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Cyber Science and Technology Congress (CyberSciTech), IEEE

作者： Jianhua Ma Qun Jin Hui-Huang Hsu John Paul C. Vergara Antonio Guerrieri Claudio Miceli Ao Guo Faculty of Computer and Information Sciences Hosei University Japan Department of Human Informatics and Cognitive Sciences Waseda University Japan Department of Computer Science and Information Engineering Tamkang University Taiwan Department of Information Systems and Computer Science Ateneo de Manila University Philippines ICAR-CNR Italy Graduate Program in Systems Engineering and Computer Science Federal University of Rio de Janeiro Brazil Graduate School of Informatics Nagoya University Japan

ISBN: (数字)9798331532093

ISBN: (纸本)9798331532109

Generative Artificial Intelligence (GenAI) represents a significant milestone in the development of artificial intelligence, bringing sophisticated AI capabilities into daily life and work. As we approach the era of Hyper Intelligence (Hyper-I), a variety of critical challenges and emerging issues have come to light, ranging from computational complexity to ethical concerns. This paper explores the evolution of AI from the perspective of human learning, comparing machine and human intelligence, and identifying key considerations for the development of future AI systems. It also highlights the growing importance of regulating advanced AI models, such as Reinforcement Learning-based Long-Term Planning Agents, to ensure that Hyper-I remains under human control. Additionally, the paper discusses the computational complexity of transformer-based models, their applicability to intractable problems, and their role in cognitive building systems and resource-constrained environments through TinyML. By analyzing these pressing challenges, this work provides insights into the future of AI and the path toward responsible innovation in generative and hyper-intelligent systems.

关键词： Hyper-intelligent systems Ethics Technological innovation Generative AI Computational modeling Tiny machine learning Pressing Transformers Regulation Computational complexity

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach

Minimizing the Number of Stunting Prevalence Using the Eucli...

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International Conference of Computer Science and Information Technology

作者： Muhammad Zarlis Tanty Oktavia Relita Buaton Ferda Ernawan Kevin Andrian Department BINUS Graduate Program - Master of Information System Management Information System Management Bina Nusantara University Jakarta Indonesia Informatics Engineering STMIK Kaputama Binjai Indonesia Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia Department of Information Systems Management BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city.

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Customer Preferences for Online Games: A Conjoint Analysis Approach with Market Segmentation 22

Customer Preferences for Online Games: A Conjoint Analysis A...

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Proceedings of the 2022 6th International Conference on Software and e-Business

作者： Rogel Angelo Rebualos Yogi Tri Prasetyo Irene Dyah Ayuwati Satria Fadil Persada School of Industrial Engineering and Engineering Management Mapua University Philippines and School of Graduate Studies Mapua University Philippines School of Industrial Engineering and Engineering Management Mapua University Philippines and International Program in Engineering for Bachelor Yuan Ze University Taiwan Department of Information Systems Institut Teknologi Telkom Surabaya Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Indonesia

ISBN: (纸本)9798400700095

Online games display a unique market with a promising economy; hence many developer companies are exploring and have been utilizing this technology because of good possibility in recent years. This study aimed to determine the composition of online game attribute that is most preferred by customers using a Conjoint Analysis Approach. This study utilized different attributes such as graphics, player-to-player interaction, character creation freedom, game accessibility, monetization, storyline, and business model. An orthogonal design of conjoint analysis was utilized to assess customer preference for online games. A survey was proposed to a community of online game players and segmented among their gender, age, and income. The results showed that business model was the most considered attribute while accessibility and monetization were the least preferred. The findings of this study could be beneficial to both technology corporations developing products that fit their target customers and customers making most of their investment.

关键词： market segmentation preference conjoint online games

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Use of Conjoint Analysis Filipino Consumer Preference on Attributes of Fixed Line Internet Service Providers 22

Use of Conjoint Analysis Filipino Consumer Preference on Att...

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Proceedings of the 2022 6th International Conference on Software and e-Business

作者： Justine Kyle Chan Nattakit Yuduang Yogi Tri Prasetyo Irene Dyah Ayuwati Satria Fadil Persada School of Industrial Engineering and Engineering Management Mapua University Philippines and School of Graduate Studies Mapua University Philippines School of Industrial Engineering and Engineering Management Mapua University Philippines and International Program in Engineering for Bachelor Yuan Ze University Taiwan Department of Information Systems Institut Teknologi Telkom Surabaya Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Indonesia

ISBN: (纸本)9798400700095

Internet has evolved from a basic communication medium into wide networks of communication networks where it has become integrated in people's daily lives. Not only that, because of the recent pandemic, the demand for internet has been rapidly increasing. With the integration of internet to our day to day interactions, choosing a provider that is inclined with consumers preference and usage should be the basis. This study aims to determine the Filipino consumer preference on choosing Fixed line internet service providers using Conjoint analysis. The method uses survey questionnaires that is disseminated across the regions of the Philippines. The data gathered from the survey are analyzed using SPSS. The result shows that out of all the attributes considered internet speed is the top priority of the consumers followed by pricing and brand. Overall, this study is beneficial in developing market strategies for companies in the telecommunications industry.

关键词： Internet Service Provider Internet ISP Conjoint Analysis Attributes

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A Constructive Heuristic for the Uniform Capacitated Vertex k-center Problem

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ACM Journal of Experimental Algorithmics 2023年第2期28卷 1-26页

作者： Cornejo-Acosta, José Alejandro García-Díaz, Jesús Pérez-Sansalvador, Julio César Ríos-Mercado, Roger Z. Pomares-Hernández, Saúl Eduardo Instituto Nacional de Astrofísica Óptica y Electrónica Computer Science Department Puebla72840 Mexico Tecnológico Nacional de México/ITS de Purísima Del Rincón Computer Engineering Department Guanajuato36425 Mexico Consejo Nacional de Humanidades Ciencias y Tecnologías Mexico City03940 Mexico Universidad Autónoma de Nuevo León Graduate Program in Systems Engineering San Nicolás de los GarzaNL 66455 Mexico LAAS-CNRS Université de Toulouse France INSA ToulouseF31400 France

The uniform capacitated vertex k-center problem is an -hard combinatorial optimization problem that models real situations where k centers can only attend a maximum number of customers, and the travel time or distance from the customers to their assigned center has to be minimized. This article introduces a polynomial-time constructive heuristic algorithm that exploits the relationship between this problem and the minimum capacitated dominating set problem. The proposed heuristic is based on the one-hop farthest-first heuristic that has proven effective for the uncapacitated version of the problem. We carried out different empirical evaluations of the proposed heuristic, including an analysis of the effect of a parallel implementation of the algorithm, which significantly improved the running time for relatively large instances. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Travel time

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NOMAD: nonlinear manifold decoders for operator learning 22

NOMAD: nonlinear manifold decoders for operator learning

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Proceedings of the 36th International Conference on Neural Information Processing systems

作者： Jacob H. Seidman Georgios Kissas Paris Perdikaris George J. Pappas Graduate Program in Applied Mathematics and Computational Science University of Pennsylvania Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania Department of Electrical and Systems Engineering University of Pennsylvania

ISBN: (纸本)9781713871088

Supervised learning in function spaces is an emerging area of machine learning research with applications to the prediction of complex physical systems such as fluid flows, solid mechanics, and climate modeling. By directly learning maps (operators) between infinite dimensional function spaces, these models are able to learn discretization invariant representations of target functions. A common approach is to represent such target functions as linear combinations of basis elements learned from data. However, there are simple scenarios where, even though the target functions form a low dimensional submanifold, a very large number of basis elements is needed for an accurate linear representation. Here we present NOMAD, a novel operator learning framework with a nonlinear decoder map capable of learning finite dimensional representations of nonlinear submanifolds in function spaces. We show this method is able to accurately learn low dimensional representations of solution manifolds to partial differential equations while outperforming linear models of larger size. Additionally, we compare to state-of-the-art operator learning methods on a complex fluid dynamics benchmark and achieve competitive performance with a significantly smaller model size and training cost.

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Atmospheric humidity regulates same-sex mating in Candida albicans through the trehalose and osmotic signaling pathways

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Science China(Life Sciences) 2023年第8期66卷 1915-1929页

作者： Chao Li Li Tao Guobo Guan Zhangyue Guan Austin M.Perry Tianren Hu Jian Bing Ming Xu Clarissa J.Nobile Guanghua Huang Department of Infectious Diseases Huashan HospitalShanghai Institute of Infectious Disease and Biosecurity and State Key Laboratory of Genetic EngineeringSchool of Life SciencesFudan UniversityShanghai 200438China State Key Laboratory of Mycology Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China Department of Molecular and Cell Biology University of CaliforniaMercedMerced CA 95343USA Quantitative and Systems Biology Graduate Program University of CaliforniaMercedMerced CA 95343USA Health Sciences Research Institute University of CaliforniaMercedMerced CA 95343USA Shanghai Engineering Research Center of Industrial Microorganisms Shanghai 200438China Shanghai Huashen Institute of Microbes and Infections Shanghai 200052China

Sexual reproduction is prevalent in eukaryotic organisms and plays a critical role in the evolution of new traits and in the generation of genetic *** factors often have a direct impact on the occurrence and frequency of sexual reproduction in *** regulatory effects of atmospheric relative humidity(RH)on sexual reproduction and pathogenesis in plant fungal pathogens and in soil fungi have been extensively ***,the knowledge of how RH regulates the lifecycles of human fungal pathogens is *** this study,we report that low atmospheric RH promotes the development of mating projections and same-sex(homothallic)mating in the human fungal pathogen Candida *** RH causes water loss in *** cells,which results in osmotic stress and the generation of intracellular reactive oxygen species(ROS)and *** water transporting aquaporin Aqy1,and the G-protein coupled receptor Gpr1 function as cell surface sensors of changes in atmospheric *** of the trehalose metabolic pathway by inactivating trehalose synthase or trehalase promotes same-sex mating in *** by increasing osmotic or ROS stresses,*** trehalose and ROS signal the Hog1-osmotic and Hsf1-Hsp90 signaling pathways to regulate the mating ***,therefore,propose that the cell surface sensors Aqy1 and Gpr1,intracellular trehalose and ROS,and the Hog1-osmotic and Hsf1-Hsp90 signaling pathways function coordinately to regulate sexual mating in response to low atmospheric RH conditions in ***.

关键词： atmospheric relative humidity sexual reproduction same-sex mating Candida albicans trehalose metabolism osmotic stress

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Improving Land Cover Segmentation Using Multispectral Dataset 8

Improving Land Cover Segmentation Using Multispectral Datase...

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8th International Conference on Informatics and Computing, ICIC 2023

作者： Herlawati, Herlawati Handayanto, Rahmadya Trias Heryadi, Yaya Abdurachman, Edi Soeparno, Haryono Irwansyah, Edy Miranda, Eka Informatics Universitas Bhayangkara Jakarta Raya Jakarta Indonesia Universitas Islam 45 Computer Engineering Bekasi Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Trisakti Institute of Transportation and Logistic Jakarta13410 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University School of Information Systems Information Systems Department Jakarta11480 Indonesia

ISBN: (纸本)9798350342604

Computer vision has been used in many areas such as medical, transportation, military, geography, etc. The fast development of sensor devices inside camera and satellite provides not only red-greed-blue (RGB) images but also multispectral dataset with some channels including RGB, infrared, short-wave, and thermal wave. Most of the dataset is panchromatic (black and white) and RGB, for example Google Map and other satellite-based map applications. This study examines the effects of multispectral dataset for semantic segmentation of land cover. The comparison between RGB with band 2 to band 7 of Landsat 8 Satellite shows an improvement of accuracy from 90.283 to 94.473 for U-Net and from 91.76 to 95.183 for DeepLabV3+. In addition, this research also compares two well-known semantic segmentation methods, namely U-Net and DeepLabV3+, that shown that DeepLabV3+ outperformed U-Net regarding to speed and accuracy. Testing was conducted in the Karawang Regency area, West Java, Indonesia. © 2023 IEEE.

关键词： Landsat

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Impact point of probing rockets by telemetry and slant range 5

Impact point of probing rockets by telemetry and slant range

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5th International Symposium on Instrumentation systems, Circuits and Transducers, INSCIT 2021

作者： Cantanhede, Nilton Rodrigues Santana, Ewaldo Eder Carvalho Da Silva Junior, Paulo Fernandes De Jesus Barros, Jonas Freire, Raimundo Carlos Silverio State University of Maranhao Graduating Program in Engineering Computation and Systems São Luís Brazil Graduated in Mathematics The Federal University of Maranhão São Luís Brazil Federal University of Campina Grande Graduate Program in Electrical Engineering Campina Grande Brazil

ISBN: (纸本)9781728197265

In this work, is developing a method for obtaining the point of impact of a rocket by telemetry data and a Slant Range device. The trajectory data was obtained from a real flight path by merging the angular components of a telemetry antenna (azimuth and elevation) and the radial distance information provided by the Slant Range device. Position components were analyzed with the Telemetry antenna in automatic mode (in tracking), comparing with the tracking performance performed by the location radar. The result is obtained by the composition of the coordinates of the Telemetry-Slant Range set. A significant reduction in the search area can be used as an alternative form of use, providing additional location information for payload recovery around the actual point of impact. © 2021 IEEE.

关键词： Rockets

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IoT for Water Quality Categorization 5

IoT for Water Quality Categorization

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5th International Conference on Cybernetics and Intelligent systems, ICORIS 2023

作者： Sastrohartono, Hermantoro Krisdiarto, Andreas Wahyu Uktoro, Arief Ika Rahutomo, Reza Suparyanto, Teddy Pardamean, Bens Institute of Agriculture Stiper Faculty of Agricultural Technology Agricultural Engineering Department Yogyakarta Indonesia Bina Nusantara University School of Information Systems Information System Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics & Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350369489

In agricultural water research, the adoption of Internet of Things (IoT) technology has emerged as a pivotal approach for large-scale data collection. Water availability in the context of water quality is very important, both for domestic and industrial purposes. For domestic purposes, drinking water and bathing water are separated. Meanwhile, for the palm oil industry, boiler filler is differentiated from additional process water (dilution water). Water quality parameters can be assessed from turbidity and Total Dissolve Solid (TDS). Measurements using measuring instruments separately and repeatedly require significant energy, time, and costs. This research was conducted with the primary objective of presenting a novel method for categorizing water quality with the approach of IoT sensor technology. The research methodology entailed the utilization of an integrated IoT water sensors system in conjunction with manual water categorization. The methods consist of (1) system design, (2) design and installation of sensor and IoT-based microcontrollers, and (3) accuracy and precision testing compared with laboratory measurements. The precision of the integrated IoT water sensors was assessed through a dedicated sensor precision test, resulting in an accuracy rate of 94.4% for the turbidity sensor and 97.5% for the TDS sensor. Notably, this approach successfully discriminated drinking water with valid categorization, while other water types, including groundwater, water with tea, and water with coffee, yielded null categorization results. © 2023 IEEE.

关键词： Internet of things

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