Methodology- The research is based on a systematic review of the literature using the kitchenham method combined with the PRISMA method and focuses on smart tourism destination articles published between 2018 and 2021. Findings- The authors summarize the result, which is the main themes came out with seven clusters;the countries, there are eighteen countries spread over five regions worldwide;the destination category found three categories which are cultural heritage attractions, special events, and museums;the current trends there are top five keywords that become trends based on previous study literature review namely: Smart Tourism Destinations, Tourist Experiences, Tourism Industry, ICT, and DMOs. The originality of the research- The study provides the SLR method to investigate the main themes, the countries, the destination category, and the current trend regarding Smart Tourism research. This finding helps build a complete understanding of smart tourism destination implementation comprehensively. © 2022 IEEE.

关键词： Tourism

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Optimization of Node Reduction Using BRKGA for GNN-Based Traffic Speed Forecasting 13

Optimization of Node Reduction Using BRKGA for GNN-Based Tra...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Inokuchi, Yuto González, Pedro Henrique Mendonça, Israel Aritsugi, Masayoshi Graduate School of Science and Technology Kumamoto University Kumamoto Japan Federal University of Rio de Janeiro System Engineering and Computer Science Program Rio de Janeiro Brazil Kumamoto University Faculty of Advanced Science and Technology Kumamoto Japan

ISBN: (纸本)9798350308365

While Spatio-Temporal Graph Convolutional Networks (STGCNs) are an effective method for traffic speed fore-casting, their training and inference tend to be time-consuming. In this paper, we aim to refine these networks by strategically reducing their number of nodes, thereby boosting computational efficiency. The nodes in these graphs represent data observed for road segments, and by analyzing the interconnections and layout of the graph, we can identify nodes with minimal contribution to overall performance. Removing these nodes can potentially decrease computation time while maintaining the prediction accuracy. We employ the Biased Random-Key Genetic Algorithm (BRKGA) to identify a good set of nodes for removal, based on a predefined percentage reduction of the original graph size (e.g., retaining 95 % of the original graph). We evaluate different graph size configurations, ranging from 95 % to 70 % node retention, to determine the least impactful node set performance. Our experiments on three real-world datasets reveal that reducing nodes can decrease computation time by up to 29%, and as a byproduct of removing noise, even improve the prediction accuracy. © 2024 IEEE.

关键词： Genetic algorithms

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Domain Adaptation in Color-Shifted Datasets Through Adversarial Learning Balancing 4

Domain Adaptation in Color-Shifted Datasets Through Adversar...

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4th International Conference on Artificial Intelligence and Data sciences, AiDAS 2023

作者： Hidayaturrahman Trisetyarso, Agung Kartowisastro, Iman Herwidiana Budiharto, Widodo School of Computer Science Bina Nusatara University Mathematics Department Jakarta11480 Indonesia Bina Nusatara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Computer Engineering Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350318432

Due to the disparity in the levels of difficulty presented by the several tasks, doing domain adaptation in an adversarial way may result in an imbalanced learning process. In the MNIST dataset, this phenomenon also manifests itself in the form of domain adaptation for color-shifted distribution. In this particular situation, the domain classifier has a higher tendency to fit more quickly, but the category classifier fits quite poorly in the learning process. In order to address this problem, a new hyper-parameter has been added to the loss function in order to strike a compromise between the learning speed of the domain and the categorical classifier. By using this technique, the categorical classifier may better match the data while still maintaining the same level of performance as the domain classifier. In order to determine whether or not making use of this hyper-parameter is useful, the phenomena in question is examined using three distinct color-shifted settings. Following the evaluations, it was discovered that the newly introduced hyper-parameter is capable of coping with imbalanced learning while simultaneously engaging in domain adaptation. © 2023 IEEE.

关键词： Color

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