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

作者： Bitew, Mekuanint Agegnehu Muhammad, Akbareza Fandiantoro, Dion Hayu Boedinoegroho, Hany Kurniawan, Arief Bahir Dar Institute of Technology Bahir Dar University Faculty of Computing Bahir Dar Ethiopia Institut Teknologi Sepuluh Nopember Department of Computer Engineering Surabaya Indonesia

ISBN: (纸本)9781728182834

Electronic money payment for public transportation uses cards or tags as the transaction media. The system is known as Check-In/Check-Out, which requires the owner of the card/tag to do an action of taking out the card to be scanned. This system has a deficiency in terms of time. Some of the existing public transportation systems can accommodate the passenger to obtain the location of the public transport itself, yet it is still unable to Figure the number of passengers that have already been inside the public transport. Therefore, this research's purpose is to make a public transportation system that uses Bluetooth Low Energy based device as a transmitter which implements the Be-In/Be-Out System that will be carried by the passenger. As a result, it's unessential for the passenger to do specific actions when riding public transport. They can also obtain the number of passengers inside public transport before riding it. © 2020 IEEE.

关键词： Bluetooth

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QSRP: Efficient Reverse k-Ranks Query Processing on High-Dimensional Embeddings 40

QSRP: Efficient Reverse k-Ranks Query Processing on High-Dim...

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Bian, Zheng Yan, Xiao Zhang, Jiahao Yiu, Man Lung Tang, Bo The Hong Kong Polytechnic University Department of Computing Hong Kong Southern University of Science and Technology Department of Computer Science and Engineering China Huawei Technologies Co. Ltd. China

ISBN: (纸本)9798350317152

Embedding models represent users and products as high-dimensional embedding vectors and are widely used for recommendation. In this paper, we study the reverse k-ranks query, which finds the users that are the most interested in a product and has many applications including product promotion, targeted advertising, and market analysis. As reverse k-ranks solutions for low dimensionality (e.g., trees) fail for the high-dimensional embeddings generated by embedding models, we propose the QSRP framework. QSRP precomputes the score table between all user and product embeddings to facilitate pruning and refinement at query time. As the score table is usually large, QSRP samples some of its columns as the index to fit in memory. To tackle the problem that naive uniform sampling results in poor pruning effect, we propose query-aware sampling, which conducts sampling by explicitly maximizing the pruning effect for a set of sample queries. Moreover, we introduce regression-based pruning, which fits cheap linear functions to predict the bounds used for pruning. We also design techniques to build the index with limited memory, reduce index building time, and handle updates. We evaluate QSRP under various configurations and compare with state-of-the-art baselines. The results show that QSRP achieves shorter query time than the baselines in all cases, and the speedup is usually over 100x. © 2024 IEEE.

关键词： Embeddings

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Testing the scalability of SaaS applications

Testing the scalability of SaaS applications

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2011 IEEE International Conference on Service-Oriented computing and Applications, SOCA 2011

作者： Tsai, Wei-Tek Huang, Yu Shao, Qihong School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ United States Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781467303194

Cloud computing and SaaS (Software-as-a-Service) received significant attention recently. Testing SaaS applications is important because many mission-critical applications will be deployed on the cloud. However, to the best of our knowledge, testing framework designed specifically for SaaS applications is not developed. The issue of testing the scalability of SaaS applications remains untouched. This paper discusses the unique features and challenges in testing SaaS applications, and proposes scalability metrics that can be used to test the scalability of SaaS applications. © 2011 IEEE.

关键词： Scalability

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Towards a scalable and robust multi-tenancy SaaS 10

Towards a scalable and robust multi-tenancy SaaS

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Proceedings of the Second Asia-Pacific Symposium on Internetware

作者： Tsai, Wei-Tek Shao, Qihong Huang, Yu Bai, Xiaoying School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ United States Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781450306942

Software-as-as-Service (SaaS) is a new approach for developing software, and it is characterized by its multi-tenancy architecture and its ability to provide flexible customization to individual tenant. However, the multi-tenancy architecture and customization requirements have brought up new issues in software, such as database design, database partition, scalability, recovery, and continuous testing. This paper proposes a hybrid test database design to support SaaS customization with two-layer database partitioning. The database is further extended with a new built-in redundancy with ontology so that the SaaS can recover from ontology, data or metadata failures. Furthermore, constraints in metadata can be used either as test cases or policies to support SaaS continuous testing and policy enforcement.

关键词： Metadata

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Novel Technique for Radiation Efficiency Enhancement of Fractal Antennas 1

Novel Technique for Radiation Efficiency Enhancement of Frac...

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1st IEEE Latin American Conference on Antennas and Propagation, LACAP 2024

作者： Gurgel, Nathan Barros, Tales Queiroz, Idalmir Fontgalland, Glauco Ravelo, Blaise Federal University of Campina Grande Electrical Enginering and Computation Department Campina Grande Brazil Federal Rural University of Semi Arid Department of Engineering and Technology Mossoro Brazil University of Mount Union Electrical & Computing Engineering Department OH United States Nanjing University of Information Science and Technology School of Electronic & Information Engineering Nanjing China

ISBN: (纸本)9798331527587

Fractality is a well stablished method for antenna miniaturization with a myriad of papers covering fractals, quasi fractals, implementations and so. Even though, they find fewer practical applications due to its downgrade on the radiation efficiency when compared to the base form in which the fractal is applied. In this paper, we cover a "smoothing"technique to optimize the radiation efficiency of a 3.5 GHz 2nd Order Square Fractal. When compared to the fractal one, the smoothed fractal radiation efficiency is enhanced by 3% absolute, and the max gain goes from 4.92dB to 5.18dB. Moreover, the smoothed fractal antenna occupies the same effective area of the unsmoothed version and is 48% smaller than the base one. More optimizations can be done for higher improvement of the fractal antenna. © 2024 IEEE.

关键词： Radiation efficiency

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DESIGNING AN INTEGRATED MULTI-ECHELON, MULTI-PERIOD HEALTHCARE SUPPLY CHAIN NETWORK 51

DESIGNING AN INTEGRATED MULTI-ECHELON, MULTI-PERIOD HEALTHCA...

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51st International Conference on Computers and Industrial engineering, CIE 2024

作者： Rahman, Rafat Sultana, Farzana Farhan, Mahmudur Rahman Ahmed, Sayem Chakrabortty, Ripon K. Department of Mechanical & Production Engineering Ahsanullah University of Science & Technology Dhaka Bangladesh School of Systems & Computing University of New South Wales CanberraACT2610 Australia

The healthcare sector faces unique supply chain management challenges because of the wide range of product life cycles, growing levels of outsourcing, and globalization. Selecting cooperators and forming alliances across different supply chain echelons is particularly crucial when designing a multi-echelon network. This study presents a mixed-integer linear programming (MILP) model to design a multi-echelon, multi-period healthcare supply chain network (HSCN) in the context of a developing country. The model aims to improve operational efficiency and cost-effectiveness by selecting optimal partners, production planning, and inventory control at each echelon. The results demonstrate that the proposed model achieves a 100% customer service level (CSL), ensuring that all demands are met without shortages. Additionally, the model minimizes the total supply chain costs, which are determined to be $183,329, while maintaining a low average inventory level of 9 units across all nodes. These findings underscore the effectiveness of the model in optimizing strategic, tactical, and operational planning for a highly efficient and competent healthcare supply chain. Finally, a 23 factorial experimental design is carried out, considering demand variability, capacity variability for selected partners, and transportation capacity variability as the main factors. Among these factors, demand variability has the largest positive effect on total cost, while both partner capacity variability and transportation capacity variability have negative effects on total cost. This framework offers valuable insights for decision-makers and provides the foundation for future research to explore more complex scenarios. © 2024 Computers and Industrial engineering. All rights reserved.

关键词： Decision making

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The Design of a Specialised Processor for the Simulation of Sintering

The Design of a Specialised Processor for the Simulation of ...

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22nd EUROMICRO Conference on Beyond 2000: Hardware and Software Design Strategies, EUROMICRO 1996

作者： Postula, Adam Abramson, David Logothetis, Paul Department of Electrical and Computer Engineering University of Queensland BrisbaneQLD Australia School of Computing and Information Technology Griffith University Kessels Rd BrisbaneQLD4111 Australia

This paper presents the design decisions encountered during the development of a specialised processor for the Monte-Carlo simulation of metallurgical sintering. Several possible architectures are presented. We show that such a specialised processor using commercially available gate array technology can solve the same problem more than 100 times faster than a modern high-end workstation. Even using slower FPGAs it is possible to achieve a speedup of over 50 times faster than a workstation, which supports the concept of programmable special purpose computers attached to general purpose machines. A prototype of the processor is now being built using Xilinx FPGA and Aptix FPIC switch technology. © 1996 IEEE Proceedings of EUROMICRO-22.

关键词： Sintering

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Impurity explicit optimal Machine learning and statistical perfect construction for air quality prediction 2

Impurity explicit optimal Machine learning and statistical p...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Nareshkumar, R. Shalinikumari, R. Kowsalya, S. Sri Nandhini Vijay Anand, P. Mohamed, Ajmal Gayathri, S. SRM Institute of Science and Technology School of Computing College of Engineering and Technology Department of Networking and Communications Tamilnadu Kattankulathur India Bharath Institute of Higher Education and Research Selaiyur Department of Architecture Tamilnadu Chennai India Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Department of Information Technology Tamilnadu Chennai India CMR Institute of Technology Department of Artificial Intelligence and Data Science Bengaluru India Saveetha School of Engineering Department of Computer Science and Engineering Chennai India K. Ramakrishnan College of Technology Department of Computer Science and Engineering Tamilnadu Trichy India

ISBN: (纸本)9798350365269

The air quality index (AQI) is a metric used to report air quality levels. There has been a substantial rise in the level of air pollution in Indian cities. Multiple methodologies exist for formulating a mathematical equation to ascertain the air quality index. Multiple studies have established a correlation between exposure to air pollution and negative health effects in the general population. The objective of this study is to determine the optimal approach for predicting AQI in order to aid in climate regulation. Nine separate Machine learning (ML) algorithms have been employed in the suggested study to ascertain the AQI. The use of the SMOTE algorithm in the datasets in ML resulted in improved accuracy when comparing the outcomes. Furthermore, all of the implementations have been thoroughly documented using graphs and metrics, which clearly illustrate the differences in outcomes and aid in identifying the specific factors that led to the improvement in accuracy. © 2024 IEEE.

关键词： Machine learning

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Implementing Data Science and Big Data Analytics to Their Full Potential: Protocols for Gaining Useful Understanding and Promoting Data-Driven Innovation 5

Implementing Data Science and Big Data Analytics to Their Fu...

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5th IEEE Global Conference for Advancement in technology, GCAT 2024

作者： Arthy, M. Nivethitha, S.B. Karuppiah, S.P. Vijayanandh, T. Sumalatha, A. Ramesh, T. School of Computing College of Engineering and Technology Department of Data Science and Business Systems Tamil Nadu Kattankulathur India Rajalakshmi Engineering College Mechatronics Engineering Tamil Nadu Chennai India St.Joseph's College of Engineering Department of Mba India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology School of Computing Department of Computer Science & Engineering Tamil Nadu Chennai India Kristu Jayanti College Autonomous Department of Computer Science Bengaluru India R.M.K Engineering College Department of Computer Science & Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350376685

The proper implementation of data science and big data analytics has become an essential component for gaining valuable insight and driving innovation across a variety of industries in this era, which is characterized by the constant presence of data. The strategies and protocols that are necessary to fully exploit the promise of these transformational technologies are investigated in depth by this research. A complete framework for enterprises to harness their data assets is the goal of the study, which will be accomplished by analyzing the fundamental principles of data science as well as the difficulties connected with big data. A number of advanced analytics methods, including machine learning, predictive modeling, and natural language processing, are being investigated as potential integrations into the decision-making process as part of this research. The relevance of data governance, quality, and the ethical considerations that surround data usage are also discussed in this document. It is demonstrated in this study that data-driven insights may lead to strategic advantages, operational efficiencies, and the development of creative goods and services. This is accomplished through a number of case studies and practical examples. In order for businesses to make the most of the potential that are given by data science and big data analytics, it is vital for them to have a culture of data literacy as well as a robust infrastructure, according to the results made. At the end of the study, a collection of best practices and recommendations for businesses and governments to implement in order to cultivate a data-driven environment that encourages innovation and usage of data in a responsible manner are presented. In light of the findings of this study, it is clear that data science and big data analytics require a more comprehensive approach, one that strikes a balance between technological capabilities, organizational readiness, and the influence on society. © 2024

关键词： Big Data Analytics Data Governance Data Infrastructure Data Literacy Data Quality Data Science Data-Driven Decision Making Data-Driven Innovation Ethical Considerations Machine Learning Natural Language Processing Predictive Modeling Strategic Advantage

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PVA-based KOH polymer gel electrolyte as a membrane separator for zinc-air flow battery

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Materials Today: Proceedings 2022年 64卷 1649-1654页

作者： Sankaralingam, Ram Kishore Seshadri, Satyanarayanan Sunarso, Jaka Bhatt, Anand I. Kapoor, Ajay Department of Applied Mechanics Indian Institute of Technology Madras Tamil Nadu Chennai 600036 India Research Centre for Sustainable Technologies Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Campus Sarawak Kuching 93350 Malaysia Faculty of Science Engineering and Technology Swinburne University of Technology Hawthorn VIC 3122 Australia CSIRO Energy Research Way Clayton VIC 3168 Australia Chinmaya Vishwavidyapeeth Veliyanad PO Ernakulam Kerala 682313 India

The anticipated future growth in the electric vehicle market is driving research and development of alternative battery technologies to lithium batteries. Among the explored batteries, metal-air batteries are an exciting option given their high potential energy density. Currently, metal-air flow batteries have received more attention over conventional metal-air batteries due to their ability to reduce metal passivation. The separator for a metal-air flow battery should be both ion-conductive and partially hydrophobic to favour the ionic movement and suppress the electrolyte flooding on the cathode. In this work, we investigate the use of polyvinyl alcohol (PVA)-based potassium hydroxide (KOH) polymer gel electrolyte (KPGE) as a membrane separator for planar zinc-air flow battery (ZAFB). The KPGE samples, i.e., S20 and S33 with respective KOH wt.% of 20 and 33 were synthesised. Their surface morphology, porosity, tensile strength, and ionic conductivity were studied. Among the samples, S33 sample with higher KOH content showed higher ionic conductivity than S20 sample however the tensile strength of S33 sample was lower than the S20 sample. When tested in the battery, ZAFB with S33 sample demonstrated higher nominal voltage and improved polarisation characteristics when compared to the ZAFB with S20 sample. © 2022

关键词： Surface morphology

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