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检索条件"任意字段=3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems"

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Applying Ant-based Multi-Agent systems to Query Routing in Distributed Environments

Applying Ant-based Multi-Agent Systems to Query Routing in D...

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International ieee Conference on intelligent systems, IS

作者： Elke Michlmayr Arno Pany Sabine Graf Women's Postgraduate College for Internet Technologies (WIT) Institute for Sof tware Technology and InteractiveSystems University of Technology Vienna Vienna Austria Institute for Sof tware Technology and InteractiveSystems University of Technology Vienna Vienna Austria

This paper presents SemAnt, a novel ant-based multi-agent system designed for distributed query routing. While the ant metaphor has been successfully applied to network routing both in wireless and fixed networks, little is yet known about its applicability to the task of query routing in distributed environments. We point out the similarities and dissimilarities between routing of data packets and routing of queries, and we present the design of SemAnt, which is based on the ant colony optimization meta-heuristic. For experimental evaluation, we deploy the algorithm in a peer-to-peer environment with a real-world application scenario and compare its performance against the well-known k-random walker approach. As we show, the benefits of SemAnt are that the routes for queries are optimized according to their popularity, and that the algorithm is highly suitable for volatile environments

关键词： Multiagent systems Query processing Routing Peer to peer computing Ant colony optimization Artificial intelligence intelligent systems Broadcasting Autonomous agents Algorithm design and analysis

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A cloud computing based mobile healthcare service system

A cloud computing based mobile healthcare service system

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ieee International Conference on Smart Instrumentation, Measurement and Applications (ICSIMA)

作者： Gao Zhiqiang He Lingsong Tian Hang Ling Cong School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan China

The promising potential of cloud computing and its convergence with technologies such as cloud storage, cloud push, mobile computing leads to new developments for divers application domains, which provides a strong technical support for remote healthcare service as well. Experts and researchers believe that cloud computing technology can greatly improve the level of healthcare services. Currently, many experts have done fruitful research in this domain. This paper presents a cloud computing based remote healthcare service system. This system mainly consists of three parts: Portable medical devices, intelligent terminals (phones, tablets, etc.), cloud services platform. Portable medical acquisition devices transmit physiological signal to the intelligent terminal via wireless way (Bluetooth/WiFi). Monitoring software in smart terminal responses for data display, storage, and push the measurement results to the cloud service platform. Cloud services platform is a special website developed using cloud server, cloud storage and cloud push technology, which is the core of the whole system. Users can view and maintain their health data record anytime and anywhere only need an Internet equipment. Physicians can view their patient's health status through the same way. If necessary, the doctor can also push the diagnosis to patients and their families' smart phone, so related people can get the diagnosis result at the first time. On the smart terminal, a virtual instrument browser is proposed which can dynamically load virtual instrument page programs and can turn them into executable virtual instrument applications, which can break through the install limitation of measurement application, to avoid installing many applications on the phone.

关键词： Cloud computing Decision support systems Medical services Instruments Handheld computers Medical diagnostic imaging Convergence

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CLOUDIO: A Cloud computing-Oriented Multi-tenant Architecture for Business Information systems

CLOUDIO: A Cloud Computing-Oriented Multi-tenant Architectur...

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ieee International Conference on Cloud computing, CLOUD

作者： Enrique Jiménez Domingo Javier Torres Nino Angel Lagares Lemos Miguel Lagares Lemos Ricardo Colomo Palacios Juan Miguel Gómez Berbís Computer Science Department Universidad Carlos III de Madrid Leganés Madrid Spain

Cloud computing is evolving from a mere “storage” technology to a new vehicle for Business Information systems (BIS) to manage, organize and provide added-value strategies to current business models. However, the underlying infrastructure for Software-as-a-Service (SaaS) to become a new platform for trading partners and transactions must rely on intelligent, flexible, context-aware Multi-Tenant Architectures. In this paper, we present Cloudio, a Cloud computing-based metadata-powered Multi-Tenant Architecture, backed with a proof-of-concept J2EE implementation.

关键词： databases Driver circuits Computer architecture Clouds Business Computational modeling data models

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Comment on “Particle Swarm Optimization Based Highly Nonlinear Substitution-Boxes Generation for Security Applications”

Comment on “Particle Swarm Optimization Based Highly Nonlin...

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ieee International Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Alexandr Kuznetsov Kateryna Kuznetsova JSC “Institute of Information Technologies” Kharkiv Ukraine V. N. Karazin Kharkiv National University Kharkiv Ukraine

ISBN: (纸本)9781665426060

This report presents a comment on the article “Particle Swarm Optimization Based Highly Nonlinear Substitution-Boxes Generation for Security Applications”, that was recently published in ieee Access (Volume 8, 2020, date of publication June 23, 2020). This article explores a new s-box generation method, which based on the particle swarm optimization. The authors claim, that their proposed technique they surpasses the known results. In particular, they assert that the s-boxes, generated by them, (the article lists three examples in Tables 1–3) are comparable in nonlinearity to the best-known results, or even outperform them. In addition, the authors argue that the new s-boxes are able to offer better resistance against linear cryptanalysis than the most recent optimization-based s-boxes. We show that this is not the case. Indeed, the resistance against linear cryptanalysis is expressed with the indexes of the s-box nonlinearity. The nonlinearity is estimated as the minimum nonlinearity of the component Boolean functions, that describes the certain s-box. However, the authors of the article erroneously estimate the nonlinearity of only the coordinate Boolean functions. Any component Boolean function has to be highly nonlinear, and we show that in the examples given by the authors, there are functions with very low value of the nonlinearity. Therefore, the authors' general conclusion about the better resistance against linear cryptanalysis is also not confirmed. Nevertheless, it should be noted that s-box generation method, based on the particle swarm optimization, is the promising direction that needs the further researches. However, it is necessary to revise the analysis of the performance of this technique (see Section 4) and to clarify the obtained dependences (see Fig. 2–4) and the gained insights.

关键词： Resistance Ciphers Boolean functions Conferences data acquisition Optimization methods Particle swarm optimization

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Fast Kernel for Calculating Structural Information Similarities

Fast Kernel for Calculating Structural Information Similarit...

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International ieee Conference on intelligent systems, IS

作者： Jin-Mao Wei Shu-Qin Wang Jing Wang Jun-Ping You Institute of Computational Intelligence Northeast Normal University China Open Symbol Computation and Knowledge Engineering Laboratory of State Education Jilin University Changchun Jilin China School of Mathematics & Statistics Northeast Normal University Changchun Jilin China

Structural similarity computation plays a crucial role in many applications such as in searching similar documents, in comparing chemical compounds, in finding genetic similarities, etc. We propose in this paper to use structural information content (SIC) for measuring structural information, considering both the nodes and edges of trees. We utilize a binary encoding approach for assigning the weights of different layer nodes and determining if some tree is a subtree of another tree. By defining a fast kernel and recursively computing SICs, we evaluate the structural information similarities of data trees to pattern trees. In the paper, we present the algorithm for calculating SICs with computation complexity of O(n), and use simple examples to instantiate the performance of the proposed method

关键词： Kernel Chemical compounds Silicon carbide XML Genetics Encoding Clustering algorithms intelligent systems intelligent structures Pattern analysis

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A Financial Decision Support Optimization System Based on Artificial Intelligence and data Mining Algorithms

A Financial Decision Support Optimization System Based on Ar...

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Electrical Engineering, Big data and Algorithms (EEBDA), ieee International Conference on

作者： Natalie Cao National University of Singapore Singapore

Effective financial decision-making is crucial for organizational growth, yet it is often impeded by limitations in information availability and subjective biases. While traditional computer-based financial decision support systems (FDSS) have marginally enhanced decision quality, they still need further improvement with data inaccuracies, limited analytical capabilities, and slow response times. This paper examines the potential of advanced Artificial Intelligence (AI) and data mining algorithms to revolutionize FDSS. We critically analyze the shortcomings of current FDSS and introduce an innovative approach incorporating AI-driven data mining into electronic financial decision support frameworks. This integration aims to create more sophisticated, agile, and intelligent tools, addressing the evolving demands of financial decision-makers. Our study highlights the transformative impact of AI and data mining on FDSS and sets the stage for future advancements in intelligent financial decision-making.

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Emergency Forecasting on the Basis of the Bifurcation Analysis Practice-Oriented to Local Climate Dynamics

Emergency Forecasting on the Basis of the Bifurcation Analys...

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ieee International Conference on intelligent data acquisition and advanced computing systems

作者： Yury Kolokolov Anna Monovskaya Orel State University

ISBN: (纸本)9781728140704

Specialized data processing aimed to the emergency forecasting on local climate dynamics over last century from the bifurcation analysis viewpoint can suppose analytics on specific phenomena which were out of considerations until recently. The paper discusses a pilot version of the computer software, where one of such phenomena (namely, so-called interannual temperature variability) is involved into the consideration in daily terms for time and temperature coordinates. Cycling is organized per a local climate system, where five logically independent procedures operate with specialized 3D-structure. Each 3D-structure consists of 20-50 thousands samples of the meteorological observations on land surface air temperature daily means. The theoretical base is provided by the conceptual model on local climate dynamics (so-called HDS-model), where both the amplitude quantization (limited by the temperature Hysteresis) and the time quantization (the Double Synchronization) compete. Thus alternations between three elementary dynamical processes with the same period (one year) and different patterns of annual warming-cooling cycles exist instead of traditional trend estimations calculated for the annual and/or monthly means. We believe that the results could be interesting for scientists and specialists in the research and practical fields connected with consequences of the climate changes.

关键词： Emergency forecasting Bifurcation analysis Instrumental observations data processing Stability margin Uncertainty Dynamic system with a variable structure Interannual variability Local climate change local climate stability margin Automatic data processing data processing time quantization Basis computer software Uncertainty BIFURCATION Cycling meteorological observations Emergencies

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Real-Time Anomaly Detection in 5G Networks Through Edge computing 3

Real-Time Anomaly Detection in 5G Networks Through Edge Comp...

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3rd ieee International Conference on intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Shaik, Riaz Raju, Dara Behera, Prakash Chandra Changala, Ravindra Mary, S. Suma Christal Balakumar, A. Kl University Department of Cse Andhra Pradesh Vaddeswaram India Vignana Bharathi Institute and Technology Dept. of Computer Science & Engineering Aushapur Ghatkesar India St. Claret College Department of Science Bangalore India Guru Nanak Institutions Technical Campus Department of Information Technology Hyderabad India Panimalar Engineering College Department of Information Technology Poonamalle Chennai India K. Ramakrishnan College of Engineering Department of Ece samayapuram Trichy India

ISBN: (纸本)9798350361186

Strong anomaly detection techniques are becoming more and more necessary as 5G networks develop in order to maintain network performance, security, and dependability. This study leverages the capabilities of Mobile Edge computing (MEC) to present a novel method for anomaly detection in 5G networks. By processing data closer to the network edge, the integration of MEC offers an efficient and decentralized architecture that lowers latency and improves real-time detection capabilities. The distributed module takes advantage of its close proximity to network devices by using sophisticated algorithms for anomaly detection, which are implemented at the mobile edge. The system can quickly detect abnormalities from typical network activity by utilizing capabilities including Flow Collection, Anomaly Symptom Detection, and Network Anomaly Detection. The distributed module provides anomalous information to the centralized decision-making module for thorough examination. It takes into account variables like resource use and network traffic and integrates this data with metrics gathered from monitoring modules. Because of its adaptive characteristics, the system may expand anomaly detection components, enhance detection functions, and modify virtualized resources in response to shifting network circumstances. The evaluation findings reveal that the suggested anomaly detection method performs well in 5G networks, with decreased false positives, increased responsiveness, and better flexibility to changing network conditions. Using MEC not only makes anomaly detection more effective, but it also fits in with the 5G design, which makes it a viable option for protecting the upcoming generation of communication networks. It obtains 95% accuracy in classification. The suggested approach has proven to be resilient in handling security issues by producing outcomes that are either comparable to or better than those attained by other techniques that have been previously presented in the s

关键词： 5G mobile communication systems

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Revolutionizing Waste Management Through intelligent Garbage Segregation Bin 3

Revolutionizing Waste Management Through Intelligent Garbage...

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3rd International Conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Veerabhadraswamy, K.M. Kumar, Karthik Indhuja, A. Barve, Amit Kannadasan, B. Bakhare, Ruhi Government Engineering College Mosalehosahalli Department of Electronics and Communication Engineering Karnataka Hassan573 212 India REVA University School of Civil Engineering Karnataka Bangalore560 064 India SNS College of Technology Department of Computer Science and Engineering Tamil Nadu Coimbatore641 035 India Parul University Parul Institute of Technology Faculty of Engineering and Technology Department of Computer Science and Engineering P.O.Limda Gujarat 391 760 India Kannadasan Balakrishnan Research Foundation Kalieswari Nagar Department of Civil Architectural Engineering and Planning Tamil Nadu Peraiyur625 703 India Dr. Ambedkar Institute of Management Studies and Research Deekshabhoomi Maharashtra Nagpur440 010 India

ISBN: (纸本)9798350343632

Efficient waste management stands as a paramount concern in the current environmental landscape. The proper handling, sorting, transportation, and disposal of waste materials are essential to mitigate environmental hazards. The separation of trash into several categories allows for a more accurate evaluation. Conventional manual waste segregation systems necessitate a significant amount of human labor, time, and money. This study proposes a waste management system integrated using advanced technologies such as the Internet of Things (IoT) and Artificial Intelligence (AI), allowing for easy and cost-effective garbage segregation and tracking. The technique is intended to separate garbage into several categories such as glass, plastic, cardboard, paper, metal, and trash. A sample dataset acquired from Kaggle was rigorously processed to design and evaluate the system, which includes operations like as image resizing and rescaling. The DenseNet, is a Deep Learning (DL) model used for accurate garbage recognition. This unique smart segregation bin makes use of the potential of AI and IoT technology. The model is embedded in a controller, allowing it to properly recognize different waste items and trigger the associated actuator for accuracy sorting. A user-friendly Graphical User Interface (GUI) structure makes the entire process visible to the public. This interface enables users to watch the system's operation in real-time, providing a clear perspective of garbage identification and sorting. By revolutionizing waste management through intelligent garbage segregation, this system enhances the efficiency of waste sorting, contributing to environmental preservation and sustainable waste management practices. © 2023 ieee.

关键词： Accuracy Camera data Processing DenseNet Garbage Loss User Interface

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Web Intelligence, Business Intelligence and Decision Support systems: A Challenge for Fuzzy Logic and Soft computing

Web Intelligence, Business Intelligence and Decision Support...

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International ieee Conference on intelligent systems, IS

作者： Janusz Kacprzyk Systems Research Institute Polish Academy of Sciences Warsaw Poland

Summary form only given. We present first some general remarks on challenges faced by modern information technology, notably when a human being is a relevant factor. These challenges are mainly related to inherent difficulties in solving some "meta-problems", in particular broadly perceived decision making. We assume, on the one hand, business intelligence related perspective, augmented with elements of Web intelligence, to fully use all available tools and resources. On the other hand, we assume a human centric computing perspective in the spirit of, for instance, Dertouzos's ideas. First, we present a brief account of modem approaches to real world decision making, emphasize the concept of a decision making process that involves more factors and aspects like: the use of own and external knowledge, involvement of various ,actors, aspects, etc., individual habitual domains, non-trivial rationality, different paradigms. As an example we mention Checkland's deliberative decision making (which is an important elements of his soft approach to systems analysis). After an analysis of specifics and difficulties encountered in many real world decision-making situations, we strongly advocate the use of computer based decision support systems. First, we briefly review the history of decision support systems, and then present a popular classification, starting from data driven to Web based and inter-organizational. We indicate that decision support systems should incorporate some sort of "intelligence", and we first briefly mention some views of what intelligence may mean in this concept, and then assume some more pragmatic, though limited, view of intelligent decision support systems. We indicate possible advantages of using elements of fuzzy logic and soft computing, notably, Zadeh's computing with words to be able to somehow merge the ideas presented like: human centric computing, decision making processes, intelligent decision support, etc. Finally, we present an example o

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