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arXiv 2024年

作者： Serracanta, Berta Gao, Kai Ros-Giralt, Jordi Rodriguez-Natal, Alberto Contreras, Luis M. Yang, Richard Cabellos, Albert UPC BarcelonaTech Spain The Department of Computer Science and Techonology Tsinghua University China Qualcomm Europe Inc. The Enterprise Networking CTO team at Cisco Technology Expert at Telefonica CTIO Computer Science and Electrical Engineeringsince The Computer Architecture Department Universitat Politècnica de Catalunya Spain

With the rise of a new generation of applications (e.g., virtual and augmented reality, artificial intelligence, etc) demanding stringent performance requirements, the need for networking solutions and architectures that can enable a higher Quality of Experience (QoE) is becoming increasingly important. While jointly optimizing application and network may increase the applications' QoE and simultaneously improve the utilization of network resources, such a paradigm has had limited success in real production networks. However, with the combination of revolutionary trends in (1) compute processing demands, (2) networking capabilities, and (3) sustainable business models, it is high time the community explores the full potential of deeper integration between application and network. In this paper, recent trends observed over the past few years are systematically reviewed. These include the paradigm shift in modern communication services towards computing-driven applications, such as on-site AI training, advances in programmable network technologies like Software Defined Networking (SDN), and new business models incentivizing collaboration and cooperation between parties. Following this, successful scenarios that benefit from various forms of deeper network-application integration are reported, highlighting their considerable potential. A unified framework is then introduced, providing an overview of possible architecture paradigms for network-application integration and bringing awareness to existing abstractions, mechanisms, tools, and their potential combinations. The paper concludes with a discussion of several remaining challenges in building practical network-application integrated systems. Copyright © 2024, The Authors. All rights reserved.

关键词： Quality of service

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A novel model for data-driven smart sustainable cities of the future: the institutional transformations required for balancing and advancing the three goals of sustainability

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Energy Informatics 2021年第1期4卷 1-37页

作者： Bibri, Simon Elias Department of Computer Science The Norwegian University of Science and Technology Sem Saelands veie 9 TrondheimNO 7491 Norway Department of Architecture and Planning The Norwegian University of Science and Technology Alfred Getz vei 3 Sentralbygg 1 5th floor TrondheimNO 7491 Norway

In recent years, it has become increasingly feasible to achieve important improvements of sustainability by integrating sustainable urbanism with smart urbanism thanks to the proven role and synergic potential of data-driven technologies. Indeed, the processes and practices of both of these approaches to urban planning and development are becoming highly responsive to a form of data-driven urbanism, giving rise to a new phenomenon known as "data-driven smart sustainable urbanism." Underlying this emerging approach is the idea of combining and integrating the strengths of sustainable cities and smart cities and harnessing the synergies of their strategies and solutions in ways that enable sustainable cities to optimize, enhance, and maintain their performance on the basis of the innovative data-driven technologies offered by smart cities. These strengths and synergies can be clearly demonstrated by combining the advantages of sustainable urbanism and smart urbanism. To enable such combination, major institutional transformations are required in terms of enhanced and new practices and competences. Based on case study research, this paper identifies, distills, and enumerates the key benefits, potentials, and opportunities of sustainable cities and smart cities with respect to the three dimensions of sustainability, as well as the key institutional transformations needed to support the balancing of these dimensions and to enable the introduction of data-driven technology and the adoption of applied data-driven solutions in city operational management and development planning. This paper is an integral part of a futures study that aims to analyze, investigate, and develop a novel model for data-driven smart sustainable cities of the future. I argue that the emerging data-driven technologies for sustainability as innovative niches are reconfiguring the socio-technical landscape of institutions, as well as providing insights to policymakers into pathways for strengthening

关键词： Sustainable development

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The evolution of inharmonicity and noisiness in contemporary popular music

arXiv

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arXiv 2024年

作者： Deruty, Emmanuel Meredith, David Lattner, Stefan Sony Computer Science Laboratories 6 rue Amyot Paris75005 France Department of Architecture Design and Media Technology Aalborg University Rendsburggade 14 Aalborg9000 Denmark

Much of Western classical music relies on instruments based on acoustic resonance, which produce harmonic or quasi-harmonic sounds. In contrast, since the mid-twentieth century, popular music has increasingly been produced in recording studios, where it is not bound by the constraints of harmonic sounds. In this study, we use modified MPEG-7 features to explore and characterise the evolution of noise and inharmonicity in popular music since 1961. We place this evolution in the context of other broad categories of music, including Western classical piano music, orchestral music, and musique concrète. We introduce new features that distinguish between inharmonicity caused by noise and that resulting from interactions between discrete partials. Our analysis reveals that the history of popular music since 1961 can be divided into three phases. From 1961 to 1972, inharmonicity in popular music, initially only slightly higher than in orchestral music, increased significantly. Between 1972 and 1986, this rise in inharmonicity was accompanied by an increase in noise, but since 1986, both inharmonicity and noise have moderately decreased. In recent years (up to 2020), popular music has remained much more inharmonic than popular music from the 1960s or orchestral music involving acoustic resonance instruments. However, it has become less noisy, with noise levels comparable to those of orchestral music. We relate these trends to the evolution of music production techniques. In particular, the use of multi-tracking may explain the higher inharmonicity in popular music compared to orchestral music. We illustrate these trends with analyses of key artists and *** Codes 68T05, 42C40 © 2024, CC BY.

关键词： Background noise

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Design and Implementation of an EMG-based System for Monitoring and Help Request

Design and Implementation of an EMG-based System for Monitor...

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2022 International Conference on Smart Systems and Power Management, IC2SPM 2022

作者： Zeine, Carla Daou, Roy Abi Zeid Telawi, Samer Boercsoek, Josef Hayek, Ali Haidar, Gaby Abou University of Kassel Faculty of Electrical Engineering /Computer Science Department of Computer Architecture and System Programming Kassel Germany Lebanese German University Faculty of Public Health Jounieh Department of Computer Architecture and System Programming Biomedical Technologies Department Jounieh Lebanon Université la Sagesse Faculty of Engineering Furn El Chebbak Mechatronics Department Beirut Lebanon University of Applied Science Hamm-Lippstadt Department Lippstadt 2 Hardware Engineering Marker Allee 76-78 Hamm59063 Germany American University of Science and Technology Faculty of Engineering Zahle Lebanon

ISBN: (数字)9781665452915

ISBN: (纸本)9781665452915

Integrating electrophysiological signals in larger systems is getting wider due to the fact that such modalities facilitate the daily tasks of users. However, the high cost of monitoring systems (e.g., oscilloscopes) limits the testing and analysis of the acquired signal from such noisy systems (i. e., electrophysiological devices). The proposed system is a part of a larger proj ect that deals with the identification of sign language movements through the use of Muscle-computer Interfaces. On one hand, the user is able to display the signal acquired by the electrodes on an LCD screen. On the other hand, the system helps a mute patient to issue a special message to his surrounding environment that does not know the sign language to ask for help. The second feature is not unique, as it can be replaced by any other application based on the user's needs. The system was tested on several persons, and the results are promising. © 2022 IEEE.

关键词： Liquid crystal displays

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AI-based Fuzzy Clustering System for Improving Customer Relationship Management 6

AI-based Fuzzy Clustering System for Improving Customer Rela...

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6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022

作者： Krishnareddy, Kr Aravinda, T.V. Nair, Kiran Patel, Umesh Kumar Sadvokasova, Gaukhar Shyamala Susan, V. Sjm Institute of Technology Department of Computer Science and Engineering India College Abu Dhabi School of Management. Department of Management United Arab Emirates Chaudhary Charan SIngh University Department of Bca Noida India International Education Corporation Department of Architecture Almaty050042 Kazakhstan A P C Mahalaxmi College for Women Department of Computer Science Tamilnadu Tuticorin India

ISBN: (数字)9781665469418

ISBN: (纸本)9781665469418

Artificial Intelligence (AI) is a technology that is becoming more and more widely recognized with the addition of technologies such as personal helpers and chatbots. To get the most out of AI, your company needs to understand how to implement it better. Today, AI enhances almost every business segment and Customer Relationship Management (CRM), which is the area that has the most benefit in enhancing a better customer experience. The existing literature does not provide sufficient empirical evidence of how social media technologies affect a company's distribution chain relationships. Today, Artificial Intelligence empowers almost every business segment and CRM, providing the greatest benefit in enhancing a better customer experience. The main purpose of this study is to show how to successfully implement chatbot in CRM using AI-based Fuzzy Clustering system (AI-FCS), how to integrate chatbot with CRM and how chatbots affect customer relationship management. From forecast lead scoring to service chatbots to customized marketing operations. Chatbots can provide tools to provide a highly productive and better, personalized customer experience to all employees. Chatbots are now easily accessible to everyone in your organization, analyzing data, predicting and planning the next steps, and automating tasks and decisions. Create an optimal control model for Customer Relationship Management using the optimal control theory, depending on the characteristics of customer relationship management. With this model, it can gain effective management insights into Customer Relationship Management for optimal new customer acquisition and existing customer retention strategies. © 2022 IEEE.

关键词： Fuzzy clustering

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DESIGNING EV CHARGING STATIONS DEPLOYMENT THROUGH HOLISTIC SIMULATIONS: THE SANEVEC PROJECT 5

DESIGNING EV CHARGING STATIONS DEPLOYMENT THROUGH HOLISTIC S...

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5th Conference on Code of Practice for Electric Vehicle Charging Equipment Installation: Charging Ahead, EVI 2023

作者： Guisado-Lizar, José-Luis Jiménez-Moreno, Gabriel Diaz-Del-Rio, Fernando Sevillano-Ramos, J.L. Cagigas-Muñiz, Daniel Morón-Fernández, María José Cascado-Caballero, Daniel Jiménez-Morales, Francisco Cárdenas-Montes, Miguel Wainer, Gabriel A. Ragel-Díaz-Jara, David Rodríguez-Leal, J. Cerezuela-Escudero, E. Montes-Sánchez, J.M. Casanueva-Morato, Daniel Ayuso-Martínez, Alvaro Universidad de Sevilla Avenida Reina Mercedes s/n Sevilla41012 Spain Department of Computer Architecture and Technology Universidad de Sevilla Avenida Reina Mercedes s/n Sevilla41012 Spain Department of Condensed Matter Physics Universidad de Sevilla Avenida Reina Mercedes s/n Sevilla41012 Spain Department of Basic Research Centro de Investigaciones Energéticas Medioambientales y Tecnológicas Madrid Spain Department of Systems and Computer Engineering Carleton University Ottawa Canada

ISBN: (纸本)9781839539848

To determine the optimal location of the large number of urban public charging stations that will have to be deployed in the following years to transition to electric vehicles (EVs) is a challenging task, as it is intimately interconnected with the complexity of urban traffic and electric grid operation. The city is a complex system in which emerging patterns such as traffic jams, and instabilities or even outages in the electric grid are difficult to predict. The layout of charging stations can alter those patterns in traffic and electric grid operation, with consequences to mobility, air quality, and electric system. The present article presents the concept under the research project SANEVEC. It will build a framework for the optimal determination of the location of EV charging stations in a city based on simulation, which will be able to reproduce the feedback effects between all the variables involved: locations of the stations, traffic patterns, characteristics, and operation of the electricity grid, charging fees and air quality in the city. It will employ artificial intelligence methods to find high-quality station location solutions from the simulations and to predict the air quality in the city. © The Institution of Engineering & technology 2023.

关键词： Air quality

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THE EFFECT OF LIMITED MOBILITY ON THE EXPERIENCED SEGREGATION OF FOREIGN-BORN MINORITIES

arXiv

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arXiv 2024年

作者： Liao, Yuan Gil, Jorge Yeh, Sonia Pereira, Rafael H.M. Alessandretti, Laura Department of Space Earth and Environment Chalmers University of Technology Gothenburg Sweden Department of Architecture and Civil Engineering Chalmers University of Technology Gothenburg Sweden - Brazil Data Science Division Brazil Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark

Segregation is a key challenge in promoting more diverse and inclusive cities. Research based on large-scale mobility data indicates that segregation between majority and minority groups persists in daily activities beyond residential areas, like visiting shops and restaurants. Aspects including lifestyle differences, homophily, and mobility constraints have been proposed as drivers of this phenomenon, but their contributions remain poorly quantified. Here, we elucidate how different mechanisms influence segregation outside home, looking at the distinctive segregation experienced by native and foreign-born individuals. Our study is based on the movement of ∼320,000 individual smartphone devices collected in Sweden, where immigration creates profound divides. We find that while day-to-day activities lead to mixing for native-born individuals, foreign-born individuals remain segregated in their out-of-home activities. Using counterfactual simulations, we show that this heterogeneous effect of mobility on experienced segregation results mainly from two mechanisms: homophily and limited travel, i.e. foreign-born individuals (i) tend to visit destinations visited by similar individuals, and (ii) have limited mobility ranges. We show that homophily, as represented by destination preference, plays a minor role, while limited mobility, associated with reduced transport access, limits opportunities for foreign-born minorities to diversify their encounters. Our findings suggest that enhancing transport accessibility in foreign-born concentrated areas could reduce social segregation. © 2024, CC BY-SA.

关键词： Smartphones

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The Seeker’s Dilemma: Realistic Formulation and Benchmarking for Hardware Trojan Detection

The Seeker’s Dilemma: Realistic Formulation and Benchmarkin...

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IEEE International Conference on Performance, Computing and Communications (IPCCC)

作者： Amin Sarihi Ahmad Patooghy Abdel-Hameed A. Badawy Peter Jamieson Klipsch School of Electrical and Computer Engineering New Mexico State University Las Cruces NM MIPS Architecture and Performance Austin TX Department of Computer Systems Technology North Carolina A&T State University Greensboro NC Department of Electrical and Computer Engineering Miami University Oxford OH

ISBN: (数字)9798350367942

ISBN: (纸本)9798350367959

This work focuses on advancing the security field in the hardware design space by formally defining the problem of Hardware Trojan (HT) detection. The goal is to model HT detection more closely to the real world, i.e., describing the problem as "The Seeker’s Dilemma" (an extension of Hide&Seek on a graph), where a detecting agent is unaware of whether HTs infect circuits or not. Using this problem formulation, we create a benchmark that consists of a mixture of HT-free and HT-infected restructured circuits while preserving their original functionalities. The restructured circuits are randomly infected by HTs, causing a situation where the defender is uncertain if a circuit is infected. Our innovative dataset will help the community better judge the detection quality of different methods by comparing their success rates in circuit classification. We use our benchmark to evaluate three state-of-the-art HT detection tools to show baseline results for this approach. We use Principal Component Analysis to assess the strength of our benchmark, where we observe that some restructured HT-infected circuits are mapped closely to HT-free circuits, leading to significant label misclassification by detectors.

关键词： Accuracy Circuits Detectors Benchmark testing Hardware Quality assessment Trojan horses Security Integrated circuit modeling Principal component analysis

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Unsupervised Deep Learning Approaches for Anomaly Detection in IoT Data Streams 4

Unsupervised Deep Learning Approaches for Anomaly Detection ...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Suresh, Helina Rajini Neelaveni, R. Kumar, Bonda Kiran Arunadevi, R. Indhumathi, G. Varun, M. Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of ECE Tamilnadu Chennai India Srm Institute of Science and Technology Department of Cse Tamilnadu Chennai India Kl School of Architecture Kl Deemed to Be University Andhrapradesh India Prince Shri Venkateshwara Padmavathy Engineering College Department of Computer Science and Engineering Tamilnadu Chennai India Rajalakshmi Engineering College Department of ECE Tamilnadu Chennai India Saveetha Engineering College Department of ECE Tamilnadu Chennai India

ISBN: (纸本)9798350300888

The proliferation of IoT devices is primarily responsible for the data deluge that has engulfed multiple industries. Nevertheless, due to the high dimensionality and complexity of IoT data streams, anomaly detection remains a significant challenge. This suggests that an unsupervised deep learning strategy could be used to identify anomalies in IoT data streams. Instead of relying on labeled data, this method employs deep neural networks, which can be trained to recognize anomalies and comprehend complex patterns. Experiments are conducted on a real-world IoT dataset to evaluate the efficacy and accuracy of the proposed method. The results demonstrate its proficiency in detecting anomalies in IoT data streams, paving the way for a safer, more reliable Internet of Things. Using unsupervised deep learning techniques, the method provides a practicable solution to the age-old problem of IoT anomaly identification. © 2023 IEEE.

关键词： Internet of things

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Speech to Reality: On-Demand Production using Natural Language, 3D Generative AI, and Discrete Robotic Assembly

arXiv

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arXiv 2024年

作者： Kyaw, Alexander Htet Jeon, Se Hwan Smith, Miana Gershenfeld, Neil Department of Architecture The Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Center for Bits and Atoms Massachusetts Institute of Technology CambridgeMA02139 United States

We present a system that transforms speech into physical objects by combining 3D generative Artificial Intelligence (AI) with robotic assembly. The system leverages natural language input to make design and manufacturing more accessible, enabling individuals without expertise in 3D modeling or robotic programming to create physical objects. We propose utilizing discrete robotic assembly of lattice-based voxel components to address the challenges of using generative AI outputs in physical production—such as design variability, fabrication speed, structural integrity, and material waste. The system interprets speech to generate 3D objects, discretizes them into voxel components, computes an optimized assembly sequence, and generates a robotic toolpath. The results are demonstrated through the assembly of various objects, ranging from chairs to shelves, which are prompted via speech and realized within 5 minutes using a 6-axis robotic arm. Copyright © 2024, The Authors. All rights reserved.

关键词： Robotic assembly

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