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International Conference on Wireless and Telematics (ICWT)

作者： Cendika Sahid Pratama Muhammad Iqbal Arrachman Muhammad Shafly Nurrasyid Eki Ahmad Zaki Hamidi Ridha Muldina Negara Syaiful Ahdan ratna Mayasari Nana rachmana Syambas School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Electrical Engineering Department UIN Sunan Gunung Djati Bandung Bandung Indonesia School of Electrical Engineering Telkom University Bandung Indonesia Faculty of Engineering & Computer Science Universitas Teknokrat Indonesia Lampung Indonesia

Named Data Networking (NDN) is a newly developing networking method that focuses on information, compared to TCP/IP, which focuses on hosts. This study proposed a solution to the growing complexity of computer networks. The fundamental problem will still be able to be found, one of them being difficulty in accessing a node as data traffic is piling up. One of the solutions is load balancing, which is implementing a system that will redirect packets to different service providers to ease up the load and reduce the number of packets that are dropped due to timeouts. This paper analyses the impact of load balancing in an extreme case emulated environment using Mini-NDN and random load balancing strategy. From the results gathered, implementing random load balancing to the consumer nodes decreases-and in some cases eliminates-dropped packets. In addition, implementing load balancing stabilizes packets' RTT (Round Trip Time) but increases the average RTT compared to using best route forwarding in an unloaded environment.

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Development of a Website-Based Financial Transaction Management System Using Agile with the Scrum Framework

Development of a Website-Based Financial Transaction Managem...

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International Conference on ICT For Smart Society (ICISS)

作者： Ayu Latifah Galih Muhammad ramdan Muhamad Lutfhi Farid Sidik Nadhif Faturrohman Dzikri Nursyaban Agus ramelan Fachrur razy rahman School of Electrical and Informatics Engineering Bandung Institute of Technology Bandung Indonesia Department of Computer Science Institut Teknologi Garut Garut Indonesia Electrical Engineering Departement Universitas Sebelas Maret Solo Indonesia Department of Installation and Electrical Engineering Metal Industry Polytechnic of Morowali Central Sulawesi Indonesia

The process of managing financial transactions, especially in the education sector, is still mostly carried out conventionally, so it has the potential to cause many risks, such as loss or damage to documents related to difficulties in searching for data as needed, transaction processes that take quite a long time, financial records that are not properly recorded. Well, it is prone to discrepancies between the nominal filing and the nominal disbursed conventional representations of financial statements that make the stakeholder evaluation process uncomfortable, and many other things. Therefore this research was conducted to build a website-based information system that can prevent this from happening in the future. The method used in the development of this information system is the Agile method with the Scrum framework. The Scrum framework consists of five stages, starting from Initiate, Plan, and Estimate, Implement, Review and Retrospect, and Release. This website was built using the Javascript programming language using the Vue JS framework for the Front-end. With this website-based application, it is hoped that transaction activities can be carried out better and correctly without being limited by space and time.

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Modern Computing: Vision and Challenges

arXiv

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arXiv 2024年

作者： Gill, Sukhpal Singh Wu, Huaming Patros, Panos Ottaviani, Carlo Arora, Priyansh Pujol, Victor Casamayor Haunschild, David Parlikad, Ajith Kumar Cetinkaya, Oktay Lutfiyya, Hanan Stankovski, Vlado Li, Ruidong Ding, Yuemin Qadir, Junaid Abraham, Ajith Ghosh, Soumya K. Song, Houbing Herbert Sakellariou, Rizos rana, Omer Rodrigues, Joel J.P.C. Kanhere, Salil S. Dustdar, Schahram Uhlig, Steve ramamohanarao, Kotagiri Buyya, rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Center for Applied Mathematics Tianjin University Tianjin China Raygun Performance Monitoring Wellington New Zealand Department of Computer Science York Centre for Quantum Technologies University of York York United Kingdom Microsoft Schiphol Netherlands Distributed Systems Group Vienna University of Technology Vienna Austria Detecon International GmbH Munich Germany Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Department of Engineering Science University of Oxford Oxford United Kingdom Department of Computer Science University of Western Ontario London Canada Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Institute of Science and Engineering Kanazawa University Japan Tecnun School of Engineering University of Navarra Spain Department of Computer Science and Engineering College of Engineering Qatar University Doha Qatar Bennett University Greater Noida India Machine Intelligence Research Labs AuburnWA United States Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Baltimore United States Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Department of Computer Science College of Computer and Information Sciences King Saud University Riyadh Saudi Arabia COPELABS Lusófona University Lisbon Portugal Sydney Australia The University of Melbourne Victoria Australia Laboratory School of Computing and Information Systems The University of Melbourne Australia

Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress. © 2024, CC BY.

关键词： Obsolescence

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Preserving the Privacy of Healthcare Data over Social Networks Using Machine Learning

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Computational Intelligence and Neuroscience 2022年第0期2022卷 4690936页

作者： Veeramakali, T. Shobanadevi, A. Nayak, Nihar ranjan Kumar, Sumit Singhal, Sunita Subramanian, Manoharan Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Sri Venkateswara College of Engineering Technology Chittoor India Indian Institute of Management Kozhikode India Department of Computer Science and Engineering Manipal University Jaipur Jaipur303007 India Department of Computer Science School of Informatics and Electrical Engineering Hachalu Hundesa Campus Ambo University Ambo Ethiopia

A key challenge in clinical recommendation systems is the problem of aberrant patient profiles in social networks. As a result of a person's abnormal profile, numerous vests might be used to make fake remarks about them, cyber bullying, or cyber-attacks. Many clinical researchers have done extensive study on this topic. The most recent studies on this topic are summarized, and an overarching framework is provided. When it comes to the methods and datasets that make up the data collection, the feature presentation and algorithm selection layers provide an overview of the various types of algorithm selections available. The categorization and evaluation of diseases and disorders has been one of the major advantages of machine learning in medical. Because it was harder to predict, it rendered it more controllable. It might range from difficult-to-find cancers in the early stages to certain other illnesses spread through the bloodstream. In healthcare, we may pick methods in machine learning depending on reliable outcomes. To do so, we must run the findings through each method. The major issue arises during information training and validation. Because the dataset is so large, eliminating mistakes might be difficult. The providers, other characteristics, various algorithms, data labelling techniques, and assessment criteria are all presented and contrasted in depth. Detecting anomalous users in medical social networks, on the other hand, is a work in progress. The result evaluation layer provides an explanation of how to evaluate and mark up the results of the various algorithm selection layers. Finally, it looks forward to more study in this area. © 2022 T. Veeramakali et al.

关键词： Diseases

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ROSTAM: A Passwordless Web Single Sign-on Solution Mitigating Server Breaches and Integrating Credential Manager and Federated Identity Systems

arXiv

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arXiv 2023年

作者： Mahnamfar, Amin Bicakci, Kemal Uzunay, Yusuf Informatics Institute Istanbul Technical University Istanbul34467 Turkey Computer Engineering Department Istanbul Technical University Istanbul34467 Turkey Securify Information Technology and Security Training Consulting Inc. Ankara06378 Turkey

The challenge of achieving passwordless user authentication is real given the prevalence of web applications that keep asking passwords. Complicating this issue further, in an enterprise environment, a single sign-on (SSO) service is often maintained but not all applications can be integrated with it. We envision a passwordless future which provides a frictionless and trustworthy online experience for users by integrating credential management and federated identity systems. In this regard, our implementation ROSTAM offers a dashboard that presents all applications the user can access with a single click after a passwordless SSO. The security of web passwords on the credential manager is ensured with a Master Key, rather than a Master Password, so that encrypted passwords can remain secure even if stolen from the server. We propose and implement novel techniques for synchronization (pairing) and recovery of this Master Key. We compare our solution to previous work using different evaluation frameworks, demonstrating that our hybrid solution combines the benefits of credential management and federated identity systems. Copyright © 2023, The Authors. All rights reserved.

关键词： Authentication

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Situating Network Infrastructure with People, Practices, and Beyond: A Community Building Workshop 25

Situating Network Infrastructure with People, Practices, and...

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25th ACM Conference on computer-Supported Cooperative Work and Social Computing, CSCW 2022

作者： Jang, Esther Han Beol Bidwell, Nicola Liu, Jen Sengers, Phoebe Bagalkot, Naveen Verdezoto, Nervo Densmore, Melissa Vigil-Hayes, Morgan Hasan, Shaddi Paul G. Allen School for Computer Science and Engineering SeattleWA United States International University of Management Windhoek Namibia Cornell University Information Science IthacaNY United States Cornell University Information Science and Science & Technology Studies IthacaNY United States Srishti Manipal Institute of Art Design and Technology Karnataka Bengaluru India Cardiff University School of Computer Science and Informatics Cardiff United Kingdom University of Cape Town Cape Town South Africa Northern Arizona University School of Informatics Computing and Cyber Systems FlagstaffAZ United States Virginia Tech Department of Computer Science BlacksburgVA United States

ISBN: (纸本)9781450391900

Our world is now connected and even entangled in unprecedented ways through networked technologies. Yet pockets of unequal connectivity persist, and technical infrastructures for connectivity remain difficult to design and build even for experts. In this workshop we aim to bring together a global community of multi- and inter-disciplinary researchers and implementers working on infrastructure development and connectivity to explore the existing design challenges and opportunities for bringing technical dimensions of networked infrastructures in conversation with human-computer interaction (HCI) and the social science of infrastructure. We will share, assess and define research problems and resources for rethinking networked infrastructures from human-, community-, and society-centered perspectives, understanding them to be embedded with human values and biases. We particularly intend our collaborative work to support real-world connectivity initiatives, which have grown in critical importance over the pandemic years - especially projects in support of Global South communities. Concrete deliverables from the workshop will include: (1) an initial shared bibliography to help formalize the state of knowledge in our area, (2) an agenda of shared goals, challenges, and intentions in our field, (3) a compilation of resources to support future work, and (4) social and organizing infrastructures for continued communication and academic collaboration. © 2022 Owner/Author.

关键词： Human computer interaction

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Dynamic Disaster Management with Real-Time IoT Data Analysis and Response

Dynamic Disaster Management with Real-Time IoT Data Analysis...

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Automation and Computation (AUTOCOM), International Conference on

作者： V Dankan Gowda Avinash Sharma Kdv Prasad Rini Saxena Tarkeshwar Barua Khalid Mohiuddin Department of Electronics and Communication Engineering BMS Institute of Technology and Management Bangalore Karnataka India Department of Computer Science and Engineering Chandigarh Engineering College Chandigarh Group of Colleges-Jhanjeri Mohali Punjab India Symbiosis Institute of Business Management Hyderabad Symbiosis International (Deemed University) Pune India Department of Business Informatics College of Business King Khalid University PO Box-3247 Abha Saudi Arabia

As natural and manmade disasters grew in number, as a result the problem of how to quickly and effectively respond to disaster has become fresh. This is precisely the purpose of this research: Using IoT technologies and powerful data analysis techniques, to integrate them into existing disaster management systems. The beginning of the article contains a broadcasted statement to the effect that traditional methods are insufficient, and real-time data and preemptive response systems are needed. With the application of Internet of Things, an integrated system is proposed in which countless types of information such as weather conditions and seismic activity are gathered by sensors and actuators. Advanced machine learning algorithms and predictive modeling are used to analyze the gathered data. This allows us to make real-time decisions. The design and construction of an IoT-based disaster management system is the methodology behind the research. In particular, we will evaluate how effective it is at reducing response times and increasing overall resilience to disasters. The results show a high efficiency in response, which reflects the feasibility of the method. Finally, the paper discusses the problems encountered in implementing IoT and advanced data analysis of disaster risk and suggests future research avenues. There is no doubt that they will change the present disaster management practice forever.

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Chinese E-Romance: Analyzing and Visualizing 7.92 Million Alibaba Valentine's Day Purchases

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Data and Information Management 2021年第4期5卷 363-371页

作者： Wang, Yongzhen Liu, Xiaozhong Ju, Yingnan Börner, Katy Lin, Jun Sun, Changlong Si, Luo WISE Lab Institute of Science of Science and S&T Management Faculty of Humanities and Social Sciences Dalian University of Technology Dalian China Computer Science Department Worcester Polytechnic Institute WorcesterMA United States School of Informatics Computing and Engineering Indiana University BloomingtonIN United States Alibaba DAMO Academy Hangzhou China

The days that precede Valentine's Day are characterized by extensive gift shopping activities all across the globe. In China, where much shopping takes place online, there has been an explosive growth in e-commerce sales during Valentine's Day over the recent years. This exploratory study investigates the extent to which each product category and each shopper group can exhibit romantic love within China's e-market throughout the 2 weeks leading up to 2019 Valentine's Day. Massive data from Alibaba, the biggest e-commerce retailer worldwide, are utilized to formulate an innovative romance index (RI) to quantitatively measure e-romantic values for products and shoppers. On this basis, millions of shoppers, along with their millions of products purchased around Valentine's Day, are analyzed as a case study to demonstrate their love consumption and romantic gift-giving. The results of the analysis are then illustrated to help understand Chinese e-romance based on the perspectives of different product categories and shopper groups. This empirical information visualization also contributes to improving the segmentation, targeting, and positioning of China's e-market for Valentine's Day. © 2021 Yongzhen Wang et al., published by Sciendo

关键词： Sales

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Lightweight Deep Learning for Resource-Constrained Environments: A Survey

arXiv

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arXiv 2024年

作者： Liu, Hou-I Galindo, Marco Xie, Hongxia Wong, Lai-Kuan Shuai, Hong-Han Li, Yung-Yui Cheng, Wen-Huang Department of Electronics and Electrical Engineering National Yang Ming Chiao Tung University Hsinchu300 Taiwan College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130000 China Faculty of Computing and Informatics Multimedia University Cyberjaya63100 Malaysia Hon Hai Research Institute Taipei114 Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei106 Taiwan

Over the past decade, the dominance of deep learning has prevailed across various domains of artificial intelligence, including natural language processing, computer vision, and biomedical signal processing. While there have been remarkable improvements in model accuracy, deploying these models on lightweight devices, such as mobile phones and microcontrollers, is constrained by limited resources. In this survey, we provide comprehensive design guidance tailored for these devices, detailing the meticulous design of lightweight models, compression methods, and hardware acceleration strategies. The principal goal of this work is to explore methods and concepts for getting around hardware constraints without compromising the model's accuracy. Additionally, we explore two notable paths for lightweight deep learning in the future: deployment techniques for TinyML and Large Language Models. Although these paths undoubtedly have potential, they also present significant challenges, encouraging research into unexplored areas. Copyright © 2024, The Authors. All rights reserved.

关键词： computer hardware

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Comb-calibrated raman Spectroscopy of Molecular Hydrogen

Comb-calibrated Raman Spectroscopy of Molecular Hydrogen

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2023 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2023

作者： Lamperti, Marco Rutkowski, Lucile Ronchetti, Daniele Gatti, Davide Gotti, Riccardo Cerullo, Giulio Thibault, Franck Jóźwiak, Hubert Wójtewicz, Szymon Maslowski, Piotr Wcislo, Piotr Polli, Dario Marangoni, Marco Dipartimento di Fisica Politecnico di Milano IFN-CNR Via Gaetano Previati 1/C Lecco23900 Italy Department of Science and High Technology University of Insubria Como22100 Italy UMR 6251 RennesF-35000 France Department of Electrical Computer and Biomedical Engineering Università degli studi di Pavia Pavia27100 Italy Institute of Physics Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Grudziadzka 5 Torun87-100 Poland

ISBN: (纸本)9798350345995

Molecular hydrogen and its isotopologues are key systems to test quantum electrodynamics (QED) at molecular length scales, as their energy levels can be calculated with high accuracy[1]. Comparison of the theoretical values with highly accurate experimental determinations of transition frequencies allows one to test QED and theories beyond the standard model of particle physics[2]. Recent accurate measurements of rovibrational frequencies of HD and D2, covering mostly the second overtone band, have shown a systematic deviation between measured and calculated transition frequencies. Yet, available measurements on H2 are characterized by uncertainties one order of magnitude larger than theory. © 2023 IEEE.

关键词： Uncertainty analysis

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