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APMS 2008 Conference on Innovations in Networks

作者： Huhta, Esko Pöyry-Lassila, Päivi Teräväinen, Helena Staffans, Aija Smeds, Riitta Helsinki University of Technology Department of Computer Science and Engineering SimLab. Finland Department of Architecture Laboratory of Urban Planning and Design Finland

ISBN: (纸本)9789512295470

The purpose of this paper is to explore the collaborative planning and design process of an innovative future school. Our case study examined, modeled, and further developed this planning and design process aiming to create a more wide-ranging place and space for learning than a mere school building We wanted to find out what kind of collaboration and network management would support the participatory planning and design process, and how it would be possible to make children's and youth's opinions visible and to accomplish collaboration in the design process. The case data was collected from a SimLab™ simulation project and architecture workshops. Our findings indicate that that the process of planning and designing innovative future schools require seamless collaboration between various actors and stakeholders, such as architects, pedagogy experts, future school users, and municipal decision makers. Furthermore, the network management aspect should be taken into account to make the collaborative design process more fruitful. Especially, the role of boundary objects was observed to be important both for supporting collaboration and participation in the design process, and for making children 's and youth's opinions visible.

关键词： Network management

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Evolutive identification of fuzzy systems for time-series prediction 7th

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7th International Conference on Parallel Problem Solving from Nature, PPSN 2002

作者： González, Jesús Rojas, Ignacio Pomares, Héctor Department of Computer Architecture and Computer Technology E.T.S. Ingeniería Informática University of Granada GranadaE. 18071 Spain

ISBN: (纸本)3540441395

This paper presents a new algorithm for designing fuzzy systems. It automatically identifies the optimum number of rules in the fuzzy knowledge base and adjusts the parameters defining them. This algorithm hybridizes the robustness and capability of evolutive algorithms with multiobjective optimization techniques which are able to minimize both the prediction error of the fuzzy system and its complexity, i.e. the number of parameters. In order to guide the search and accelerate the algorithm’s convergence, new specific genetic operators have been designed, which combine several heuristic and analytical methods. The results obtained show the validity of the proposed algorithm for the identification of fuzzy systems when applied to time-series prediction. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Multiobjective optimization

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LoRa-Powered Energy-Effcient Object Detection Mechanism in Edge Computing Nodes 6

LoRa-Powered Energy-Effcient Object Detection Mechanism in E...

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

作者： Jindal, Anshul Jose, Jiby Mariya Benedict, Shajulin Gerndt, Michael Technical University Munich Computer Architecture and Parallel Systems Germany Indian Institute of Information Technology Kottayam Department of Computer Science and Engg. India

ISBN: (数字)9781665469418

ISBN: (纸本)9781665469418

The ongoing accomplishments in the decades-long realization of computer vision have infused new dimensions in various research areas such as smart mobility, smart healthcare, education, finance, and so forth. Research works relating to automated object detection, deep learning-assisted data pipelines, and energy-efficient end-to-end solutions have enabled newer perceptions among researchers, albeit the existence of challenges. This paper proposes an object detection system using energy-efficient Long Range (LoRA) communication media on edge nodes such as Raspberry Pi, Coral DevBoard, and Nvidia Jetson Nano. The proposed approach utilized energy-efficient methods to collaboratively offload object detection-related tasks such as capturing images, training images, and inferring objects across a compendium of computing nodes using LoRA. In addition, this research study has attempted to reveal the inference capabilities of images on three different edge nodes. The proposed work has achieved a power difference of at least 1.2 watts during the inference period of the deep learning models without challenging the prediction accuracy with respect to the base model. © 2022 IEEE.

关键词： Object detection

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Data-Driven Representation Model of Urban Movement Space 2020

Data-Driven Representation Model of Urban Movement Space

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3rd International Conference on Geoinformatics and Data Analysis, ICGDA 2020

作者： Arregui, Harbil Otaegui, Oihana Arbelaitz, Olatz Vicomtech Donostia-San Sebastian Spain Computer Architecture and Technology Department UPV/EHU Donostia-San Sebastian Spain

ISBN: (纸本)9781450377416

Tracking urban mobility with current heterogeneous sensing capabilities has opened a wide research area on analytical and predictive data-driven models for improvements in transport operations and planning. These improvements are applicable for individual users, service providers and decision-makers. People, vehicles and goods move along the city according to the physical resources (roads, bike-lanes, side-walks...) and non-physical resources (such as scheduled public transportation services). We present this set of resources as the Urban Movement Space (UMS). We collect the main challenges and research foundations that geoinformatic approaches need to cope when tackling transportation resources and mobility data. The work presented in this paper proposes a conceptual modelling framework to represent the urban movement space, in order to match observed tracking data accordingly, and allow further analytical queries. Our approach combines an open free-space and network-based space to model the time-varying urban movement space, considering seasonality and uncertainty of multimodal travel options. © 2020 ACM.

关键词： Decision making

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Longitudinal study of mobile technology adoption: Evolution at work 1

Longitudinal study of mobile technology adoption: Evolution ...

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1st International Conference on the Digital Society, ICDS 2007

作者： Lawence, Elaine Er, Michael Department of Computer Systems Faculty of Information Technology Australia School of the Built Environment Faculty of Design Architecture and Building University of Technology Sydney Australia

ISBN: (纸本)0769527604

Workplaces are changing as new technologies are introduced in an effort to improve efficiency and increase business turnover. Although there has been an explosion of mobile technologies and devices in recent time, very few in situ studies of the adoption of these technologies have been undertaken. This paper reports on the results of a longitudinal case study of a business over a six year period as a knowledge worker shifted from Australia to the USA and then to England. It outlines how the company moved from paper based systems to an online system and finally to a mobile commerce system. The authors have used Mobile Informatics to analyze the use of mobile devices in particular settings and low end disruption theory to assist in the interpretation of the data. © 2007 IEEE.

关键词： Mobile commerce

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SofEA, a pool-based framework for evolutionary algorithms using CouchDB 12

SofEA, a pool-based framework for evolutionary algorithms us...

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14th International Conference on Genetic and Evolutionary Computation Companion, GECCO'12 Companion

作者： Merelo, Juan J. Mora, Antonio M. Fernandes, Carlos M. Esparcia-Alcázar, Anna I. University of Granada Department of Computer Architecture and Technology ETSIIT 18071 - Granada Spain S2 Grupo Spain

ISBN: (纸本)9781450311786

This paper studies SofEA, an architecture for distributing evolutionary algorithms (EAs) across computer networks in an asynchronous and decentralized way. SofEA is based on a pool architecture which is implemented using an object store interacting asynchronously with several clients. The fact that each client is autonomous leads to a complex behavior that will be examined in this paper, so that the design can be validated, rules of thumb can be extracted and the limits of scalability found. We will show how, beyond the usual measures employed in EA, specific measures such as the number of conicts across clients can give us hints on the algorithm behavior, and how implementation details can change not only the running time, but also the behavior of the evolutionary algorithm itself. By using these measures we try to find ideal values for parameters such as the simultaneous number of individuals evaluated by a client or the way these are chosen from the pool. Copyright 2012 ACM.

关键词： Complex networks

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Modeling the failures of power-aware data centers by leveraging heat recirculation

Modeling the failures of power-aware data centers by leverag...

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作者： Feng, Hao Deng, Yuhui Yu, Liang Department of Computer Science Jinan University Guangzhou China Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

With the explosive growth of data, hundreds of thousands of servers may be contained in a single data center. Hence, node failures are unavoidable and generally negatively effects the performance of the whole data center. Additionally, data centers with a large number of nodes will cause plenty of energy consumption. Many existing task scheduling techniques can effectively reduce the power consumption in data centers by considering heat recirculation. However, the traditional techniques do not take the situation of node failures into account. This paper proposes an airflow-based failure model for data centers by leveraging heat recirculation. In this model, the spatial distribution and time distribution of failures are considered. Furthermore, a genetic algorithm (GA) and a simulated annealing algorithm (SA) are implemented to evaluate the proposed failure model. Because the positions of node failures have a significant impact on the heat recirculation and the energy consumption of data centers, failures with different positions are analyzed and evaluated. The experimental results demonstrate that the energy consumption of data centers can be significantly reduced by using the GA and SA algorithms for task scheduling based on the proposed failure model. © 2019 John Wiley & Sons, Ltd.

关键词： Energy efficiency

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Designing OS for HPC applications: Scheduling

Designing OS for HPC applications: Scheduling

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作者： Gioiosa, Roberto McKeey, Sally A. Valero, Mateo Computer Science Division Barcelona Supercomputing Center Spain Computer Science and Engineering Chalmers University of Technology Sweden Computer Architecture Department Universitat Politecnica de Catalunya Spain

ISBN: (纸本)9780769542201

Operating systems have historically been implemented as independent layers between hardware and applications. User programs communicate with the OS through a set of well defined system calls, and do not have direct access to the hardware. The OS, in turn, communicates with the underlying architecture via control registers. Except for these interfaces, the three layers are practically oblivious to each other. While this structure improves portability and transparency, it may not deliver optimal performance. This is especially true for High Performance Computing (HPC) systems, where modern parallel applications and multi-core architectures pose new challenges in terms of performance, power consumption, and system utilization. The hardware, the OS, and the applications can no longer remain isolated, and instead should cooperate to deliver high performance with minimal power consumption. In this paper we present our experience with the design and implementation of High Performance Linux (HPL), an operating system designed to optimize the performance of HPC applications running on a state-of-the-art compute cluster. We show how characterizing parallel applications through hardware and software performance counters drives the design of the OS and how including knowledge about the architecture improves performance and efficiency. We perform experiments on a dual-socket IBM POWER6 machine, showing performance improvements and stability (performance variation of 2.11% on average) for NAS, a widely used parallel benchmark suite. © 2010 IEEE.

关键词： Electric power utilization

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Forecasting and managing urban futures: machine learning models and optimization of urban expansion

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Asian Journal of Civil Engineering 2024年第6期25卷 4673-4682页

作者： Abid, Mohammed Talib Aljarrah, Njood Shraa, Tamer Alghananim, Haneen Marouf Department of Architecture College of Engineering Al-Nahrain University Baghdah Iraq Computer Sciences Faculty of Information Technology and Computer Sciences Ajloun National University Ajloun Jordan Faculty of Science and Information Technology Cyber Security Irbid National University Irbid Jordan Faculty of Engineering Architecture Department Ain Shams University Cairo Egypt

This paper presents a novel method for predicting and controlling urban growth by combining convolutional neural networks (CNN) with Spider Monkey Optimization (SMO) to efficiently use their combined capabilities. This strategy utilizes sophisticated machine learning algorithms to forecast urban development patterns, while optimization technologies enhance these forecasts by including sustainable urban design ideas. Integration plays a crucial role in tackling the difficulties presented by fast urbanization, including issues related to land use, resource administration, and environmental sustainability in the fields of civil and architectural engineering. The study employs large datasets to assess the efficacy of CNN models in detecting urban expansion patterns and enhances these models with optimization scenarios encompassing land use, traffic flow, electricity efficiency, water resources, and waste management, all with the goal of enhancing urban sustainability. The findings demonstrate a significant improvement in the precision of predictions and the ability to maintain positive results, highlighting the crucial role of integrating machine learning and optimization in urban planning methodologies. This method not only provides urban planners and politicians with strong and effective tools for making decisions but also creates opportunities for implementing creative and sustainable solutions for urban growth. The results provide a substantial contribution to the existing urban planning literature by demonstrating the actual use of these technologies in regulating urban expansion. This will stimulate more study in this rapidly evolving subject. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Convolutional neural networks Machine learning Optimization techniques Spider monkey optimization Sustainable urban planning Urban expansion

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Lightweight user access control in energy-constrained wireless network services

Lightweight user access control in energy-constrained wirele...

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6th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2012

作者： Naranjo, J.A.M. Orduña, Pablo Gómez-Goiri, Aitor López-De-Ipiña, Diego Casado, L.G. Department of Computer Architecture and Electronics University of Almería Spain Deusto Institute of Technology - DeustoTech University of Deusto Bilbao Spain

ISBN: (纸本)9783642353765

This work introduces a novel access control solution for infrastructures composed of highly constrained devices which provide users with services. Low energy consumption is a key point in this kind of scenarios given that devices usually run on batteries and are unattended for long periods of time. Our proposal achieves privacy, authentication, semantic security, low energy and computational demand and device compromise impact limitation on a simple manner. The access control provided is based on user identity and time intervals. We discuss these properties and compare our proposal to previous related work. © 2012 Springer-Verlag.

关键词： Internet of things

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