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Development of Educational Game for Indonesian History Lesson Focusing on Indonesia Pre-Literacy Relics 'Prehistoria' for Grade X High School Student

Development of Educational Game for Indonesian History Lesso...

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2020 International Conference on computer engineering, Network, and Intelligent Multimedia, CENIM 2020

作者： Nugroho, Supeno Mardi Susiki Rahman, Muhammad Daffa Abiyyu Hariadi, Mochamad Arief, Muhammad Faculty of Intelligent Electrical and Informatics Technology Sepuluh Nopember Institute of Technology Computer Engineering Department Surabaya Indonesia Tokyo University of Technology Media Science Program Graduate School of Bionics Computer and Media Sciences Tokyo Japan

ISBN: (纸本)9781728182834

The development of game technology has opened up new possibilities in learning methods through educational games. However, in Indonesia, the application of this concept is lacking. One lesson that can benefit from educational games is Indonesian History in class X, with a focus on history in the pre-literacy period. This study aims to create a puzzle-Adventure type of digital game that can help educate students about the pre-literacy period, developed with Unity, and uses WebGL as a target device while referring to Indonesia's revised 2013 national curriculum. The result of this research is the creation of a digital game that can be played on average of 254.36 seconds, with potential for educational use. A survey result shows that many of the ancient objects and some of the ages are well-recognized. However, the survey also shows many of the gameplay aspects, such as UI, gameplay features, and adventure elements, need improvements. © 2020 IEEE.

关键词： Surveys

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Fault Diagnosis of Wind Energy Conversion Systems Using Gaussian Process Regression-based Multi-Class Random Forest

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IFAC-PapersOnLine 2022年第6期55卷 127-132页

作者： Majdi Mansouri Radhia Fezai Mohamed Trabelsi Hajji Mansour Hazem Nounou Mohamed Nounou Electrical and Computer Engineering Program Texas A&M University at Qatar Doha Qatar Department of Mathematics and Sciences Prince Sultan University Riyadh 11586 Saudi Arabia Research Laboratory of Automation Signal Processing and Image National Engineering School of Monastir 5019 Tunisia Electronic and Communications Engineering Department Kuwait College of Science and Technology P. O. Box 27235 Kuwait Higher Institute of Applied Science and Technology of Kasserine University of Kairouan PO Box 471 1200 Kasserine Tunisia Chemical Engineering Program Texas A&M University at Qatar Doha Qatar

This work proposes a new fault diagnosis approach for a wind energy conversion (WEC) system. The proposed technique merges the benefits of feature extraction based on Gaussian Process Regression (GPR) and Multi-Class Random Forest (MCRF)-based fault classification where instances are classified into one or more classes. In the developed GPR-MCRF approach, the nonlinear statistical features including the mean vector M GPR and the variance matrix C GPR are computed using the GPR model with aim of extracting the most relevant features from the WEC system. Then, these features are introduced to the RF classifier for classification and diagnosis purposes. Therefore, the application of the GPR-MCRF technique for WEC systems aims to enhance the use of the classical raw data-based MCRF and diagnosis accuracy. Three kinds of faults (wear-out, open-circuit, and short-circuit faults) are considered in this work. Different case studies are investigated in order to illustrate the effectiveness and robustness of the developed technique compared to the state-of-the-art methods. The obtained results show that the the developed GPR-MCRF technique is an effective feature extraction and fault diagnosis technique for WEC systems.

关键词： Random Forest (RF) Multi-Class Gaussian Process Regression (GPR) Fault Diagnosis Wind Energy Conversion Systems

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Single Cell Investigative Genetics: Single-Cell Data Produces Genotype Distributions Concentrated at the True Genotype Across All Mixture Complexities

SSRN

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SSRN 2023年

作者： Grgicak, Catherine M. Bhembe, Qhawe Sheth, Nidhi C. Duffy, Ken R. Lun, Desmond S. Department of Chemistry Rutgers University CamdenNJ08102 United States Center for Computational and Integrative Biology Rutgers University CamdenNJ08102 United States Program in Biomedical Forensic Sciences Boston University BostonMA02118 United States Department of Mathematics Northeastern University BostonMA02115 United States Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Hamilton Institute Maynooth University Ireland Department of Computer Science Rutgers University CamdenNJ08102 United States

In the absence of a suspect or PoI the forensic aim is investigative, and the focus is one of discerning what candidate genotypes best explain the evidence. In traditional bulk systems, the list of candidate genotypes may become vast if the sample contains DNA from many donors or the information from a minor contributor is swamped by that of major contributors, leading to lower evidential value for a true donor’s contribution and, as a result, possibly overlooked or inefficient investigative *** developments in single-cell analysis offer a way forward, by producing data capable of discriminating between genotypes. This is accomplished by first clustering single-cell data by similarity without reference to a known genotype. With good clustering it is reasonable to assume that the scEPGs in a cluster are of a single contributor. With that assumption we determine the probability of a cluster’s content given each possible genotype at each locus, which is then used to determine the posterior probability mass distribution for all genotypes by application of Bayes’ rule. A decision criterion is then applied such that the sum of the ranked probabilities of all genotypes falling in the set is at least . This is the credible genotype set and is the one used to inform database search criteria and, thus, investigative *** demonstrate the salience of single cell analysis by performance testing a set of 630 previously constructed admixtures containing up to 5 donors of balanced and unbalanced contributions. We use scEPGs that were generated by isolating single cells, employing a direct-to-PCR extraction treatment, amplifying STRs that are compliant with existing national databases and applying post-PCR treatments that elicit a detection limit of one DNA copy. We determined that, for these test data, 99.3% of the true genotypes are included in the 99.8% credible set, regardless of the number of donors that comprised the mixture. We also determined that the most proba

关键词： DNA

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Flexible dual-branched message passing neural network for quantum mechanical property prediction with molecular conformation

arXiv

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arXiv 2021年

作者： Jo, Jeonghee Kwak, Bumju Lee, Byunghan Yoon, Sungroh Interdisciplinary Program in Bioinformatics Seoul National University Recommendation Team Kakao Corporation Department of Electronic and IT Media Engineering Seoul National University of Science and Technology Department of Electrical and Computer Engineering Seoul National University

A molecule is a complex of heterogeneous components, and the spatial arrangements of these components determine the whole molecular properties and characteristics. With the advent of deep learning in computational chemistry, several studies have focused on how to predict molecular properties based on molecular configurations. Message passing neural network provides an effective framework for capturing molecular geometric features with the perspective of a molecule as a graph. However, most of these studies assumed that all heterogeneous molecular features, such as atomic charge, bond length, or other geometric features always contribute equivalently to the target prediction, regardless of the task type. In this study, we propose a dual-branched neural network for molecular property prediction based on message-passing framework. Our model learns heterogeneous molecular features with different scales, which are trained flexibly according to each prediction target. In addition, we introduce a discrete branch to learn single atom features without local aggregation, apart from message-passing steps. We verify that this novel structure can improve the model performance with faster convergence in most targets. The proposed model outperforms other recent models with sparser representations. Our experimental results indicate that in the chemical property prediction tasks, the diverse chemical nature of targets should be carefully considered for both model performance and generalizability. © 2021, CC BY.

关键词： Deep learning

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Spin scattering and Hall effects in monolayer Fe3GeTe2

arXiv

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arXiv 2023年

作者： Yu, Luyan Yu, Jie-Xiang Zang, Jiadong Lake, Roger K. Zhuang, Houlong Yin, Gen Department of Physics University of Texas at Austin AustinTX78712 United States Department of Physics University of Florida GainesvilleFL32611 United States Department of Physics and Materials Science Program University of New Hampshire DurhamNH03824 United States Department of Electrical and Computer Engineering University of California-Riverside RiversideCA92521 United States Mechanical and Aerospace Engineering Arizona State University TempeAZ85287 United States Department of Physics Georgetown University WashingtonDC20057 United States

We theoretically show that the carrier transport in monolayer Fe3GeTe2 experiences a transition between anomalous Hall effect and spin Hall effect when the spin polarization of disorders switches between out-of-plane and in-plane. These Hall effects are allowed when the magnetization is polarized in-plane, breaking the C3 rotation symmetry. The transition originates from the selection rule of spin scattering, the strong spin-orbit coupling, and the van Hove singularities near the Fermi surface. The scattering selection rule tolerates the sign change of the disorder spin, which provides a convenient method to detect the switching of antiferromagnetic insulators regardless of the interfacial roughness in a heterostructure. This provides a convenient platform for the study of 2D spintronics through various van-der-Waals heterostructures. Copyright © 2023, The Authors. All rights reserved.

关键词： Monolayers

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Current status of the preclinical evaluation of alternating electric fields as a form of cancer therapy

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Bioelectrochemistry 2023年 149卷 108287页

作者： Pohling, Christoph Nguyen, Ha Chang, Edwin Schubert, Keith E. Nie, Ying Bashkirov, Vladimir Yamamoto, Vicky Zeng, Yuping Stupp, Roger Schulte, Reinhard W. Patel, Chirag B. Division of Biomedical Engineering Sciences Loma Linda University School of Medicine Loma LindaCA92350 United States Department of Electrical and Computer Engineering Baylor University WacoTX76798 United States Molecular Imaging Program at Stanford Department of Radiology Stanford University School of Medicine StanfordCA94305 United States Department of Neurosurgery Loma Linda University School of Medicine Loma LindaCA92350 United States Norris Comprehensive Cancer Center University of Southern California Keck School of Medicine Los AngelesCA90033 United States Department of Electrical and Computer Engineering University of Delaware NewarkDE19716 United States Department of Neurosurgery Department of Neurology Division of Neuro-OncologyDepartment of Medicine Division of Hematology/Oncology Northwestern University Feinberg School of Medicine ChicagoIL60611 United States Department of Neuro-Oncology The University of Texas MD Anderson Cancer Center HoustonTX77030 United States Neuroscience Graduate Program The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences HoustonTX77030 United States Cancer Biology Graduate Program The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences HoustonTX77030 United States

Exposing cancer cells to alternating electric fields of 100-300 kHz frequency and 1-4 V/cm strength has been shown to significantly reduce cancer growth in cell culture and in human patients. This form of anti-cancer therapy is more commonly referred to as tumor treating fields (TTFields), a novel treatment modality that has been approved by the U.S. Food and Drug Administration for use in patients with glioblastoma and malignant pleural mesothelioma. Pivotal trials in other solid organ cancer trials are underway. In regards to overall survival, TTFields alone is comparable to chemotherapy alone in recurrent glioblastoma. However, when combined with adjuvant chemotherapy, TTFields prolong median survival by 4.9 months in newly-diagnosed glioblastoma. TTFields hold promise as a therapeutic approach to numerous solid organ cancers. This review summarizes the current status of TTFields research at the preclinical level, highlighting recent aspects of a relatively complex working hypothesis. In addition, we point out the gaps between limited preclinical in vivo studies and the available clinical data. To date, no customized system for TTFields delivery in rodent models of glioblastoma has been presented. We aim to motivate the expansion of TTFields preclinical research and facilitate the availability of suitable hardware, to ultimately improve outcomes in patients with cancer. © 2022 The Authors

关键词： Tumors

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A Genetic Algorithm to Optimize Cargo Stability in Container Transportation

A Genetic Algorithm to Optimize Cargo Stability in Container...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Chi-Jung Hsieh Kuang-Sung Wu Tin-Yu Wu Fu Jie Tey Yi-Kai Chen Jye Yi Ho Department of Computer Science and Information Engineering National Ilan University Ilan County Taiwan Master Program of E-Learning for Multimedia and Network Communications National Ilan University Yilan Taiwan Department of Management Information Systems National Pingtung University of Science and Technology Pingtung County Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan

ISBN: (纸本)9781665492331

In the era of the global village, frequent cross-border trade in goods has made container transportation a significant part in delivery of cargo. However, rollover accidents of container trucks often occur because of tall truck height, improper cargo stowage or crooked roads. Therefore, how to find the optimal center of gravity (CG) of the packed cargo remains an issue that the transportation industry should not neglect. To optimize cargo stability and reduce the incidence of rollovers, this paper proposes a genetic algorithm that scores the cargo stacking process to find the best CG of the cargo based on the CG of the vehicle. According to the deviation angle and the point closest to the best CG, we can Figure out the optimal cargo stacking method.

关键词： Rollover Transportation industry Roads Stacking Transportation Containers Safety

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Crack Catcher AI — Enabling Smart Fracture Mechanics Approach for Damage Control in Thin Silicon Wafers for 3D Semiconductor Integrated Devices/Packages

Crack Catcher AI — Enabling Smart Fracture Mechanics Approa...

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Annual International Symposium on Reliability Physics

作者： Gabriel Preston Greer Gonzolez Andrea S. Karnyoto Fitya S. Mozar Matthew M. Henry Mahmud Isnan Kuncahyo S. Nugroho Henry Candra Muhamad Doris Dianing N. N. Putri Tyas K Sari Bens Pardamean Endang Djuana Derrric Speaks Arief S. Budiman Oregon Renewable Energy Center (OREC) Oregon Institute of Technology (Oregon Tech) Klamath Falls OR USA Dept. of Manufacturing & Mechanical Eng. & Tech. (MMET) Oregon Institute of Technology Klamath Falls OR USA Bioinformatics & Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia Computer Sci. Dept. BINUS Grad. Program - Master of Computer Sci. Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Center for Artificial Intelligence and Advanced Technology (CAPTIVATE) Universitas TRISAKTI Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Universitas TRISAKTI Jakarta Indonesia Industrial Eng. Dept. BINUS Grad. Program – Master of Industrial Eng. Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

The importance of silicon cannot be undermined - in photovoltaics (PV) as well as in semiconductor industries. However, silicon is very brittle. Silicon cells/wafers crack easily during manufacturing assembly and/or during device operations. Crack Catcher AI uses novel smart fracture mechanics approach with Artificial Intelligence (AI) methodologies to predict and control crack/damage evolution in thin silicon cells/wafers. This is critical as semiconductor 3D integration technology calls for wafer-to-wafer bonding with utmost alignment accuracy and yield/reliability.

关键词： Semiconductor device measurement Three-dimensional displays Accuracy Semiconductor device reliability Silicon Artificial intelligence Bonding Stress Three-dimensional integrated circuits Stress measurement

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The Role of Heterogeneity in Autonomous Perimeter Defense Problems

arXiv

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arXiv 2022年

作者： Adler, Aviv Mickelin, Oscar Ramachandran, K. Sukhatme, Gaurav S. Karaman, Sertac Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Program in Applied and Computational Mathematics Princeton University Princeton NJ08544 United States Department of Computer Science University of Southern California Los AngelesCA90089 United States Department of Aeronautics and Astronautics Massachusetts Institute of Technology CambridgeMA02139 United States

When is heterogeneity in the composition of an autonomous robotic team beneficial and when is it detrimental? We investigate and answer this question in the context of a minimally viable model that examines the role of heterogeneous speeds in perimeter defense problems, where defenders share a total allocated speed budget. We consider two distinct problem settings and develop strategies based on dynamic programming and on local interaction rules. We present a theoretical analysis of both approaches and our results are extensively validated using simulations. Interestingly, our results demonstrate that the viability of heterogeneous teams depends on the amount of information available to the defenders. Moreover, our results suggest a universality property: across a wide range of problem parameters the optimal ratio of the speeds of the defenders remains nearly constant. Copyright © 2022, The Authors. All rights reserved.

关键词： Dynamic programming

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3D Printed Biomimetic Composite for Treatment of Osteochondral Defects: A Preliminary Study in Porcine

SSRN

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SSRN 2025年

作者： Eckstein, Kevin N. Liu, Boyuan Schoonraad, Sarah A. Guastaldi, Fernando Pozzi Semeghini Uzcategui, Camila Muralidharan, Archish McLeod, Robert R. Randolph, Mark A. Bryant, Stephanie J. Ferguson, Viginia L. Paul M. Rady Department of Mechanical Engineering University of Colorado at Boulder BoulderCO80309 United States Materials Science and Engineering Program University of Colorado at Boulder BoulderCO80309 United States Division of Oral and Maxillofacial Surgery Department of Surgery Massachusetts General Hospital Harvard School of Dental Medicine Harvard Medical School BostonMA02114 United States Division of Plastic and Reconstructive Surgery Department of Surgery Massachusetts General Hospital Harvard Medical School BostonMA02114 United States Department of Electrical Computer and Energy Engineering University of Colorado at Boulder BoulderCO80309 United States Department of Chemical and Biological Engineering University of Colorado at Boulder BoulderCO80309 United States BioFrontiers Institute University of Colorado at Boulder BoulderCO80309 United States

Osteochondral defects in diarthrodial joints can occur as a result of trauma. When left untreated, the surrounding tissues experience abnormal mechanical loads that can cause further degeneration. Thus, treatment of osteochondral defects requires the ability to support physiological loads and prevent further degeneration of surrounding tissues. Additive manufacturing techniques, such as bio-ink printing, have been explored to structurally reinforce soft scaffolds;however, these methods struggle to accurately print complex designs with small feature sizes (e.g., on the order of ~100 micrometers). In this study, we present a composite osteochondral scaffold with regional stiffness gradients, optimized to mimic the mechanical properties of articular cartilage and limit high strains in the subchondral bone. This scaffold incorporates a load-bearing structure, with ≥ 180 μm diameter truss elements, that is 3D printed via projection micro-stereolithography with a biomimetic soft hydrogel. We hypothesized that incorporating a reinforcing structure with cartilage and bone regions possessing tissue-specific stiffnesses, compared to a soft gel alone, would reduce degradation of native cartilage tissue adjacent to osteochondral defects and promote multi-tissue integration in porcine knees after six weeks. Histological analysis and microcomputed tomography revealed site-specific changes in the surrounding tissue, notably in the adjacent cartilage. Mechanical evaluation of adjacent native tissue showed that scaffolds with the 3D printed composite structure resulted in 33% less surrounding cartilage degradation compared to gel-only treatments. Within the defect, the soft gel alone limited mineralization, while the composite supported mineralization but only in its stiffer region. These findings suggest that incorporating a 3D printed reinforcing osteochondral mimetic structure protects the adjacent cartilage, enhances tissue integration, and spatially supports mineralization. © 2

关键词： Bone

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