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SSRN 2022年

作者： Zeng, Dong Miao, Jingjing Tang, Chaogang Long, Yaxin He, Maoen School of Architecture and Design China University of Mining and Technology Xuzhou China School of Computer Science and Technology China University of Mining and Technology Xuzhou China College of Design and Innovation Tongji University Shanghai China

Interactive evolutionary design (IED) systems, based on interactive evolutionary algorithm, have been the hot topic in both computer science and design recently. Due to the difference in both designer preferences and design capabilities for product styling, there are still many challenges which need to be addressed in practical application of IED systems. In order to tackle these challenges, we in this paper propose to construct a hybrid complex network model for product styling. The model incorporates both design knowledge and personal preferences, through a so-called gene regulatory network (GRN). First, we construct a GRN for product styling using design knowledge with both explicit and implicit knowledge, and then a GRN for product styling based on personal preferences using Boolean evaluation. In the next, combining the design knowledge and personal preferences, we construct a hybrid GRN for product styling. Then, according to the knowledge findings from GRNs, we develop an application strategy of the analytic knowledge in an IED. Taking the product styling SUV as an example, validation work is carried out to evaluate the evolutionary efficiency and design quality. The experimental results demonstrate that the proposed strategy, that embeds expert knowledge in an IED, can greatly improve the efficiency and quality of product styling designs. More important, our strategy can acquire the individual preferences during the evolutionary process as soon as possible. © 2022, The Authors. All rights reserved.

关键词： Efficiency

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A Toolbox of Feminist Wonder: Theories and methods that can make a difference 26

A Toolbox of Feminist Wonder: Theories and methods that can ...

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26th ACM Conference on computer-Supported Cooperative Work and Social Computing, CSCW 2023

作者： Hansson, Karin Bardzell, Shaowen Bhandari, Aparajita Boulicault, Marion Doyle, Dylan Thomas Erete, Sheena Cerratto Pargman, Teresa Lazem, Shaimaa Muller, Michael Normark, Maria Petterson, Adrian Rosén, Anton Poikolainen Taylor, Alex S. Thomas, Jakita O. Watson, Julia Södertörn University The School of Natural Sciences Technology and Environmental Studies Sweden Georgia Institute of Technology The School of Interactive Computing United States Cornell University Department of Communication United States University of Edinburgh Department of Philosophy United States University of Colorado Boulder Department of Information Science United States University of Maryland College of Information United States Stockholm University The Department of Computer and Systems Sciences Sweden City for Scientific Research and Technological Applications The Informatics Research Institute Egypt Ibm Research Human Centered Ai United States Uppsala University Department of Informatics and Media Sweden University of Toronto Faculty of Information Canada Aalto University The School of Arts Design and Architecture Finland City University of London The Centre for Human Computer Interaction Design United Kingdom Auburn University Department of Computer Science and Software Engineering United States University of Toronto Department of Computer Science Canada

ISBN: (纸本)9798400701290

This one-day hybrid workshop builds on previous feminist CSCW workshops to explore feminist theoretical and methodological approaches that have provided us with useful tools to see things differently and make space for change. Since its inception over a decade ago, feminist HCI has progressed from the margins to mainstream HCI, with numerous references in the literature. Feminist HCI has also evolved to incorporate other critical HCI practices such as Queer HCI, participatory design, and speculative design. While feminist approaches have grown in popularity and become mainstream, it is getting more difficult to distinguish the feminist emancipatory core from other attempts of developing and improving society in various ways. In this workshop, we therefore want to revisit our feminist roots, where theory is a liberatory and creative practice, motivated by affect, curiosity, and wonder. From this standpoint, we consider which of our feminist tools can make a significant difference today, in a highly datafied world. The goal of this workshop is to;1) create an inventory of feminist theories and concepts that have had an impact on our work as designers, educators, researchers, and activists;2) develop a feminist toolbox for the CSCW community to strengthen our feminist literacy. © 2023 Owner/Author.

关键词： Computation theory

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Inventory Management System based on IoT and Microservices architecture Design

Inventory Management System based on IoT and Microservices A...

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International Electrical Engineering Congress (iEECON)

作者： Paisan Sithiyopasakul Chavinkorn Piyatananugoon Vasutorn Chaowalittawin Woranidtha Krungseanmuang Posathip Sathaporn Isoon Kanjanasurat Boonchana Purahong Tunjai Archevapanich Attasit Lasakul Computer Engineering Department King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand College of Computing Khon Kean University KhonKean Thailand Faculty of Engineering and Architecture Rajamangala University of Technology Suvarnabhumi Nonthaburi Thailand

This paper presents the inventory management system based on IoT and microservices architecture that synced between IoT (Internet of Things) and web application. There are two main parts consisting of IoT forklift vehicle and data transmitted system by MQTT protocol. Microservice can utilize data to process business logic and provides API. Inventory area includes a zone, a subzone and parking area for forklifts to scan QR code on each subzone. Data of forklifts is published to back-end service. The results of system microservice publish information events and processes business data to the admin client with a delay under a second.

关键词： Productivity Industries Protocols Microservice architectures QR codes Inventory management Manufacturing

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Energy-efficient NTT Design with One-bank SRAM and 2-D PE Array

Energy-efficient NTT Design with One-bank SRAM and 2-D PE Ar...

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Design, Automation and Test in Europe Conference and Exhibition

作者： Jianan Mu Huajie Tan Jiawen Wu Haotian Lu Chip-Hong Chang Shuai Chen Shengwen Liang Jing Ye Huawei Li Xiaowei Li State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences CASTEST Tianjin University Nanyang Technological University Rock-Solid Security Lab Fiberhome

In Number Theoretic Transform (NTT) operation, more than half of the active energy consumption stems from memory accesses. Here, we propose a generalized design method to improve the energy efficiency of NTT operation by considering the effect of processing element (PE) geometry and memory organization on the data flow between PEs and memory. To decrease the number of data bits that are required to be accessed from the memory, a two-dimensional (2-D) PE array architecture is used. A pair of ping-pong buffers are proposed to transposed swap the coefficients to enable a single bank of memory to be used with the 2-D PE array to reduce the average memory bit access energy without compromising the throughput. Our experimental results show that this design method can produce NTT accelerators with up to 69.8% saving in average energy consumption compared with the existing designs based on multi-bank SRAM and one-bank SRAM with one-dimensional PE array with the same number of PEs and total memory size.

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Identify Initial Nodes for Spreader in A New Diffusion Model Based on Topology (DBT) in Social Networks

Identify Initial Nodes for Spreader in A New Diffusion Model...

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International Conference on Web Research (ICWR)

作者： Ehsan Khosravi Fatemeh Yazdanifar Nikoo Salimi Hamid Ahmadi Beni Dept. of Computer Engineering Sharif University of Technology Tehran Iran Dept. of Mathematics and Computer Science Amirkabir University of Technology Tehran Iran Dept. of the Electrical Electronics Electronics and Telecommunication Engineering and Naval Architecture University of Genoa Genoa Italy Dept. of Software Engineering Azarbaijan Shahid Madani University Tabriz Iran

With the development of science and technology through social networks, the process of diffusion has become a controversial subject. In social networks, the process of diffusion is transmitted from one individual to another. The influence maximization problem, in which at least k nodes are chosen as the initial nodes of the spreader in the smallest amount of time, is one of the most critical aspects of the diffusion process. Furthermore, the initial nodes in the social network should generate the most influence on the other nodes in the network. However, in the algorithms proposed to solve the problem of influence maximization, the real-world factors which affect the influence probability in diffusion models are ignored for example, the influence probability is determined randomly. This problem causes influence maximization algorithms based on diffusion models to face the challenge of time-consuming Monte Carlo simulation. So, the RIM algorithm presented in this article which this method selects the initial nodes of the spreader according on their local reachability. In addition, Due to privacy in social networks, complete information about people such as gender, education, etc. is not available. For this reason, in the RIM algorithm, using the graph structure in social networks, the influence probability is calculated in the new DBT diffusion model. In addition, the RIM algorithm exhibits stable performance in the selection of the spreader's initial nodes in terms of influence spread, and execution time.

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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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Recommendation System Towards Residential Energy Saving Based on Anomaly Detection 5

Recommendation System Towards Residential Energy Saving Base...

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5th International Conference on Signal Processing and Information Security, ICSPIS 2022

作者： Atalla, Shadi Himeur, Yassine Mansoor, Wathiq Amira, Abbes Fadli, Fodil Copiaco, Abigail Sohail, Shahab Saquib University of Dubai College of Engineering and IT Dubai United Arab Emirates University of Sharjah Department of Computer Science Sharjah United Arab Emirates Qatar University Dept. of Architecture & Urban Planning Doha2713 Qatar Jamia Hamdard School of Engineering Sciences & Technology New Delhi110062 India

ISBN: (纸本)9781665492652

This paper presents a recommender system to promote energy consumption reduction behaviors in residential buildings. The system exploits data stream processing methods jointly with machine learning algorithms on real-time residential data. Specifically, the data stream includes disaggregated power consumption, context, and weather conditions data. Internally the system converts time-series data streams into discrete ordered data points, which serve as inputs for training ML models. This method is used to predict power consumption anomalies. Gradually, the system helps to shape its users' activities into more energy-efficient ones. The experimental evaluation on real and simulated datasets demonstrates the promising performance of the proposed method, primarily when the K-neighbors neighbors' algorithm is used to classify the features extracted with interleaving current with the previous data points. The performance assessment of the machine learning algorithms shows the suitability of our implementation for Edge and Fog platforms in terms of accuracy, latency, and model size. © 2022 IEEE.

关键词： Electric power utilization

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A Smart Capacity Enhancement and Estimation Model for Hybrid Buildings by using Light Weight Deep Learning Model

A Smart Capacity Enhancement and Estimation Model for Hybrid...

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2023 International Conference on Disruptive Technologies, ICDT 2023

作者： Kumar, Senthil Atyam, Nageswara Rao Khadar Nawas, K. Awasthi, Shashank Kotteeswaran, M. Thirunavukkarasu, K.S. Koneru Lakshmanan Education Foundation Kl School of Architecture Andhra Pradesh Guntur India Cmr Institute of Technology Electrical and Electronics Department Karnataka Bengaluru India Vellore Institute of Technolog School of Computing Science and Engineering Tamil Nadu Chennai India Gl Bajaj Institute of Technology and Management Department of Computer Science and Engineering Uttar Pradesh Greater Noida India School of Management and Commerce Tamil Nadu Pallavaram Chennai India School of Computing Science Tamil Nadu Pallavaram Chennai India

ISBN: (纸本)9798350323887

Generally, for the buildings constructed in our areas, the conventional foundation known as 'shallow', i.e. from the ground level downwards, is set up in three dimensions such as length, width and depth. Foundations are not the same for all types of structures. The size and structure of the foundation varies depending on the nature of the prevailing soil, ground water level of the plot, type of building, and total load of the structure. In this paper an innovation estimation model was proposed based on light weigth deep learning technique. The proposed model introduces capacity estimation and energy efficiency plans and designs. These are all relating to commercial buildings, craft facilities and mass housing projects to enable design, construction. It also maintains the buildings under minimum energy consumption without stressing the operation of buildings. The health and comfort of the occupants are establishing compliance standards and ensure the maximum standards for energy efficiency in the plans or designs of commercial buildings. The proposed model also focuses the capacity estimation and energy efficiency programs beyond maximum standards. © 2023 IEEE.

关键词： Foundations

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Low-power emerging memristive designs towards secure hardware systems for applications in internet of things

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Nano Materials Science 2021年第2期3卷 186-204页

作者： Nan Du Heidemarie Schmidt Ilia Polian Department Nano Device Technology Fraunhofer Institute for Electronic Nano SystemsTechnologie-Campus 309126ChemnitzGermany Faculty of Electrical Engineering and Information Technology Chemnitz University of Technology(TU Chemnitz)Straße der Nationen 6209126ChemnitzGermany Department of Quantum Detection Leibniz Institute of Photonic Technology(IPHT)Albert-Einstein-Str.907745JenaGermany Institute for Solid State Physics Friedrich Schiller University JenaFürstengraben 107743JenaGermany Institute of Computer Engineering and Computer Architecture(ITI) University of StuttgartPfaffenwaldring 4770569StuttgartGermany

Emerging memristive devices offer enormous advantages for applications such as non-volatile memories and inmemory computing(IMC),but there is a rising interest in using memristive technologies for security applications in the era of internet of things(IoT).In this review article,for achieving secure hardware systems in IoT,lowpower design techniques based on emerging memristive technology for hardware security primitives/systems are *** reviewing the state-of-the-art in three highlighted memristive application areas,*** non-volatile memory,memristive reconfigurable logic computing and memristive artificial intelligent computing,their application-level impacts on the novel implementations of secret key generation,crypto functions and machine learning attacks are explored,*** the low-power security applications in IoT,it is essential to understand how to best realize cryptographic circuitry using memristive circuitries,and to assess the implications of memristive crypto implementations on security and to develop novel computing paradigms that will enhance their *** review article aims to help researchers to explore security solutions,to analyze new possible threats and to develop corresponding protections for the secure hardware systems based on low-cost memristive circuit designs.

关键词： Memristive technology Nanoelectronic device Low-power consumption Miniaturization Nonvolatility Reconfigurability In memory computing Artificial intelligence Hardware security primitives Machine learning-related attacks and defenses

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City models: past, present and future prospects

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Frontiers of Urban and Rural Planning 2025年第1期3卷 1-24页

作者： Ritter, Helge Herzog, Otthein Rothermel, Kurt Cohn, Anthony G. Wu, Zhiqiang Faculty of Technology Bielefeld University Bielefeld Germany College of Architecture and Urban Planning Tongji University Shanghai People’s Republic of China FB 03 University of Bremen Bremen Germany Institute of Parallel and Distributed Systems University of Stuttgart Stuttgart Germany School of Computer Science University of Leeds Leeds UK The Alan Turing Institute London UK

This paper attempts to take a comprehensive look at the challenges of representing the spatio-temporal structures and dynamic processes that define a city’s overall characteristics. For the task of urban planning and urban operation, we take the stance that even if the necessary representations of these structures and processes can be achieved, the most important representation of the relevant mindsets of the citizens are, unfortunately, mostly neglected. After a review of major “traditional” urban models of structures behind urban scale, form, and dynamics, we turn to major recent modeling approaches triggered by recent advances in AI that enable multimodal generative models. Some of these models can create representations of geometries, networks and images, and reason flexibly at a human-compatible semantic level. They provide huge amounts of knowledge extracted from huge collections of text and image documents and cover the required rich representation spectrum including geographic knowledge by different knowledge sources, degrees of granularity and scales. We then discuss what these new opportunities mean for coping with the modeling challenges posed by cities, in particular with regard to the role and impact of citizens and their interactions within the city infrastructure. We propose to integrate these possibilities with existing approaches, such as agent-based models, which opens up new modeling spaces including rich citizen models which are able to also represent social interactions. Finally, we put forward some thoughts about a vision of a “social AI in a city ecosystem” that adds relevant citizen models to state-of-the-art structural and process models. This extended city representation will enable urban planners to establish citizen-oriented planning of city infrastructures, to make them into inviting environments that reconcile and foster human culture, city resilience and sustainability.

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