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Automatic deterioration Evaluation Technique to Improve the Efficiency of Manhole Inspection

NTT Technical review 2023年第1期16卷

作者： Furukawa, Takayuki Saito, Chihiro Okutsu, Masaru Takahashi, Hiroyuki Nakagawa, Masafumi Yanagi, Shuichi Civil Engineering Project NTT Access Network Service Systems Laboratories Japan R&D Promotion Research and Planning Department NTT Japan Civil System Project NTT Access Network Service Systems Laboratories Japan

We have developed a non-entry manhole inspection technique with a function for automatic deterioration judgment. This enables workers to operate safely without having to enter manholes and can eliminate the need to drain manholes, substantially reducing the inspection workload. This technique not only improves the safety and efficiency of manhole inspections but also yields high-resolution inspection images that can be used to accurately predict the deterioration of facilities. It can therefore play an important role in improving the maintenance cycle. © 2023 Nippon Telegraph and Telephone Corp.. All rights reserved.

关键词： Inspection

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Establishing a Certification system for the Field Project of Outdoor Battery Energy Storage system

Establishing a Certification System for the Field Project of...

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Power, Energy and Electrical Engineering (CPEEE), International Conference on

作者： Wei-Shan Lin Liang-Yang Lin Pei-Jen Wang Wei-Hung Wu Chung-Hsien Chen Ching-Hua Lin Department of Power Mechanical Engineering National Tsing Hua University Hsinchu Taiwan Inspection Technology Division Bureau of Standards Metrology and Inspection MOEA Taipei Taiwan Intelligence and System R&D Service Department Metal Industries Research & Development Centre Taichung Taiwan Metrology Section Hsinchu Branch Bureau of Standards Metrology and Inspection MOEA Hsinchu Taiwan

ISBN: (数字)9798331520090

ISBN: (纸本)9798331520106

Taiwan actively promotes energy transformation and net zero emissions. Generating 15.1% of energy using renewable sources by 2025 and reducing net zero emissions by 2050 is a goal set by Taiwan. Solar, Wind, and other renewable energy sources will be built on a large scale. The intermittent supply features of renewable energy will affect the traditional power grid. An energy storage system is a key technology to reduce the influence of intermittent renewable energy on the power grid, it can solve the problem of integrating renewable energy with the power grid on a large scale. Currently, the technological development of energy storage systems shows a diverse trend. In Taiwan, an energy storage system with a lithium battery is the first choice for most enterprises. Therefore, a certification system for outdoor battery energy storage system field project is proposed in this research for the outdoor grid-integrated energy storage system. This certification system adopts a three-stage certification method, including a design review before construction, field certification after completion, and regular test every two years. It guarantees the safety of the energy storage system and its related equipment. It facilitates the energy storage system industry's development and renewable energy policies.

关键词： renewable energy sources reviews Battery energy storage system Net zero Lithium batteries Power grids Safety Certification Standards Energy storage

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The Frontier of Geospatial AI deep Learning Applications in data Mining and Spatial Analysis

The Frontier of Geospatial AI Deep Learning Applications in ...

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2024 IEEE International Conference on Intelligent systems and Advanced Applications, ICISAA 2024

作者： Mishra, Ajit Kumar Verma, Vikash Manivannan, r. Kumar, N. Krishna Srividya, Mudunuru Sharma, Sanskriti IES College of Technology Department of Electrical & Electronics Engineering M.P Bhopal462044 India GGITS Dept of Artificial Intelligence & Machine Learning M.P Jabalpur India Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology School of Computing Computer Science & Engineering TN Chennai India Guru Nanak Institutions Technical Campus Ibrahimpatam Dept.of CSE Telangana Hyderabad India MLR Institute of Technology Dept. of CSE Telangana Hyderabad India GGITS Dept of Computer Science & Business System M.P Jabalpur India

ISBN: (纸本)9798331539948

Modern artificial intelligence uses geographical data mining and regional analysis to analyze large datasets. deep learning is a new geographic AI method. Example: Geographic deep Mining Network (GdMN). The Spatial Feature Extractor (SFE), Temporal Geospatial Attention Mechanism (TGAM), and Geospatial data Fusion Module (GdFM) comprise this technique. We examined six popular approaches and found GdMN performed best. It worked successfully for several reasons. GdMN always outperforms its competitors in memory, F1 score, IoU, training time, and inference time. This is always true. These findings suggest that GdMN might boost geospatial AI's data mining and location analysis abilities. After all the effort, we have developed a solid basis for location intelligence, making it useful in various subject areas. Because it's versatile, mapping specialists may use GdMN for better environmental monitoring or city development. deep learning helps GdMN make better space choices and uncover insights in large, challenging data sets that no one knew about. GdMN's cutting-edge approaches make space and time research and prediction simpler. This wide perspective offers a more full and all-encompassing picture of today's challenges than previous techniques. This makes it impossible to overstate how significant this work is to location intelligence. Its unmatched research and insights usher in a new era. © 2024 IEEE.

关键词： Adversarial machine learning

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Optimization of 2.2d Underfill Process by Novel Methodology and direct Observation of Capillary Underfill Process

Optimization of 2.2D Underfill Process by Novel Methodology ...

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Electronic Components and Technology Conference (ECTC)

作者： Chia-Peng Sun Yu-En Liang dyi-Chung Hu Er-Hao Chen Jeffrey ChangBing Lee Srikar Vallury Product R&D Division CoreTech System (Moldex3D) Zhubei City Taiwan R.O.C. CEO SiPlus Co. Hsinchu Taiwan R.O.C. CEO Department SiPlus Co. Hsinchu Taiwan R.O.C. Global Engineering Development Division Integrated Service Technology Inc Hsinchu Taiwan R.O.C. Moldex3D North America Inc. Detroit United States

The process of capillary underfill encapsulation encounters productivity issue of long filling time that draws additional manufacturing costs. Since the chip size becomes larger, multiple passes are required for fill and fillet passes to fill up the cavity and create the sealing joint. Traditionally, to obtain an adequate dispensing design (pass route and order) for the capillary process to fill up the package without obvious voids, a long waiting time between passes is set to ensure that the underfill moving front for each pass to halts dispensing before the next pass. Based on our direct underfill observation experiments, the underfill dispensing waiting time is unnecessarily too long. In this work, to reduce the cycle time of underfill process without extensive and tedious trial and error, a novel methodology for optimizing dispensing strategy is proposed. A well-validated model-equivalent bump group (EBG) model of 3d CAE modeling for capillary underfill process is applied to predict the optimal waiting time between passes for dispensing design. Moreover, in-situ observation of underfill process experiment is employed to verify the methodology. It shows that when the optimized waiting time for each pass is applied, the propagation of the underfill moving front by EBG model is like that of the experiment with a long waiting time for each pass. This methodology can optimize the underfill process to reduce cost and speed up production time compared to the conventional try and error underfill process.

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Green Ports - Shore Power Supply State of the Art

Green Ports - Shore Power Supply State of the Art

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Mediterranean Electrotechnical Conference (MELECON)

作者： Pedro Costa C. I. Faustino Agreira rui Pestana Y. Cao Coimbra Polytechnic - ISEC Coimbra Portugal Coimbra Portugal Coimbra Polytechnic - ISEC Coimbra Portugal SUScita - Research Group on Sustainability Cities and Urban Intelligence INESC Coimbra Coimbra Portugal System Operator Department REN - Rede Eléctrica Nacional S.A. Sacavém Portugal Centro de Investigação em Energia REN - State Grid S.A R&D Nester Lisbon Portugal

ISBN: (数字)9798350387025

ISBN: (纸本)9798350387032

In a world that is in constant changing and where carbon neutrality becomes a common objective, it is necessary to implement European policies and targets to reduce greenhouse gas emissions. The maritime sector is one of the most polluting in the world, becoming mandatory to implement technologies in port area to reduce their footprint. Most of the good’s transportation are made by sea, the maritime industry is growing, and the biggest chair of greenhouse gas emission comes from shipping. The seaport has the role to implement solutions to reduce the emissions in port area, allowing the ships to shutdown their engines while they are moored in port. renewable energy production alongside with shore power supply systems are becoming a common solution in ports as some of the technologies that allows to reduce ships emissions in port area. This paper presents the state of the art of onshore power supply in ports and standards related to shore power supply and data requirements for load model built and emissions calculations.

关键词： Industries renewable energy sources Power supplies Green products Production Seaports Marine vehicles

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European Ports Transition - A new Approached of a Load Model, Consumption Integration of renewable Energy Sources and Energy Storage systems Profiles

European Ports Transition - A new Approached of a Load Model...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Pedro Costa C. I. Faustino Agreira rui Pestana Y. Cao Rua da Misericórdia Lagar dos Cortiços S. Martinho do Bispo Polytechnic University of Coimbra Coimbra Portugal Portugal SUScita - Research Group on Sustainability Cities and Urban Intelligence INESC Coimbra Coimbra Portugal System Operator Department REN - Rede Eléctrica Nacional S.A. Sacavém Portugal Centro de Investigação em Energia REN - State Grid S.A R&D Nester Lisbon Portugal

ISBN: (数字)9798331541606

ISBN: (纸本)9798331541613

Carbon neutralization is a European concern, which is why the maritime sector should implement strategies to reduce greenhouse gas (GHG) emissions, particularly in port areas. The Port of Sines, a very important maritime hub in Portugal, is in a stage of significant expansion including new terminal constructions and renewable energy projects, which amplify its energy demands. This paper presents a new approached of a load model, consumption Integration of renewable energy sources and energy storage systems for the Port of Sines, analysing a global hourly energy consumption in two months of 2023. Using a Software Package MATLAB, the details of the consumption profiles of all ships and terminals in order to identify periods of peak demand, the information on the integration of renewable energy sources and energy storage systems, will be studied and analysed. due to the increase in maritime traffic and the use of potential Onshore Power Supply systems (OPS) to reduce emissions, in this study a new energy requirements will be analysed. This new model will be as a step for optimizing the port’s electrical infrastructure, enhancing energy efficiency, and supporting sustainable growth. Finally, some conclusions that provide a valuable contribution to the understanding of the Portuguese Ports, aims to provide a critical study of the load model to be taken, into account when managing port energy demand and advancing environmental goals are pointed out.

关键词： renewable energy sources Energy consumption Software packages Power supplies Europe Seaports Propulsion Mathematical models Load modeling Energy storage

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rehabilitation service Needs and Preferences among Veterans with Tinnitus: A Qualitative Study

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Seminars in Hearing 2023年第1期45卷 029-039页

作者： Khaya d. Clark Tara Zaugg Susan deFrancesco Christine Kaelin James A. Henry Kathleen F. Carlson VA Rehabilitation Research & Development Service National Center for Rehabilitative Auditory Research VA Portland Health Care System (P5-NCRAR) Portland Oregon Department of Medical Informatics and Clinical Epidemiology Oregon Health and Science University Oregon Health and Science University Portland Oregon Department of Defense Hearing Center of Excellence San Antonio Texas VA Health Services Research & Development Service Center of Innovation Center to Improve Veteran Involvement in Care VA Portland Health Care System (R&D 66) Portland Oregon Oregon Health and Science University – Portland State University School of Public Health Oregon Health and Science University Portland Oregon Department of Otolaryngology – Head and Neck Surgery School of Medicine Oregon Health & Science University Portland Oregon

Tinnitus is prevalent among military Veterans, yet there is a gap between the demand and the provision of services for tinnitus rehabilitation services within the Veterans Health Administration (VHA). We sought to understand tinnitus rehabilitation service needs and preferences among Veterans with bothersome tinnitus who use Veterans Affairs (VA) services. We conducted semistructured telephone interviews in 2019 with Veterans diagnosed with tinnitus, who reported it as bothersome. Veterans were purposively sampled to represent national VA users, with and without comorbid traumatic brain injury (TBI), and who were or were not interested in tinnitus rehabilitation services. Qualitative data were analyzed using a modified grounded theory approach. Among 40 Veterans interviewed (32 men, 8 women; 50% with TBI), 72.5% endorsed being somewhat/very likely to be interested in tinnitus rehabilitation services while 27.5% were very/somewhat unlikely. Themes related to Veterans' interest in tinnitus rehabilitation services included barriers and facilitators to participation and preferences for receiving tinnitus services (e.g., individual vs. group-based; in-person vs. remote access). Our findings highlight factors that influence Veterans' reported need and preferences for, and readiness to engage in, rehabilitation services for tinnitus. Personalized or otherwise adaptable approaches to program delivery may help ensure maximal uptake among Veterans.

关键词： audiology auditory rehabilitation hearing healthcare tinnitus veterans

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Novel Biodegradable Ca–P/Ti–F Composite Conversion Coatings for Improving the Corrosion resistance of Medical Magnesium Materials

SSRN

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SSrN 2024年

作者： Sun, Ying-Sui Chu, Peng-Wei Cheng, An-Yu You, Jhu-Lin Chang, Tsung-Ming Jian, Shun-Yi Chi, Chun-Shang Liu, Yu-Cheng Chang, Chin-Jou School of Dental Technology College of Oral Medicine Taipei Medical University Taipei Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu300044 Taiwan Department of Chemical & Materials Engineering Chung Cheng Institute of Technology National Defense University Taoyuan335 Taiwan System Engineering and Technology Program National Chiao Tung University Hsinchu300 Taiwan Department of Material Engineering Ming Chi University of Technology New Taipei City24301 Taiwan Center for Plasma and Thin Film Technology Ming Chi University of Technology New Taipei243303 Taiwan Combination Medical Device Technology Division Medical Devices R&D Service Department Metal Industries Research & Development Centre Kaohsiung802 Taiwan

Mg and its alloys are characterized by favorable biocompatibility and nontoxicity, and these properties have stimulated considerable research interest in their application as degradable biomaterials for medical implants. However, the clinical application of these materials is restricted by their rapid degradation. Therefore, this study designed a surface modification method for Mg and Mg alloys to enable them to satisfy clinical requirements. A two-step conversion coating method was applied to pure Mg. Pure Mg samples were first coated with calcium phosphate (Ca–P), following which they were coated with titanium fluoride (Ti–F), resulting in the production of Mg samples coated with a bioactive Ca–P/Ti–F composite. The composition of the coated samples was investigated through energy-dispersive X-ray spectroscopy with transmission electron microscopy, and their morphology was characterized through scanning electron microscopy. Moreover, hydrogen evolution measurements in simulated body fluid (SBF), electrochemical impedance spectroscopy, and polarization curves were employed to evaluate the samples’ corrosion resistance. The prepared composite conversion coatings had an average thickness of approximately 350 nm, and their corroded area was less than 5% of their total area following their immersion in SBF for 72 h. Thus, the prepared Ca–P/Ti–F composite conversion coatings effectively inhibited Mg corrosion in SBF. Moreover, the attachment and differentiation of MG-63 cells on the prepared coatings were observed. © 2024, The Authors. All rights reserved.

关键词： Energy dispersive spectroscopy

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Smart Class on Android: A Handy Classroom Scheduling Solution

Smart Class on Android: A Handy Classroom Scheduling Solutio...

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Next Generation Communication & Information Processing (INCIP), International Conference on

作者： Vishnuraja Palanisamy M. Thiyagarajan r. Bhavani Arun Anthonisamy K. Manivannan S. Vaishnavi Department of Artificial Intelligence and Data Science Builders Engineering College Kangeyam Tamil Nadu India Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai Tamil Nadu India Department of Electronics and Communication Engineering K. Ramakrishnan College of Technology Trichy Tamil Nadu India Department of Computer Science and Business System Panimalar Engineering College Chennai Tamil Nadu India Department of Information Science and Engineering School of Computer Science & Engineering JAIN (Deemed-to-be) University Bengaluru Karnataka India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education (MAHE) Manipal India

ISBN: (数字)9798331528140

ISBN: (纸本)9798331528157

Classroom scheduling is vital but difficult for educational institutions, especially those with large student populations and diverse needs. Traditional methods using outdated software or manual processes often cause inefficiencies, disagreements, and administrative workload. In low-resource regions without access to cutting-edge technology and infrastructure, these issues are severe. This paper introduces Android-based SmartClass Mobile to transform classroom scheduling. The program's SOA-based functionality offers flexibility, adaptability, and integration with institution-specific procedures. The Heuristic algorithm and Solution Space Navigation (SSN) tackle scheduling problems such as room availability, multimedia needs, and seating capacities. SSN dynamically resolves conflicts by exploring alternate configurations, while the Heuristic Algorithm assigns time slots and classrooms depending on availability and priority. SmartClass Mobile analysis indicates benefits. The solution reduces conflicts, increases user satisfaction, and decreases scheduling time by 50% compared to manual methods with 85% test user approval. due to its mobile-first approach, the initiative is open to urban and rural institutions. dependence on internet access for some functions is a downside, especially in resource-constrained contexts. The findings suggest that SmartClass Mobile provides a scalable, effective, and simple classroom scheduling solution. Mobile technology, advanced algorithms, and SOA concepts make it valuable for school administrators. Additions like AI and machine learning will boost its potential.

关键词： Navigation Heuristic algorithms Software algorithms Manuals Transforms Scheduling Software real-time systems Mobile applications reliability

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The Frontier of Geospatial AI deep Learning Applications in data Mining and Spatial Analysis

The Frontier of Geospatial AI Deep Learning Applications in ...

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Intelligent systems and Advanced Applications (ICISAA), International Conference on

作者： Ajit Kumar Mishra Vikash Verma r. Manivannan N. Krishna Kumar Mudunuru Srividya Sanskriti Sharma Department of Electrical & Electronics Engineering IES College of Technology Bhopal M.P India Dept of Artificial Intelligence & Machine Learning GGITS Jabalpur M.P India School of Computing Computer Science & Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai TN India Dept.of CSE Guru Nanak Institutions Technical Campus Ibrahimpatam Hyderabad Telangana India Dept. of CSE MLR Institute of Technology Hyderabad Telangana India Dept of Computer Science & Business System GGITS Jabalpur M.P India

ISBN: (数字)9798331539948

ISBN: (纸本)9798331539955

Modern artificial intelligence uses geographical data mining and regional analysis to analyze large datasets. deep learning is a new geographic AI method. Example: Geographic deep Mining Network (GdMN). The Spatial Feature Extractor (SFE), Temporal Geospatial Attention Mechanism (TGAM), and Geospatial data Fusion Module (GdFM) comprise this technique. We examined six popular approaches and found GdMN performed best. It worked successfully for several reasons. GdMN always outperforms its competitors in memory, F1 score, IoU, training time, and inference time. This is always true. These findings suggest that GdMN might boost geospatial AI’s data mining and location analysis abilities. After all the effort, we have developed a solid basis for location intelligence, making it useful in various subject areas. Because it’s versatile, mapping specialists may use GdMN for better environmental monitoring or city development. deep learning helps GdMN make better space choices and uncover insights in large, challenging data sets that no one knew about. GdMN’s cutting-edge approaches make space and time research and prediction simpler. This wide perspective offers a more full and all-encompassing picture of today’s challenges than previous techniques. This makes it impossible to overstate how significant this work is to location intelligence. Its unmatched research and insights usher in a new era.

关键词： deep learning Training Urban areas Transforms Feature extraction Solids Spatial databases Geospatial analysis data mining Artificial intelligence

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