Resource Type

Journal Article 29

Year

2023 1

2022 4

2020 3

2019 4

2018 4

2017 3

2016 1

2015 1

2013 1

2011 1

2009 1

2007 1

2006 1

2004 1

2002 1

2001 1

open ︾

Keywords

Artificial intelligence 3

Cognitive radio networks 2

Abstract thinking 1

Abstraction 1

AlF 3 addition 1

Artificialintelligence 1

Behavioral prescription 1

Big data scheduling 1

Bulk power grid dispatch 1

Causality 1

Channel impulse response 1

Chemometrics 1

Cloud– 1

Cognition 1

Cognitive learning 1

Cognitive radio 1

Cognitive radio network 1

Complex systems 1

Computer vision 1

open ︾

Search scope:

排序： Display mode:

Framework and case study of cognitive maintenance in Industry 4.0 Special Feature on Industrial Internet

Bao-rui Li, Yi Wang, Guo-hong Dai, Ke-sheng Wang,kesheng.wang@ntnu.no

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 11,   Pages 1493-1504 doi: 10.1631/FITEE.1900193

Abstract: We present a new framework for (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent approaches and intelligent decision-making techniques, which can be used by maintenance professionals who are working with . The systems will provide technical solutions to real-time online maintenance tasks, avoid outages due to equipment failures, and ensure the continuous and healthy operation of equipment and manufacturing assets. The implementation framework of CM consists of four modules, i.e., cyber-physical system, Internet of Things, data mining, and Internet of Services. In the data mining module, fault diagnosis and prediction are realized by methods. In the case study, the backlash error of cutting-edge machine tools is taken as an example. We use a deep belief network to predict the backlash of the machine tool, so as to predict the possible failure of the machine tool, and realize the strategy of CM. Through the case study, we discuss the significance of implementing CM for cutting- edge equipment, and the framework of CM implementation has been verified. Some CM system applications in manufacturing enterprises are summarized.

Keywords： 认知维护；工业4.0；尖端设备；深度学习；绿色监视器；智能制造工厂    

HTML PDF Collect

认知中继三跳网络联合优化 Article

澄 赵,万良 王,信威 姚,双华 杨

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 2,   Pages 253-261 doi: 10.1631/FITEE.1601414

Abstract: 认知中继网络中，传输的吞吐量和传输距离一直是衡量性能的重要指标。现有的研究多数都集中在两跳网络的优化，但其也存在着传输距离不长，只能进行单项传输等缺点。本文提出了一种新的使用认知中继的三跳网络传输方案，通过三阶段的传输过程，实现了次级用户之间的双向传输。同时，引入了叠加编码技术来处理网络中双接收节点的情况。

Keywords： 解码转发；三跳；认知中继网络；时间功率分配；叠加编码    

HTML PDF Collect

混合-增强智能：协作与认知 Review

南宁 郑,子熠 刘,鹏举 任,永强 马,仕韬 陈,思雨 余,建儒 薛,霸东 陈,飞跃 王

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 2,   Pages 153-179 doi: 10.1631/FITEE.1700053

Abstract: 由于人类面临的许多问题具有不确定性、脆弱性和开放性，任何智能程度的机器都无法完全取代人类，这就需要将人的作用或人的认知模型引入到人工智能系统中，形成混合-增强智能的形态，这种形态是人工智能或机器智能的可行的混合-增强智能可以分为两类基本形式：一类是人在回路的人机协同混合增强智能，另一类是将认知模型嵌入机器学习系统中，形成基于认知计算的混合智能。本文讨论人机协同的混合-增强智能的基本框架，以及基于认知计算的混合-增强智能的基本要素：直觉推理与因果模型、记忆和知识演化；特别论述了直觉推理在复杂问题求解中的作用和基本原理，以及基于记忆与推理的视觉场景理解的认知学习网络；阐述了竞争-对抗式认知学习方法，并讨论了其在自动驾驶方面的应用；最后给出混合-增强智能在相关领域的典型应用。

Keywords： 人-机协同；混合增强智能；认知计算；直觉推理；因果模型；认知映射；视觉场景理解；自主驾驶汽车    

HTML PDF Collect

Study on Hengsha deepwater port location and maintainability in Yangtze estuary

Lou Fei,Ji Lan,Chen Zhong,Wang Dawei

Strategic Study of CAE 2013, Volume 15, Issue 6,   Pages 108-112

Abstract:

Hengsha east shoal is a large mouth bar in Yangtze estuary. The main problem of building large excavated-in deepwater harbor basin here is the maintainability of the basin and waterway. In this paper, on the basis of the characteristics of current and sediment, the basin and its entrance sites selection and the maintainability of the basin and waterway are discussed. The results show that the entrance of the basin should be set in the east side of Hengsha east shoal and on the south of Jigu reef, and towards southeast. The entrance and waterway should be built in the area where the depth is greater than 10 m. If do so, the tidal prism is large; the siltation is small, and the maintainability is good.

Keywords： Yangtze estuary     Hengsha east shoal     excavated-in deepwater harbor basin     site selection     maintainability    

HTML PDF Collect

Lifecycle Management and Maintenance of Marine Bridge Engineering

Liu Muyu, Liang Lei, Wu Hao, Xu Gang, Li Qian

Strategic Study of CAE 2019, Volume 21, Issue 3,   Pages 25-30 doi: 10.15302/J-SSCAE-2019.03.013

Abstract:

Marine bridge engineering in China is continuously developing to the offshore, deep-sea, long-distance, and large-scale directions. However, due to its harsh natural environment and complex geological and loading conditions, there still exist many problems in health monitoring, measurement technology, inspection technology, and maintenance-management for the lifecycle of marine bridge engineering. Therefore, after summarizing the existing problems in lifecycle management and maintenance of bridges, this paper proposes several key technologies for marine bridge development, including health monitoring based on multi-parameter, high-reliability, large-capacity, and long-distance optical-fiber sensing; space–air–ground–sea integrated measurement; automated inspection; and intelligent management and maintenance platforms. Meanwhile, this paper studies the difficulties and development directions of these technologies, and explores development strategies and recommendations for the lifecycle management and maintenance technology of marine bridge engineering, thereby providing technical support for the construction and operation safety of marine bridge engineering.

Keywords： marine bridge engineering     lifecycle management     health monitoring     automated inspection     engineering mapping     intelligent maintenance    

HTML PDF Collect

Achieving Cognitive Mass Personalization via the Self-X Cognitive Manufacturing Network: An Industrial Knowledge Graph- and Graph Embedding-Enabled Pathway

Xinyu Li, Pai Zheng, Jinsong Bao, Liang Gao, Xun Xu

Engineering 2023, Volume 22, Issue 3,   Pages 14-19 doi: 10.1016/j.eng.2021.08.018

HTML PDF Collect

Multi-user rate and power analysis in a cognitive radio network with massive multi-input multi-output None

Shang LIU, Ishtiaq AHMAD, Ping ZHANG, Zhi ZHANG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 5,   Pages 674-684 doi: 10.1631/FITEE.1700081

Abstract: This paper discusses transmission performance and power allocation strategies in an underlay cognitive radio (CR) network that contains relay and massive multi-input multi-output (MIMO). The downlink transmission performance of a relay-aided massive MIMO network without CR is derived. By using the power distribution criteria, the kth user’s asymptotic signal to interference and noise ratio (SINR) is independent of fast fading. When the ratio between the base station (BS) antennas and the relay antennas becomes large enough, the transmission performance of the whole system is independent of BS-to-relay channel parameters and relates only to the relay-to-users stage. Then cognitive transmission performances of primary users (PUs) and secondary users (SUs) in an underlay CR network with massive MIMO are derived under perfect and imperfect channel state information (CSI), including the end-to-end SINR and achievable sum rate. When the numbers of primary base station (PBS) antennas, secondary base station (SBS) antennas, and relay antennas become infinite, the asymptotic SINR of the PU and SU is independent of fast fading. The interference between the primary network and secondary network can be canceled asymptotically. Transmission performance does not include the interference temperature. The secondary network can use its peak power to transmit signals without causing any interference to the primary network. Interestingly, when the antenna ratio becomes large enough, the asymptotic sum rate equals half of the rate of a single-hop single-antenna K-user system without fast fading. Next, the PUs’ utility function is defined. The optimal relay power is derived to maximize the utility function. The numerical results verify our analysis. The relationships between the transmission rate and the antenna number, relay power, and antenna ratio are simulated. We show that the massive MIMO with linear pre-coding can mitigate asymptotically the interference in a multi-user underlay CR network. The primary and secondary networks can operate independently.

Keywords： Massive multi-input multi-output     Cognitive radio     Relay network     Transmission rate     Power analysis    

HTML PDF Collect

Physical layer security of underlay cognitive radio using maximal ratio combining Article

Hui ZHAO,Dan-yang WANG,Chao-qing TANG,Ya-ping LIU,Gao-feng PAN,Ting-ting LI,Yun-fei CHEN

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 9,   Pages 929-937 doi: 10.1631/FITEE.1500351

Abstract: We investigate the secrecy outage performance of maximal ratio combining (MRC) in cognitive radio networks over Rayleigh fading channels. In a single-input multiple-output wiretap system, we consider a secondary user (SU-TX) that transmits confidential messages to another secondary user (SU-RX) equipped with ( 1) antennas where the MRC technique is adopted to improve its received signal-to-noise ratio. Meanwhile, an eavesdropper equipped with ( 1) antennas adopts the MRC scheme to overhear the information between SU-TX and SU-RX. SU-TX adopts the underlay strategy to guarantee the service quality of the primary user without spectrum sensing. We derive the closed-form expressions for an exact and asymptotic secrecy outage probability.

Keywords： Cognitive radio networks     Maximal ratio combining     Secrecy outage probability     Single-input multiple-output    

HTML PDF Collect

Parallel cognition: hybrid intelligence for human-machine interaction and management Research Article

Peijun YE, Xiao WANG, Wenbo ZHENG, Qinglai WEI, Fei-Yue WANG

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1765-1779 doi: 10.1631/FITEE.2100335

Abstract: As an interdisciplinary research approach, traditional cognitive science adopts mainly the experiment, induction, modeling, and validation paradigm. Such models are sometimes not applicable in cyber-physical-social-systems (CPSSs), where the large number of human users involves severe heterogeneity and dynamics. To reduce the decision-making conflicts between people and machines in human-centered systems, we propose a new research paradigm called parallel cognition that uses the system of intelligent techniques to investigate cognitive activities and functionals in three stages: descriptive cognition based on artificial cognitive systems (ACSs), predictive cognition with computational deliberation experiments, and prescriptive cognition via parallel . To make iteration of these stages constantly on-line, a hybrid learning method based on both a psychological model and user behavioral data is further proposed to adaptively learn an individual's cognitive knowledge. Preliminary experiments on two representative scenarios, urban travel and cognitive visual reasoning, indicate that our parallel cognition learning is effective and feasible for human , and can thus facilitate human-machine cooperation in both complex engineering and social systems.

Keywords： Cognitive learning     Artificial intelligence     Behavioral prescription    

HTML PDF Collect

Smart Society and Artificial Intelligence: Big Data Scheduling and the Global Standard Method Applied to Smart Maintenance Article

Ruben Foresti, Stefano Rossi, Matteo Magnani, Corrado Guarino Lo Bianco, Nicola Delmonte

Engineering 2020, Volume 6, Issue 7,   Pages 835-846 doi: 10.1016/j.eng.2019.11.014

Abstract:

The implementation of artificial intelligence (AI) in a smart society, in which the analysis of human habits is mandatory, requires automated data scheduling and analysis using smart applications, a smart infrastructure, smart systems, and a smart network. In this context, which is characterized by a large gap between training and operative processes, a dedicated method is required to manage and extract the massive amount of data and the related information mining. The method presented in this work aims to reduce this gap with near-zero-failure advanced diagnostics (AD) for smart management, which is exploitable in any context of Society 5.0, thus reducing the risk factors at all management levels and ensuring quality and sustainability. We have also developed innovative applications for a humancentered management system to support scheduling in the maintenance of operative processes, for reducing training costs, for improving production yield, and for creating a human–machine cyberspace for smart infrastructure design. The results obtained in 12 international companies demonstrate a possible global standardization of operative processes, leading to the design of a near-zero-failure intelligent system that is able to learn and upgrade itself. Our new method provides guidance for selecting the new generation of intelligent manufacturing and smart systems in order to optimize human–machine interactions, with the related smart maintenance and education.

Keywords： Smart maintenance     Smart society     Artificial intelligence     Human-centered management system     Big data scheduling     Global standard method     Society 5.0     Industry 4.0    

HTML PDF Collect

On detecting primary user emulation attack using channel impulse response in the cognitive radio network Article

Qiao-mu JIANG, Hui-fang CHEN, Lei XIE, Kuang WANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1665-1676 doi: 10.1631/FITEE.1700203

Abstract: Cognitive radio is an effective technology to alleviate the spectrum resource scarcity problem by opportunistically allocating the spare spectrum to unauthorized users. However, a serious denial-of-service (DoS) attack, named the ‘primary user emulation attack (PUEA)’, exists in the network to deteriorate the system performance. In this paper, we propose a PUEA detection method that exploits the radio channel information to detect the PUEA in the cognitive radio network. In the proposed method, the uniqueness of the channel impulse response (CIR) between the secondary user (SU) and the signal source is used to determine whether the received signal is transmitted by the primary user (PU) or the primary user emulator (PUE). The closed-form expressions for the false-alarm probability and the detection probability of the proposed PUEA detection method are derived. In addition, a modified subspace-based blind channel estimation method is presented to estimate the CIR, in order for the proposed PUEA detection method to work in the scenario where the SU has no prior knowledge about the structure and content of the PU signal. Numerical results show that the proposed PUEA detection method performs well although the difference in channel characteristics between the PU and PUE is small.

Keywords： Cognitive radio network     Primary user emulation attack     Subspace-based blind channel estimation     Channel impulse response    

HTML PDF Collect

A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps Article

Weichao Yue、 Weihua Gui、 Xiaofang Chen、 Zhaohui Zeng、 Yongfang Xie

Engineering 2019, Volume 5, Issue 6,   Pages 1060-1076 doi: 10.1016/j.eng.2019.10.005

Abstract:

In the aluminum reduction process, aluminum fluoride (AlF3) is added to lower the liquidus temperature of the electrolyte and increase the electrolytic efficiency. Making the decision on the amount of AlF3 addition (referred to in this work as MDAAA) is a complex and knowledge-based task that must take into consideration a variety of interrelated functions; in practice, this decision-making step is performed manually. Due to technician subjectivity and the complexity of the aluminum reduction cell, it is difficult to guarantee the accuracy of MDAAA based on knowledge-driven or data-driven methods alone. Existing strategies for MDAAA have difficulty covering these complex causalities. In this work, a data and knowledge collaboration strategy for MDAAA based on augmented fuzzy cognitive maps (FCMs) is proposed. In the proposed strategy, the fuzzy rules are extracted by extended fuzzy k-means (EFKM) and fuzzy decision trees, which are used to amend the initial structure provided by experts. The state transition algorithm (STA) is introduced to detect weight matrices that lead the FCMs to desired steady states. This study then experimentally compares the proposed strategy with some existing research. The results of the comparison show that the speed of FCMs convergence into a stable region based on the STA using the proposed strategy is faster than when using the differential Hebbian learning (DHL), particle swarm optimization (PSO), or genetic algorithm (GA) strategies. In addition, the accuracy of MDAAA based on the proposed method is better than those based on other methods. Accordingly, this paper provides a feasible and effective strategy for MDAAA.

Keywords： AlF 3 addition     Fuzzy cognitive maps     Learning algorithms     State transition algorithm     Fuzzy decision trees    

HTML PDF Collect

The engineering and technology progress of CAR-CA

Zhao Qinping

Strategic Study of CAE 2009, Volume 11, Issue 10,   Pages 25-31

Abstract:

It is a new aspect of engineering science that uses augmented reality and collaboration technology to aid the design and maintenance of large equipment. To meet the requirement of the design and manufacture of commercial aircraft in China, CAR-CA(collaborative augmented reality for commercial aircraft design & maintenance) is under development now to aid the cockpit design and training of components disassembly and assembly. This paper introduced the engineering and technology progress of CAR-CA, including the system architecture, system components, technology researches and system application prospect, etc.

Keywords： augmented reality     collaboration     cockpit     design     maintenance    

HTML PDF Collect

PASS - BDI Model for Software Agent

Fan Wei,Chen Zengqiang,Yuan Zhuzhi

Strategic Study of CAE 2004, Volume 6, Issue 6,   Pages 43-49

Abstract:

Recent research on software agent is mainly based on rational agent theories that have been presented by Bratman and its core is to build BDI models for agent. But the models can not present the active cognitive processes of agent, and it is hard to richly present the relations between agent problem solving and agent mental states. Because it is not easy to build the explicit corresponding relations between the theory model and the model structure, agent rational models are difficult to realize. This paper introduces a psychologically recognized model-PASS (planning, attention, simultaneous processing and successive processing) into the study about intelligent agent, builds a new agent model named as PASS-BDI, describes the mental states, cognitive processes and whole behaviors with pi-calculus at length and strengthens the active cognitive attributes of agent. Because having built the explicit corresponding relations between this theory model and the model structure, it is easy to program in AOP practice. An application of the model in MAS is presented at last.

Keywords： agent     pi-calculus     cognitive processes     mental state    

HTML PDF Collect

Determination Model for Replacement of Water Pipeline

Cui Hongsheng,Zhang Hongwei,Niu Zhiguang,Fu Yufen

Strategic Study of CAE 2007, Volume 9, Issue 9,   Pages 68-71

Abstract:

A fund distribution model for water pipeline replacement at the level of limited fund is established.  By analyzing maintenance fee of pipe network and construction fee,  and decreasing the difference of pipeline maintenance fee before and after replacement at the most,  the pipeline needed to be replaced is determined.  The establishment of model makes construction fund be utilized fully,  and decreases pipeline leakage loss most effcfivedy,  and provides theoretical support and guidance for water supply department to utilize fund reasonably,  control leakage loss and production and marketing difference ratio effectively.

Keywords： water pipeline     maintenance fee     replacement fee     fund distribution    

HTML PDF Collect

Title Author Date Type Operation

Framework and case study of cognitive maintenance in Industry 4.0

Bao-rui Li, Yi Wang, Guo-hong Dai, Ke-sheng Wang,kesheng.wang@ntnu.no

Journal Article

认知中继三跳网络联合优化

澄 赵,万良 王,信威 姚,双华 杨

Journal Article

混合-增强智能：协作与认知

南宁 郑,子熠 刘,鹏举 任,永强 马,仕韬 陈,思雨 余,建儒 薛,霸东 陈,飞跃 王

Journal Article

Study on Hengsha deepwater port location and maintainability in Yangtze estuary

Lou Fei,Ji Lan,Chen Zhong,Wang Dawei

Journal Article

Lifecycle Management and Maintenance of Marine Bridge Engineering

Liu Muyu, Liang Lei, Wu Hao, Xu Gang, Li Qian

Journal Article

Achieving Cognitive Mass Personalization via the Self-X Cognitive Manufacturing Network: An Industrial Knowledge Graph- and Graph Embedding-Enabled Pathway

Xinyu Li, Pai Zheng, Jinsong Bao, Liang Gao, Xun Xu

Journal Article

Multi-user rate and power analysis in a cognitive radio network with massive multi-input multi-output

Shang LIU, Ishtiaq AHMAD, Ping ZHANG, Zhi ZHANG

Journal Article

Physical layer security of underlay cognitive radio using maximal ratio combining

Hui ZHAO,Dan-yang WANG,Chao-qing TANG,Ya-ping LIU,Gao-feng PAN,Ting-ting LI,Yun-fei CHEN

Journal Article

Parallel cognition: hybrid intelligence for human-machine interaction and management

Peijun YE, Xiao WANG, Wenbo ZHENG, Qinglai WEI, Fei-Yue WANG

Journal Article

Smart Society and Artificial Intelligence: Big Data Scheduling and the Global Standard Method Applied to Smart Maintenance

Ruben Foresti, Stefano Rossi, Matteo Magnani, Corrado Guarino Lo Bianco, Nicola Delmonte

Journal Article

On detecting primary user emulation attack using channel impulse response in the cognitive radio network

Qiao-mu JIANG, Hui-fang CHEN, Lei XIE, Kuang WANG

Journal Article

A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps

Weichao Yue、 Weihua Gui、 Xiaofang Chen、 Zhaohui Zeng、 Yongfang Xie

Journal Article

The engineering and technology progress of CAR-CA

Zhao Qinping

Journal Article

PASS - BDI Model for Software Agent

Fan Wei,Chen Zengqiang,Yuan Zhuzhi

Journal Article

Determination Model for Replacement of Water Pipeline

Cui Hongsheng,Zhang Hongwei,Niu Zhiguang,Fu Yufen

Journal Article