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Decision Theory and Risk Simulation Analysis for Optimizing Profit in PayLater Services

Procedia Computer science 2023年 219卷 60-67页

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

The projected increase in PayLater utilization reaches up to five million people by 2025. To optimize the yearly profit from their PayLater service, fintech companies must examine all possible risks before a unanimous decision is taken. Therefore, we proposed a unified decision framework derived from decision theory and the Monte Carlo simulation technique. Two schemes were coined: (1) a decision-making scheme, and (2) a risk simulation scheme. Throughout experiments, the framework was able to estimate several alternative decisions and their impacts, analyze the causes of failure and delays in the development of the PayLater service, and execute Monte Carlo simulations in up to 10,000 trials. Outputs of this study will benefit decision-makers in the fintech initiative before launching their PayLater products.

关键词： PayLater decision-making Bayesian analysis fault tree analysis critical path method Monte Carlo simulation

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Machine Learning Implementations in Childhood Stunting Research: A Systematic Literature Review 8

Machine Learning Implementations in Childhood Stunting Resea...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Rahutomo, Reza Elwirehardja, Gregorius Natanael Isnan, Mahmud Asadi, Faisal Pardamean, Bens School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Binus Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350326093

Childhood stunting is a condition anticipated to affect the growth potential of children under the age of five. With numerous stunting researches that have been conducted, stunting datasets are now widely available to facilitate stunting research. This provides an opportunity to implement machine learning (ML) principles to produce a broader insight or a novel technique in stunting prediction. A systematic literature review is necessary to discover the landscape of machine learning implementation in the application domain as a preliminary study for creating an effective research roadmap. This paper presents a systematic literature review (SLR) of 22 curated manuscripts that focuses on identifying the ML models applied in stunting research, as well as the datasets used in such studies that were published during 2017-2022. The SLR process found that ML principles have been applied in stunting research since 2017, and the diversity of ML implementation has become more varied in 2021-2022. In terms of ML models, XGBoost and Random Forest are recognized as the two most utilized models, and stunting prediction is the most common ML implementation. The majority of stunting research utilizing ML has been conducted in Indonesia. Although national survey data has been the most commonly utilized dataset in stunting research, researchers in Indonesia have shown a preference for utilizing data from regional or independent surveys. This study will be followed by developing a classifier model for stunted children using XGBoost and Random Forest algorithms. The model will be trained on a dataset generated from StuntingDB. © 2023 IEEE.

关键词： Machine learning

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Mobile Internet Mobile Agent System Dynamic Trust Model for Cloud Computing

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Computers, Materials & Continua 2020年第1期62卷 123-136页

作者： Weijin Jiang Yang Wang Yirong Jiang Yuhui Xu Jiahui Chen Lina Tan Guo Liang Key Laboratory of Hunan Province for New Retail Virtual Reality Technology Hunan University of Technology and BusinessChangsha410205China Institute of Big Data and Internet Innovation Hunan University of Technology and BusinessChangsha410205China School of Computer Science and Technology Wuhan University of TechnologyWuhan430073China Tonghua Normal University Tonghua134002China School of Bioinformatics University of MinnesotaTwin CitiesUSA

In mobile cloud computing,trust is a very important parameter in mobile cloud computing security because data storage and data processing are performed remotely in the *** at the security and trust management of mobile agent system in mobile cloud computing environment,the Human Trust Mechanism(HTM)is used to study the subjective trust formation,trust propagation and trust evolution law,and the subjective trust dynamic management algorithm(MASTM)is *** on the interaction experience between the mobile agent and the execution host and the third-party recommendation information to collect the basic trust data,the public trust host selection algorithm is *** isolated malicious host algorithm and the integrated trust degree calculation algorithm realize the function of selecting the trusted cluster and isolating the malicious host,so as to enhance the security interaction between the mobile agent and the *** algorithm simulation and verification were carried out to prove its feasibility and effectiveness.

关键词： Cloud computing mobile agent system subjective trust objective trust dynamic trust management mobile Internet

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Ecological Show Cave and Wild Cave: Negative Binomial Gllvm's Arthropod Community Modelling 3

Ecological Show Cave and Wild Cave: Negative Binomial Gllvm'...

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3rd International Conference on Computer science and Computational Intelligence, ICCSCI 2018

作者： Caraka, Rezzy Eko Shohaimi, Shamarina Kurniawan, Isma Dwi Herliansyah, Riki Budiarto, Arif Sari, Shinta Purnama Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia Department of Statistics Padjadjaran University Indonesia Department of Biology UIN Sunan Gunung Djati Bandung Indonesia Kalimantan Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

Ecology is a branch of biology that studies the interaction and relationship between organisms and their environment. Abundance, distribution of organisms and patterns of biodiversity are great interests for many ecologists. One of interesting ecosystems to be studied is a cave. A cave has a typical environment character with a vulnerable ecosystem. Many caves in Indonesia, particularly in Gunungsewu karst area have been developed into tourist objects (show caves) and managed imprudently. Such cave management has potential to harm the environment and leads to ecosystem destruction. Arthropods are the most abundance fauna in cave that play critical roles in maintaining cave ecosystems equilibrium. In the heart of statistical ecology, we need to analyze the differences on Arthropods community and abiotic (climatic-edaphic) parameters among show caves and wild caves. Statistical techniques are needed for the extraction of such information. GLLVM is one method that is able to explain spatial-based information and is particularly suitable for ecology. In this paper, we use negative binomial models to see the differences on spatial patterns of predator and decomposer Arthropods, also characteristic of edaphic and climatic in each cave. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Caves

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Health Assistant Wearable-Based data science System Model: A Pilot Study 3

Health Assistant Wearable-Based Data Science System Model: A...

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3rd International Conference on Information Management and Technology, ICIMTech 2018

作者： Budiarto, Arif Febriana, Trisna Suparyanto, Teddy Caraka, Rezzy Eko Pardamean, Bens Computer Science Department Bina Nusantara University School of Computer Science Jakarta11480 Indonesia Information Systems Department Bina Nusantara University School of Information Systems Jakarta11480 Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Indonesia Faculty of Science National University of Malaysia School of Mathematical Science Bangi43000 Malaysia Computer Science Department Bina Nusantara University BINUS Graduate Program-Master of Computer Science Jakarta11480 Indonesia

ISBN: (纸本)9781538658215

The rapid development of Information and Communication Technology (ICT) has an impact on the innovation of new technology that gives benefits for health. One of its latest development is wearable device technology. Nowadays, the growth of this technology market is very positive. But unfortunately the growth of this technology is not followed by the availability of supporting applications that provide maximum benefits for users by utilizing personal health and activity data. This paper is intended to provide a report of our initial research in developing a health assistant solution that utilizes wearable device generated data. The whole research process is executed using Design Thinking approach that put the users as the main consideration. This initial research is started by designing a field research that can potentially gathered users' data generated from wearable device. A series of statistical and machine learning techniques are presented to analyze time series data to create a model. Finally, to implement the model, a mobile application prototype is also proposed. The outcomes from this initial research will be used to develop a fully working solution. © 2018 IEEE.

关键词： Learning systems

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Implementation of expert systems in potassium deficiency in cocoa plants using forward chaining method 7

Implementation of expert systems in potassium deficiency in ...

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7th International Conference on Computer science and Computational Intelligence, CSCI 2022

作者： Hafizal, Muhammad Titan Putra, Dian Pratama Wirianata, Herry Nugraha, Nanda Satya Suparyanto, Teddy Hidayat, Alam Ahmad Pardamean, Bens Faculty of Agriculture STIPER Institute of Agriculture Yogyakarta55282 Indonesia Faculty of Forestry STIPER Institute of Agriculture Yogyakarta55282 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

As one of the largest exporters in the world, cocoa (Theobroma cacao L.) production in Indonesia provides an important contribution to the plantation sector that can, directly and indirectly, attribute to the national economic development. However, recent data shows a decline in cocoa productivity in Indonesia. This is arguably caused by various factors, including poor agricultural management and practices in cocoa plantations, that may lead to lower fertility in the soil and an increased risk of diseases and pests. Potassium deficiency is a major contributing factor to the low soil fertility that affects cocoa yields. Therefore, in this work, we implement an application with an expert system utilizing the forward chaining method to detect potassium deficiency in cocoa plants and then give a fertilization-based recommendation based on the plants' condition. The system employs a set of rules to identify symptoms related to the deficiency on the sample photo of a cocoa leaf according to the channels of red, green, and blue of the image. The sample images of cocoa leaves are submitted to the application with an easy-To-use interface that can show the scanning result and proceed to display the suggested quantity of fertilizers to prevent potassium deficiency. Implementing the system can contribute constructive impacts to improve current practices in the overall cropping system of cocoa plants. © 2022 Elsevier B.V.. All rights reserved.

关键词： Expert systems

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HSPA2 influences the differentiation and production of immunomodulatory mediators in human immortalized epidermal keratinocyte lines

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Cell Death and Disease 2025年第1期16卷 1-15页

作者： Gogler, Agnieszka Wilk, Agata Małgorzata Sojka, Damian Robert Adamiec-Organiściok, Małgorzata Matysiak, Natalia Kania, Daria Wiecha, Klaudia Małusecka, Ewa Cortez, Alexander Jorge Zamojski, Dawid Marczyk, Michał Mazurek, Agnieszka Maria Oziębło, Sylwia Scieglinska, Dorota Center for Translational Research and Molecular Biology of Cancer Maria Sklodowska-Curie National Research Institute of Oncology Gliwice Branch Wybrzeze Armii Krajowej 15 Gliwice 44-102 Poland Department of Biostatistics and Bioinformatics Maria Sklodowska-Curie National Research Institute of Oncology Gliwice Branch Wybrzeze Armii Krajowej 15 Gliwice 44-102 Poland Department of Systems Biology and Engineering Silesian University of Technology Akademicka 16 Gliwice 44-100 Poland Department of Histology and Cell Pathology Faculty of Medical Sciences in Zabrze Medical University of Silesia in Katowice Jordana 19 Zabrze 41-808 Poland Department of Data Science and Engineering Silesian University of Technology Akademicka 16 Gliwice 44-100 Poland Genetic Laboratory Gyncentrum Sp. z o.o. Sosnowiec 41-208 Poland Yale Cancer Center Yale School of Medicine New Haven CT United States

Chaperone proteins constitute a molecular machinery that controls proteostasis. HSPA2 is a heat shock-non-inducible member of the human HSPA/HSP70 family, which includes several highly homologous chaperone proteins. HSPA2 exhibits a cell type-specific expression pattern in the testis, brain, and multilayered epithelia. It is a crucial male fertility-related factor, but its role in somatic cells is poorly understood. Previously, we found that HSPA2 deficiency can impair epidermal keratinocyte differentiation. In this study, we confirmed the crucial role of HSPA2 in keratinocyte differentiation by investigating immortalized keratinocytes cultured in a reconstructed human epidermis model. Moreover, we uncovered the influence of HSPA2 on immunomodulation. Transcriptomic analysis revealed that the total loss of HSPA2 affected the expression of genes related to keratinocyte differentiation and interleukin- and interferon-mediated signaling. The functional analysis confirmed bidirectional changes associated with the loss of HSPA2. The HSPA2 knockout in HaCaT and Ker-CT keratinocytes, but not HSPA2 overproduction, impaired granular layer development as evidenced by reduced levels of late keratinocyte differentiation markers, filaggrin and involucrin, along with structural abnormalities in the upper epidermal layer. Differentiation defects were accompanied by increased mRNA expression and extracellular secretion of keratinocyte-derived pro-inflammatory IL-6 cytokine and CCL2, CCL8, CXCL1, CXCL6, and CXCL10 chemokines. The loss of HSPA2 also led to increased expression of extracellular HSPA1 and interferon-stimulated genes and secretion of immune cell modulator SLAMF7. Knocking down HSPA1 expression in keratinocytes decreased the secretion of IL-6 and CCL5 release, suggesting extracellular HSPA1’s role in the HSPA2-regulated molecular network. To summarize, we uncovered the complex homeostatic role of HSPA2 in epidermal keratinocytes. Our results suggest that dysfunction in H

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On the integration of graph exploration and data analysis: The creative exploration toolkit

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in bioinformatics) 2012年 7250卷 301-312页

作者： Haun, Stefan Gossen, Tatiana Nürnberger, Andreas Kötter, Tobias Thiel, Kilian Berthold, Michael R. Data and Knowledge Engineering Group Faculty of Computer Science Otto-von-Guericke-University Germany Department for Bioinformatics and Information Mining University of Konstanz Germany

ISBN: (纸本)9783642318290

To enable discovery in large, heterogenious information networks a tool is needed that allows exploration in changing graph structures and integrates advanced graph mining methods in an interactive visualization framework. We present the Creative Exploration Toolkit (CET), which consists of a state-of-the-art user interface for graph visualization designed towards explorative tasks and support tools for integration and communication with external data sources and mining tools, especially the data-mining platform KNIME. All parts of the interface can be customized to fit the requirements of special tasks, including the use of node type dependent icons, highlighting of nodes and clusters. Through an evaluation we have shown the applicability of CET for structure-based analysis tasks. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： User interfaces

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Machine learning identification of zeolite framework types

Machine learning identification of zeolite framework types

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2009 International Conference on Artificial Intelligence, ICAI 2009

作者： Yang, Shujiang Lach-Hab, Mohammed Vaisman, Iosif I. Blaisten-Barojas, Estela Computational Materials Science Center George Mason University Fairfax VA United States Department of Bioinformatics and Computational Biology George Mason University Manassas VA United States Department of Computational and Data Sciences George Mason University Manassas VA United States

ISBN: (纸本)9781601321091

The characteristic framework types of zeolite crystals are routinely determined by calculating coordination sequences and vertex symbols of the 3D crystal structures. This method has limitations and tends to fail when the synthesized crystals are not close to perfect and present some types of crystallographic disorder. A machine learning based Zeolite-Structure-Predictor (ZSP) model is developed to predict framework types for both near perfect and moderately disordered zeolite crystals. The ZSP uses various attributes, including topological descriptors based on a computational geometry approach and relevant physical, chemical properties of the crystals. Trained with 41 framework types, the ZSP can correctly classify zeolite crystals with over 98% accuracy. Additionally, it is shown that the ZSP model is able to predict the framework types for strongly disordered zeolite crystals with reliable success rate.

关键词： Crystal structure

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A bioinformatics Analysis and Homology 3D Modeling of Dihydroxy-orotate-dehydrogenase of Plasmodium ovale

A Bioinformatics Analysis and Homology 3D Modeling of Dihydr...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Rudi Nirwantono Khoirunnisa Assidqi Alam Ahmad Hidayat Joko Pebrianto Trinugroho Bens Pardamean Biotechnology Department Faculty of Engineering Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Biotechnology Department Faculty of Engineering Food Biotechnology Research Center Bina Nusantara University Jakarta Indonesia Mathematics Departement School of Computer Science Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta Indonesia

The infection of Plasmodium vivax is relatively less virulent than the deathliest Plasmodium falciparum. However, it still can lead to a fatal case and often induces recurring malaria due to dormant parasites in the liver. Thus, the research to study the drug to treat Plasmodium vivax is essential, where the enzyme dihydroorotate dehydrogenase (DHODH) has recently become a new drug target. However, the drug-enzyme interaction study has only recently been conducted in Plasmodium falciparum (pfDHODH) due to the lack of the 3D structure of enzyme DHODH from Plasmodium vivax that is crucial for the study. Therefore, this study aimed to perform the modelling study of Plasmodium vivax DHODH (PvDHODH) to create a 3D structure as a basis for drug-protein interaction study in upcoming studies. Sequence pvDHODH (Accession: SCO68359.1) was used in homology modelling using Modeller 10.2 with the crystal structure of DHODH from DHODH (Accession: 7KZY) as a template. Overall, the model generated from the homology modelling was considered a good model, and the 3D structure was close to the native state according to several parameters, including DOPE score, GA341 score, QMEAN4 value, 3D-1D score, ERRAT2 score, and ProSA score. Ramachandran plot also revealed that almost all amino acids were distributed in the desirable and allowed area (99.1%), and only 0.9% were in generously allowed regions. Superimposition of the model with the template also indicated that the model has an almost similar structure and amino acids positioning, including in the binding pocket and active site. Therefore, the model can be used for downstream analysis in drug-protein interaction studies. Nevertheless, some improvements can still be performed to upgrade the quality of the model by deleting unaligned residues on the C-terminal and realigning the residues at the doubting site.

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