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Efficiently catalyzing photo-oxidation of water by surface engineering of bismuth vanadate with nickel molybdenum oxide coverages

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International Journal of Hydrogen Energy 2024年 51卷 613-622页

作者： Kuo, Tsung-Rong Huang, Hsiao-Wen Kongvarhodom, Chutima Saukani, Muhammad Yougbaré, Sibidou Chen, Hung-Ming Lin, Lu-Yin International PhD Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan Department of Chemical Engineering King Mongkut's University of Technology Thonburi 126 Pracha-u-thit Toong-kru Bangkok10140 Thailand Department of Mechanical Engineering Faculty of Engineering Universitas Islam Kalimantan MAB Jl. Adhyaksa No. 2 Banjarmasin70124 Indonesia /Nanoro 03 B.P 7192 Ouagadougou 03 Burkina Faso Gingen Technology Co. LTD. Rm. 7 10F. No.189 Sec. 2 Keelung Rd. Xinyi Dist. Taipei11054 Taiwan

Bismuth vanadate with suitable band edges is one of the efficient photocatalysts for water oxidation. Establishing heterojunction can improve electron diffusion lengths and photocatalytic ability of BiVO4. In this work, nickel molybdenum oxide (Ni–Mo–O) and BiVO4 heterojunction is established by the hydrothermal process with different nickel to molybdenum precursor ratios. The Ni–Mo–O/BiVO4 electrode is applied as photoanodes for water oxidation. The growth mechanism of Ni–Mo–O on BiVO4 surface is proposed. The Ni–Mo–O deposition amount is optimized regarding to light absorbance and charger transportation. The largest photocurrent density of 1.72 mA/cm2 at 1.23 VRHE is obtained for the optimal NiMoO4/BiVO4 electrode (NM12) in the electrolyte without hole scavenger, while the pure BiVO4 electrode only shows a photocurrent density of 0.90 mA/cm2. The NM12 electrode even presented an impressive photocurrent density of 5.39 mA/cm2 at 1.23 VRHE in the electrolyte with the hole scavenger, owing to the abundant active sites and higher light absorbance as well as the favorable synergistic effects from its suitable Ni to Mo ratio. The NM12 electrode also shows excellent long-term stability with the photocurrent retention of 83% after illumination for 6500 s. This work opens a blueprint for establishing a novel heterojunction with the adjustable metal ratio and coverage on BiVO4. © 2023 Hydrogen Energy Publications LLC

关键词： Heterojunctions

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A Novel Approach for Commercial Opportunities Qualification Using the BANT Methodology under the Fuzzy Set Theory Framework.

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Procedia Computer Science 2024年 246卷 1271-1280页

作者： Marcus Vinicius Leite Jair Minoro Abe Marcos Leandro Hoffmann Souza Graduate Program in Production Engineering-Paulista University-UNIP Rua Dr. Bacelar 1212-São Paulo-SP-04026002 Brazil Graduate Program in Applied Computing-Vale do Rio dos Sinos University-UNISINOS Av. Unisinos 950 - São Leopoldo-RS-93022-000- Brazil

Demand generation is crucial for organizations, supplying sales teams with well-qualified commercial opportunities. Despite the wide variety of existing opportunity qualification methodologies, the subjective nature of experts’ final evaluation remains an obstacle to efficiency and productivity in the business process. This research investigated how Fuzzy Set Theory and Fuzzy Logic could be applied to the BANT methodology for qualifying commercial opportunities, aiming to replace these deliberative evaluations by experts to increase the sales cycle performance. A fuzzy inference system was developed to emulate the assessments of the experts. The analysis of the ratings obtained after processing a sample of commercial opportunities from 2022 and 2023 confirmed the system’s effectiveness in aligning with expert perceptions. While the study indicated room for refinements in the model, the findings underscore the potential to streamline the qualification of opportunities and improve sales cycle performance.

关键词： Fuzzy Set Theory Fuzzy Logic Decision Making Commercial Opportunity Qualification BANT Methodology Sales Force Support Commercial Process Optimization

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Multivariate Time-Series Deep Learning for Joint Prediction of Temperature and Relative Humidity in a Closed Space 8

Multivariate Time-Series Deep Learning for Joint Prediction ...

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8th International Conference on Computer Science and Computational Intelligence, ICCSCI 2023

作者： Gunawan, Fergianto E. Budiman, Arief S. Pardamean, Bens Juana, Endang Romeli, Sugiarto Cenggoro, Tjeng W. Purwandari, Kartika Hidayat, Alam A. Redi, Anak A.N.P. Asrol, Muhammad Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia PT Impack Pratama Industri Jakarta14350 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia

An accurate predictive model of temperature and humidity plays a vital role in many industrial processes that utilize a closed space such as in agriculture and building management. With the exceptional performance of deep learning on time-series data, developing a predictive temperature and humidity model with deep learning is propitious. In this study, we demonstrated that deep learning models with multivariate time-series data produce remarkable performance for temperature and relative humidity prediction in a closed space. In detail, all deep learning models that we developed in this study achieve almost perfect performance with an R value over 0.99. © 2023 The Authors. Published by Elsevier B.V.

关键词： closed space deep learning humity prediction indoor temperature prediction

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First Demonstration of HZO-LNOI Integrated Ferroelectric Electro-Optic Modulator and Memory to Enable Reconfigurable Photonic Systems

First Demonstration of HZO-LNOI Integrated Ferroelectric Ele...

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2023 International Electron Devices Meeting, IEDM 2023

作者： Xu, Zefeng Chen, Chun-Kuei Lin, Hong-Lin Gao, Yuan Ke, Wei Xu, Baochang Dmitriev, Pavel Arbiz, Carlan Zamburg, Evgeny Touzard, Steven Cai, Xinlun Lee, James Venkatesan, Suresh Danner, Aaron Thean, Aaron Voon-Yew Department of Electrical and Computer Engineering Singapore Nus Graduate School Integrative Sciences and Engineering Program Singapore 117583 Singapore School of Electronics and Information Technology 117583 Singapore Centre for Quantum Technologies Nus Singapore Poet Technologies Canada Sun Yat-Sen University 510275 China

ISBN: (纸本)9798350327670

We have successfully demonstrated, for the first time, an innovative back-end-of-line (BEOL) compatible electro-optic modulator and memory (EOMM) based on Lithium Niobate on Insulator (LNOI) micro-ring resonator (MRR) integrated with Ferroelectric Hafnium Zirconate Hf0.5Zr0.5O (HZO) non-volatile analog memory. High non-volatile memory and modulation performances are both achieved in a single compact device, exhibiting high extinction ratio of 13.3 dB, excellent efficiency of 66pm/V, stable nine-state switching, record-high endurance exceeding 109 cycles. This is accomplished by utilizing Pockels effect in LNOI, induced by electric-field effect from remnant HZO ferroelectric polarization. We studied the system implementation of reconfigurable chiplet-interposer photonic interconnect, enabled by the EOMM and EOMM with hybrid thermal-optical modulation. Our model shows a potential 70% energy efficiency improvement over conventional electrical interposer interconnect. We have also tested the integration of the EOMM with POET technologies' 400G Tx/Rx optical interposer chip and studied a limited scale demonstration of the EOMM device. © 2023 IEEE.

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Basal and Edge Plane Activity of Two-Dimensional Dirac Semimetal Nite2 for Hydrogen Evolution Reaction

SSRN

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SSRN 2025年

作者： Cho, Suyeon Jeong, Seung Weon Kim, Jeong Hyo Lee, Seungyeon Yang, Heejun Lee, Sangheon Division of Chemical Engineering and Materials Science Graduate Program in System Health Science and Engineering Ewha Womans University Seoul03760 Korea Republic of Daejeon34141 Korea Republic of

. Nickel ditelluride (NiTe2), one of group-10 transition metal dichalcogenides, has shown intriguing surface states originating from its topological semi-metallicity. Here, we demonstrate abnormal catalytic activities at the NiTe2 surface for hydrogen evolution reaction (HER). We investigate the differences in catalytic activities at the basal and edge planes of NiTe2 using a micro-sized electrochemical reactor. The basal plane is found to be more active than the edge plane, resulting in a current density at the basal plane of NiTe2 exceeding 800 mA/cm2 with a small overpotential of -0.162 V. We conduct ab initio calculations to estimate the intrinsic catalytic activities of HER on the basal and edge planes of NiTe2. Interestingly, our calculation results suggest that the active sites at the edge plane are electrochemically more active than those at the basal plane. The discrepancy between the experimental measurements and theoretical predictions for the crystal-orientation-dependent HER activity highlights that the specialty of a topological semimetal plays a vital role in determining the HER rate for NiTe2 nanoparticle catalysts © 2025, The Authors. All rights reserved.

关键词： Hydrogen evolution reaction

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Multi-task Learning Graph Neural Networks for Cancer Prognosis Prediction with Genomic Data

Multi-task Learning Graph Neural Networks for Cancer Prognos...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Tsung-Wei Lin Sofia Ormazabal Arriagada Che Lin Graduate Institute of Communication Engineering National Taiwan University (NTU) Taiwan International Graduate Program AIoT NTU Research Center for Information Technology Innovation Academia Sinica Department of Electrical Engineering NTU Center for Advanced Computing and Imaging in Biomedicine NTU Smart Medicine and Health Informatics Program NTU

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

Providing robust prognosis predictions for cancers with limited data samples remains a challenge for precision oncology. In this study, we propose a novel approach that combines multi-task learning (MTL) and graph neural networks (GNNs) to address this issue. By representing gene-gene interactions as a graph network, our approach leverages multi-task learning to effectively capture the relationships of genes relevant to the oncogenesis and progression of breast, lung, and colon cancer. We demonstrate that our approach improves the cancer prognosis prediction for cancers with fewer samples, such as colon adenocarcinoma, by leveraging the shared gene-gene interactions across different cancer types, obtaining increases in the area under the precision-recall curve (AUPRC) of 24%. Our work contributes to the field of smart healthcare by demonstrating the potential of MTL and GNNs for enhancing cancer prognosis prediction, even with limited data samples.

关键词： Lungs Genomics Medical services Colorectal cancer Breast Multitasking Oncology Graph neural networks Prognostics and health management Cancer

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Improvıng Maternal Health Servıces in Remote Rural Areas: Through the Use of Geographıc Informatıon System Technology 8th

Improvıng Maternal Health Servıces in Remote Rural Areas: ...

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8th International Congress on Information and Communication Technology, ICICT 2023

作者： Dewi, Arlina Supriyatiningsih Sundari, Sri Nursetiawan Master of Hospital Administration Faculty of Post Graduate Program Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia Obstetrics and Gynecology Faculty of Medicine and Health Sciences Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia School of Medicine Faculty of Medicine and Health Sciences Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia Civil Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia

ISBN: (纸本)9789819932351

Indonesia’s high Maternal Mortality Rate (MMR) and İnfant Mortality Rate (IMR) are major health concerns. In Indonesia’s 2020, MMR was 199/100,000 live births, exceeding the 2015–2030 global target of 70/100,000. Geographic Information Systems (GISs) maternal and infant health are useful in mapping and evaluating pregnant women’s locations to determine health facility access. This study aimed to describe the use of GIS to map pregnant women, risky pregnant women, and the distance to the nearest health facility in a remote rural Indonesian area. The study used descriptive quantitative surveying. This study focused on rural pregnant women in Bulukumba, South Sulawesi. The sampling method used the total population. This study uses ArcGIS to find coordinates points using latitude and longitude points. Descriptive analysis to be used maps pregnant women’s risk of accessing health facilities. Results this research, using GIS to map pregnant women, especially high-risk ones, to shelters and health facilities found 47.7% have a risk of pregnancy, 34.9% get to the hospital in 50–60 min, and 1.1% above 60 min. GIS mapping in rural pregnant women can monitor high-risk pregnancies, but it must be enhanced continuously. GIS in health, especially for mothers and children, can help the government present health equality policies by estimating distance and time to access health facilities, especially in specific geographic locations, with decreased MMR and improving maternal and child health. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Rural areas

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Preferences in Construction Workers Selection to a Project Team: A Conjoint Analysis Approach 24

Preferences in Construction Workers Selection to a Project T...

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6th International Conference on Management Science and Industrial engineering, MSIE 2024

作者： Bonete, Lorenz Ian B. Prasetyo, Yogi Tri Ahmed, Nagib Ismail Cahigas, Maela Madel L. Nadlifatin, Reny Ayuwati, Irene Dyah School of Industrial Engineering and Engineering Management Mapúa University Manila Philippines School of Graduate Studies Mapúa University Manila Philippines International Bachelor Program in Engineering Yuan Ze University Chung-Li Taiwan Department of Industrial Engineering and Management Yuan Ze University Chung-Li Taiwan Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia University of Surabaya Surabaya60284 Indonesia

ISBN: (纸本)9798400717130

Construction teams are responsible for building complex projects within the allotted budget, time and expected quality. Thus, team members must be able to work with each other to avoid any complications during the construction process. As such, team supervisors must select from a pool of applicants or from their current roster of workers, which would be composed of different personalities and capabilities. This paper aims to identify the preferences of team supervisors when building up their team using conjoin analysis. The study found out that supervisors would like to have workers that respects and values their work and can work harmoniously with others. This study is beneficial for the human resource department of construction companies when recruiting workers, for the management when trying to develop their current personnel and for the workers who are trying to improve themselves. © 2024 ACM.

关键词： Supervisory personnel

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Tomato Leaf Disease Classification with Image Augmentation Methods

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Transactions of the Korean Institute of Electrical Engineers 2021年第1期70卷 184-189页

作者： Ham, Hyun-Sik Cho, Hyun-Chong Dept. of Electronics Engineering Kangwon National University Korea Republic of Dept. of Electronics Engineering and Interdisciplinary Graduate Program for Bit Medical Convergence Kangwon National University Korea Republic of

The tomato is one of important crops in the world market with high commercial value. The early detection of disease is crucial for an successful crop yield. Many studies have recently been conducted to identify plant disease. In this paper, tomato disease classification using leaf images is proposed. Using the convolutional neural network(CNN), the features of disease are extracted and learned to classify. Data augmentation methods, Google's AutoAugment algorithm and GAN(Generative Adversarial Networks), are used to increase tomato disease data. The classification model classifies nine classes of tomato disease. We compared the original model with the data augmentation models and explored that the classification that produced good performance. As a result, the SVHN policy of AutoAugment model achieved F1 Score 0.945. © 2021 Korean Institute of Electrical Engineers. All rights reserved.

关键词： Generative adversarial networks

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Design and Implementation of Decisioning System for Wifi Access Point Installation using Genetic Algorithm

Design and Implementation of Decisioning System for Wifi Acc...

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2022 International Electrical engineering Congress, iEECON 2022

作者： Thitinaruemit, Aphirak Sitjongsataporn, Suchada Prongnuch, Sethakarn Mahanakorn University of Technology Electrical Engineering Graduate Program Faculty of Engineering and Technology Bangkok Thailand Faculty of Engineering and Technology Dept. of Electronic Engineering Bangkok Thailand Suan Sunandha Rajabhat University Faculty of Industrial Technology Dept. of Robotics Engineering Bangkok Thailand

ISBN: (纸本)9781665402064

This paper presents the design and implementation of a WiFi indoor localization system using genetic algorithm. The coverage capability of the wireless access point is an important parameter in the design to estimate the distance from the transmitted and received signals. The main purpose of this work is to find the effective number of wireless access points in the design area by using genetic algorithm. The Received Signal Strength (RSSI) is measured for the signal quality. The test area consists of the multiple classrooms on the same floor inside the building and the conditions are unobstructed and used the line-of-sight for transmitted and received signals. The experimental results by measuring the received signal through a laptop are indicated that RSSI = -35 dBm at a distance of 5 meters is a prominent indicator of signal quality that can be used to search a variety of information from internet inside the classroom. © 2022 IEEE.

关键词： Genetic algorithms

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