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International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Kus Andriadi Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Batik is an Indonesian world cultural heritage. Batik consists of many kinds of patterns depending on where the batik comes from, Batik-making techniques continue to develop along with technology development. Among the batik making techniques that are widely used are hand-written, stamping, and printing. Batik motifs have been widely used as research material, especially in the field of artificial intelligence. The diverse appearance of batik motifs has attracted many researchers to carry out research on making synthetic batik patterns, one of which uses a Generative Adversarial Network. This paper presents a synthetic batik pattern model based on the Wasserstein Generative Adversarial Network with Gradient Penalty. This model has been proven to create new synthetic batik patterns quite well and almost identical with images provided in the dataset, with the notes if the dataset provided is large.

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Interpretable Machine Learning for Multi-Class Crop Yield Prediction

Interpretable Machine Learning for Multi-Class Crop Yield Pr...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Aldian Nurcahyo Yaya Heryadi Lukas Wayan Suparta Ilvico Sonata Compuer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia Compuer Science Departement Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

Crop Yield Analysis and Prediction is a fast-expanding discipline that is critical for optimizing agricultural methods. A lack of trustworthy data is one of the challenges in estimating crop yields. We develop predictive models for 22 different fruits and vegetables data. The goals of this study are to create accurate and interpretable crop recommendation models. We used multiple machine learning (ML) models for multi-class crop production prediction to fulfill our research goal. We thoroughly examined the influence of climate and nutrient factors on crop yield, considering their complex interactions. To improve the dataset, augmented data techniques were applied. Configuring the parameters and fine-tuning the hyperparameters is our technique to increase the model performance. Furthermore, we employ explainable artificial intelligence (XAI) techniques and interpretability tools like Shapley Additive exPlanations (SHAP) to improve the interpretability of our prediction model. Our findings reveal that the XGBoost model has the best performance model with 99.86% accuracy, followed by SVM Poly Kernel with 99.32% and Random Forest with 98.82%. Feature selection and analysis are emphasized, particularly in regional agricultural contexts. This study contributes to the creation of accurate and interpretable crop recommendation models while also addressing the issue of untrustworthy data, providing useful insights for optimizing agricultural practices.

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Cloud-Native Mobile Application Applied for Law and Regulations Harmonization

Cloud-Native Mobile Application Applied for Law and Regulati...

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Intelligent Cybernetics Technology & Applications (ICICyTA), International Conference on

作者： Muhammad Juan Al Qausar Yaya Heryadi Lukas Lukas Wayan Suparta Ilvico Sonata Computer Science Department Binus Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group (CERG) Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Navigating the complex legal and regulatory landscape requires a sophisticated platform that is not only comprehensive but also user-friendly and enables seamless analysis and document comparison in the legal realm. To address this challenging requirement, this research is dedicated to the user experience (UX) design of state-of the-art cloud-native mobile applications specifically designed for legal and regulatory harmonization. The methodology used is based on design thinking principles and takes advantage of the benefits of cloud computing. These include, but are not limited to, scalability, reliability, and security. The result is a solution that is not only powerful but also cost-effective. The core of this application follows a user-centered design philosophy and involves potential users closely in the design process. A comprehensive evaluation is performed using the System Usability Scale (SUS) methodology to measure the effectiveness and usability of the application. The results of this comprehensive approach are convincing. The application has an impressive 95.5% usage rate, indicating strong user engagement. Furthermore, user satisfaction ratings are particularly high and transformative impact of this application in a complex environment of legal harmonization. Through its innovative design, seamless functionality, and user-centric approach, this application has proven to be not only a technical solution, but also a catalyst for positive change in the legal and regulatory harmonization process.

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Analyzing microbial communities and metabolic functions in estuaries affected by human activity to uncover bioelectrochemical system potential

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Environmental Advances 2024年 16卷

作者： Amin, Muhammad Hilman Fu'adil Kim, Hyun-Woo Kim, Kyunghoi Wahyudianto, Febri Eko Dianbudiyanto, Wahid Oktavitri, Nur Indradewi Advanced Tropical Biodiversity Genomics and Conservation Research Group Faculty of Science and Technology Universitas Airlangga Surabaya 60115 Indonesia Department of Biology Faculty of Science and Technology Universitas Airlangga Surabaya 60115 Indonesia Department of Marine Biology Pukyong National University Busan 48513 South Korea Department of Ocean Engineering Pukyong National University Busan 48513 South Korea Study Program of Environmental Engineering Faculty of Science and Technology Universitas Airlangga Surabaya 60115 Indonesia

In the context of bioelectrochemical systems (BES), a profound understanding of the taxonomic composition within indigenous microbial communities is crucial. Their metabolic versatility assumes a foundational role in dictating the functionality of BES, yielding diverse applications for bioenergy production and bioremediation in anthropogenically impacted estuaries. Employing high-throughput sequencing of the V3-V4 region of 16S rRNA and predictive metagenomic analyses of three different estuaries samples (eutrophicated urban reservoir, mud volcano impacted river, and its river mouth), this study delves into the intricate interplay between these communities and their metabolic functions in response to human-induced perturbations, with a specific focus on their applicability to BES. Our findings illuminate remarkable distinctions among the three samples, manifesting in variations in microbial composition and functional metabolic pathways within the respective ecosystems. The mud volcano-affected river, characterized by the highest microbial diversity, exhibited the most diverse array of functional metabolic processes, prominently dominated by chemoheterotrophy (67.43%). In contrast, the river mouth displayed a distinct penchant for autotrophy (33.33%). The eutrophicated urban reservoir showcased a balanced coexistence of chemoheterotrophy (41.18%) and autotrophy (35.29%). Regarding metabolic potential for BES application, most of metabolism potential were associated with anodic activity, while cathodic activity was restricted to autotrophy and its relatives. The results suggested that the microbial communities anthropogenically impacted estuaries were potentially used for anodic and cathodic reactions in BES as electrogens to generate bioelectricity and reduce of pollutants. © 2024

关键词： 16S rDNA Estuaries Microbial communities Pollution Predictive metagenomic Renewable energy

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Atmospheric dynamics and early warning system low level windshear for airport runway hazard mitigations 10

Atmospheric dynamics and early warning system low level wind...

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10th International Seminar on New Paradigm and Innovation of Natural sciences and itsApplication, ISNPINSA 2020

作者： Gernowo, R. Subagio, A. Adi, K. Widodo, A.P. Widodo, C.E. Putranto, A.B. Department of Physics Faculty of Science and Mathematics Diponegoro University Indonesia Department of Informatics Faculty of Science and Mathematics Diponegoro University Indonesia Study Program of Automation Engineering Technology Vocational School Diponegoro University Jl. Prof. Soedarto SH. Tembalang Semarang50275 Indonesia

Natural disaster nowadays often occur in Indonesia due to climate change, especially those related to atmospheric dynamics anomalies. The statutory event of atmospheric turbulence statistically is quite significant in its improvement. This is an important issue to conduct research both in the analysis of atmospheric dynamics and early detection solutions for these events. The Windshear phenomenon is an atmospheric turbulence disaster that occurs below an altitude of 3000 feet, often known as low level windshear (LLWS), which is very dangerous for planes taking take-off or landing. Its effect on the aircraft will result in increased airflow on the wings, so this increased airflow will result in a sudden increase in aircraft speed. If the pilot is not aware of the indication of the windshear, he will instinctively throttle back to reduce/compensate for the aircraft's speed. However, once the plane passes through the wind shear zone, the wind suddenly turns into a downdraft. The design of windshear early detection devices have been developed to complement research on the dynamics of the atmosphere. The results obtained are anomalous changes in temperature and atmospheric pressure at this time, and the windshear sensor can detect it well. © Published under licence by IOP Publishing Ltd.

关键词： Aircraft

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TranDRL: A Transformer-Driven Deep Reinforcement Learning Enabled Prescriptive Maintenance Framework

arXiv

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arXiv 2023年

作者： Zhao, Yang Yang, Jiaxi Wang, Wenbo Yang, Helin Niyato, Dusit 2 Fusionopolis Way Innovis #08-04 Singapore138634 Singapore Shenzhen Institute for Advanced Study School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Faculty of Mechanical and Electrical Engineering Yunnan Key Laboratory of Intelligent Control and Application Kunming University of Science and Technology Kunming650050 China Department of Information and Communication Engineering Xiamen University Xiamen361005 China School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore

Industrial systems require reliable predictive maintenance strategies to enhance operational efficiency and reduce downtime. Existing studies rely on heuristic models which may struggle to capture complex temporal dependencies. This paper introduces an integrated framework that leverages the capabilities of the Transformer and Deep Reinforcement Learning (DRL) algorithms to optimize system maintenance actions. Our approach employs the Transformer model to effectively capture complex temporal patterns in IoT sensor data, thus accurately predicting the Remaining Useful Life (RUL) of equipment. Additionally, the DRL component of our framework provides cost-effective and timely maintenance recommendations. Numerous experiments conducted on the NASA C-MPASS dataset demonstrate that our approach has a performance similar to the ground-truth results and could be obviously better than the baseline methods in terms of RUL prediction accuracy as the time cycle increases. Additionally, experimental results demonstrate the effectiveness of optimizing maintenance actions. Copyright © 2023, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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Meaningful human control: actionable properties for AI system development

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AI and Ethics 2022年第1期3卷 241-255页

作者： Cavalcante Siebert, Luciano Lupetti, Maria Luce Aizenberg, Evgeni Beckers, Niek Zgonnikov, Arkady Veluwenkamp, Herman Abbink, David Giaccardi, Elisa Houben, Geert-Jan Jonker, Catholijn M. van den Hoven, Jeroen Forster, Deborah Lagendijk, Reginald L. AiTech Interdisciplinary Research Program on Meaningful Human Control Delft University of Technology Delft The Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands Faculty of Industrial Design Engineering Delft University of Technology Delft The Netherlands Faculty of Mechanical Maritime and Materials Engineering Delft University of Technology Delft The Netherlands Faculty of Technology Policy and Management Delft University of Technology Delft The Netherlands

How can humans remain in control of artificial intelligence (AI)-based systems designed to perform tasks autonomously? Such systems are increasingly ubiquitous, creating benefits - but also undesirable situations where moral responsibility for their actions cannot be properly attributed to any particular person or group. The concept of meaningful human control has been proposed to address responsibility gaps and mitigate them by establishing conditions that enable a proper attribution of responsibility for humans; however, clear requirements for researchers, designers, and engineers are yet inexistent, making the development of AI-based systems that remain under meaningful human control challenging. In this paper, we address the gap between philosophical theory and engineering practice by identifying, through an iterative process of abductive thinking, four actionable properties for AI-based systems under meaningful human control, which we discuss making use of two applications scenarios: automated vehicles and AI-based hiring. First, a system in which humans and AI algorithms interact should have an explicitly defined domain of morally loaded situations within which the system ought to operate. Second, humans and AI agents within the system should have appropriate and mutually compatible representations. Third, responsibility attributed to a human should be commensurate with that human’s ability and authority to control the system. Fourth, there should be explicit links between the actions of the AI agents and actions of humans who are aware of their moral responsibility. We argue that these four properties will support practically minded professionals to take concrete steps toward designing and engineering for AI systems that facilitate meaningful human control.

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Biocompatibility evaluation of electrospun Poly-L lactic Acid-chitosan immobilized with heparin as scaffold for vascular tissue repair

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Journal of science: Advanced Materials and Devices 2023年第3期8卷

作者： Suroto, Nur Setiawan Al Fauzi, Asra Widiyanti, Prihartini Bella, Fitria Renata Department of Neurosurgery Faculty of Medicine Universitas Airlangga – Dr. Soetomo General Academic Hospital Surabaya Indonesia Biomedical Engineering Study Program Department of Physics Faculty of Science and Technology Universitas Airlangga Jawa Timur 60115 Indonesia

Stroke is the second leading cause of death worldwide, disability, high morbidity, and mortality. One of the leading causes of infarct stroke is carotid stenosis. The postoperative narrowing of the carotid artery diameter is a common complication after primary arterial closure in carotid endarterectomy surgery. A biomaterial design that combines synthetic and natural polymers is a promising strategy for patching arterial closure. In this paper, the electrospinning process was employed and Poly-L Lactic Acid (PLLA) was used as a base material. Chitosan and heparin were added to increase the biocompatibility of the biomaterial. The electrospun PLLA-chitosan immobilized with heparin (C sample) had better characteristics than the pure electrospun PLLA. The fiber diameter decreased to a micrometer scale and the pore size fell and became narrower, resulting in a smoother surface. Fiber diameter results for each sample were 1312.66 nm, 486.29 nm and 387.87 nm. Thereby potentially reducing the activation of blood coagulation and inflammation. The ultimate tensile strength test result for each sample were 2.28 MPa, 3.61 MPa and 3.25 MPa, for elongation results were 12.05%, 17.39%, and 18.14%, aligned with those of the human carotid artery and indicating potential use in patch angioplasty applications. This scaffold nanofiber was declared non-haemolytic for the C sample was 1.13% and non-cytotoxic. Percent viability for each sample was 89.35%, 83.81% and 78.92%. The in vivo host tissue response was shown to decrease pro-inflammatory cytokine expressions. This research shows that the proposed PLLA-chitosan-heparin biomaterial has strong physical properties and can modify the inflammatory response. However, it requires additional biofunctional alterations to optimize its tissue engineering capabilities. © 2023 Vietnam National University, Hanoi

关键词： Chitosan Electrospinning Heparin Poly-L-lactic acid Vascular patch

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Hotel Information System Management Audit Using COBIT 2019 - APO12

Hotel Information System Management Audit Using COBIT 2019 -...

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Innovation in Technology (INOCON), IEEE International Conference for

作者： Joy Nashar Utamajaya Suhono Harso Supangat Ford Lumban Gaol Benny Ranti BINUS Graduate Program School of Information System BINUS University Jakarta Indonesia School of Electrical Engineering and Informatic Bandung Institute of Technology Bandung Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Faculty of Computer Science University of Indonesia Depok Indonesia

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company’s business goals. Given the large contribution of information technology in the application of hotel applications as a supporting information system, it is a vital system that must avoid risks that can hinder and cause harm to the hotel management business processes. Therefore, it is necessary to carry out risk management using the COBIT 5 framework to manage possible risks that may occur based on the APO12 (Manage Risk) domain. From the evaluation results of the data obtained through observation and interviews as well as the calculation of the results of the questionnaire based on 6 APO12 subdomains, the results of the risk management level capability assessment in hotel applications are still at level 3 or have reached the level of established process with the target to be achieved at level 4 resulting in a gap of 1 level. Based on the results obtained, it is necessary to propose recommendations that can be used by hotels in improving the application of information technology risk management so that in the future it can achieve the expected target level so that the APO12 level of capability can increase and become more optimal.

关键词： Technological innovation Companies Risk management Information technology Interviews Information systems

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Cross-system biological image quality enhancement based on the generative adversarial network as a foundation for establishing a multi-institute microscopy cooperative network

arXiv

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arXiv 2024年

作者： Panek, Dominik Rząca, Carina Szczypior, Maksymilian Sorysz, Joanna Misztal, Krzysztof Baster, Zbigniew Rajfur, Zenon Doctoral School of Exact and Natural Sciences Jagiellonian University ul. Lojasiewicza 11 Kraków30-348 Poland Department of Molecular and Interfacial Biophysics Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University ul. Lojasiewicza 11 Kraków30‑348 Poland Undergraduate Program in Biophysics Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University ul. Lojasiewicza 11 Kraków30‑348 Poland Undergraduate program in Biomedical Engineering Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Al. A. Mickiewicza 30 Building B-1 Kraków30-059 Poland Division of Computational Mathematics Faculty of Mathematics and Computer Science Jagiellonian University 6 Lojasiewicza St. Kraków Poland

High-quality fluorescence imaging of biological systems is limited by processes like photobleaching and phototoxicity, and also in many cases, by limited access to the latest generations of microscopes. Moreover, low temporal resolution can lead to a motion blur effect in living systems. Our work presents a deep learning (DL) generative-adversarial approach to the problem of obtaining high-quality (HQ) images based on their low-quality (LQ) equivalents. We propose a generative-adversarial network (GAN) for contrast transfer between two different separate microscopy systems: a confocal microscope (producing HQ images) and a wide-field fluorescence microscope (producing LQ images). Our model proves that such transfer is possible, allowing us to receive HQ-generated images characterized by low mean squared error (MSE) values, high structural similarity index (SSIM), and high peak signal-to-noise ratio (PSNR) values. For our best model in the case of comparing HQ-generated images and HQ-ground truth images, the median values of the metrics are 6·10-4, 0.9413, and 31.87, for MSE, SSIM, and PSNR, respectively. In contrast, in the case of comparison between LQ and HQ ground truth median values of the metrics are equal to 0.0071, 0.8304, and 21.48 for MSE, SSIM, and PSNR respectively. Therefore, we observe a significant increase ranging from 14% to 49% for SSIM and PSNR respectively. These results, together with other single-system cross-modality studies, provide proof of concept for further implementation of a cross-system biological image quality enhancement. © 2024, CC BY-SA.

关键词： Fluorescence imaging

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