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

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

引用

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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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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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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Design of a Non-Volatile Ambulatory data acquisition and Control System for a Brain-Computer Interface

Design of a Non-Volatile Ambulatory Data Acquisition and Con...

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International ieee/EMBS Conference on Neural Engineering, CNE

作者： T. E. Doyle A. Ieta Z. Kucerovsky Department of Electrical and Computer Engineering McMaster University Hamilton ONT Canada Department of Engineering and Physics Murray State University Murray KY USA Department of Electrical and Computer Engineering University of Western Ontario London ONT Canada

Brain-computer interface (BCI) research is primarily conducted with equipment designed for the considerable spatial and temporal requirements needed for the observation of brain current anomalies. For ambulatory in situ evaluation the implementation of BCI models will require a smaller and inexpensive platform. As the field of ambulatory/wearable computing continues to mature, the greatest benefit will be observed in the integration of BCI into augmentative and rehabilitative prosthetics. This paper presents a specification and design for an inexpensive modular BCI platform that may be used for ambulatory data collection, processing, and control.

关键词： data acquisition Control systems Brain computer interfaces Wearable computers Electroencephalography Biomedical monitoring Computer interfaces Costs USA Councils Prosthetics

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A BP Neural Network-based Approach to intelligent Computer Image Recognition

A BP Neural Network-based Approach to Intelligent Computer I...

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Power Electronics, Computer Applications (ICPECA), ieee International Conference on

作者： Jingwen Ze Tianjin University of Technology Tianjin China

The computer image recognition model based on BP neural network can effectively identify the convergence recognition error. To solve the problems of low convergence speed and inability to quickly reduce recognition errors in the practical application of traditional image recognition methods, an optimized model for computer image recognition based on GA & BP deep neural network algorithm is proposed through computer image data acquisition and processing, image recognition model construction based on BP neural network and computer image recognition model training.

关键词： Training Image recognition Computational modeling Neural networks data models Real-time systems Power electronics

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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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Latency Reduction for Narrowband LTE with Semi-Persistent Scheduling

Latency Reduction for Narrowband LTE with Semi-Persistent Sc...

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ieee International Symposium on Wireless systems (IDAACS-SWS)

作者： Zubair Arnjad Axel Sikora Benoit Hilt Jean-Philippe Lauffenburger ivESK Offenburg University of Applied Sciences Offenburg Germany IRIMAS University of Haute Alsace Mulhouse France

ISBN: (纸本)9781538675885

The excessive control signaling in Long Term Evolution networks required for dynamic scheduling impedes the deployment of ultra-reliable low latency applications. Semi-persistent scheduling was originally designed for constant bit-rate voice applications, however, very low control overhead makes it a potential latency reduction technique in Long Term Evolution. In this paper, we investigate resource scheduling in narrowband fourth generation Long Term Evolution networks through Network Simulator (NS3) simulations. The current release of NS3 does not include a semi-persistent scheduler for Long Term Evolution module. Therefore, we developed the semi-persistent scheduling feature in NS3 to evaluate and compare the performance in terms of uplink latency. We evaluate dynamic scheduling and semi-persistent scheduling in order to analyze the impact of resource scheduling methods on up-link latency.

关键词： Long Term Evolution Dynamic scheduling Job shop scheduling Uplink Automation 3GPP Cellular networks

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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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A tool-mediated cognitive apprenticeship approach for a computer engineering course

A tool-mediated cognitive apprenticeship approach for a comp...

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International Conference on advanced Learning Technologies (ICALT)

作者： S. Murray J. Ryan C. Pahl Computer Applications University of Dublin Dublin Ireland

Teaching database engineers involves a variety of learning activities. A strong focus is on practical problems that go beyond the acquisition of knowledge. Skills and experience are equally important. We propose a virtual apprenticeship model for the knowledge- and skills-oriented Web-based education of database students. We adapt the classical cognitive apprenticeship theory to the Web context utilising scaffolding and activity theory. The choice of educational media and the forms of student interaction with the media are central success criteria.

关键词： data engineering Computer applications Computer science education Programming profession Knowledge engineering Mediation Software tools database systems Spine Collaboration

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An experimental active-memory-based network element

An experimental active-memory-based network element

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International Symposium on High Performance Distributed computing

作者： A. Asthana M. Cravatts P. Krzyzanowski AT and T Bell Laboratories Inc. Murray Hill NJ USA

We describe a network element based on an active memory named SWIM (Structured Wafer-based intelligent Memory), designed for efficient storage and manipulation of data structures. The key architectural idea in SWIM is to put some processing logic inside each memory chip that allows it to perform data manipulation operations locally and to interact with a disk or a communication line through a backend port. The processing logic is specially designed to perform operations such as pointer dereferencing, memory indirection, searching and bounds checking efficiently. The network element is built using an interconnected ensemble of such memory logic pairs. A complex processing task can now be distributed between a large number of small memory processors each doing a sub-task, while still retaining a common locus of control in the host CPU for higher level administrative and provisioning functions. We argue that active memory based processing enables more powerful, scalable and robust designs for storage and communications subsystems, that can support emerging network services, multimedia workstations and wireless PCS systems. A complete parallel hardware and software system constructed using an array of SWIM elements has been operational for over a year.< >

关键词： intelligent networks intelligent structures data structures Logic design Communication system control Robustness Multimedia systems Workstations Personal communication networks Hardware

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