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Cyber Security Against Denial of service of Attacks on Load Frequency Control of Multi-area Power systems

Cyber Security Against Denial of Service of Attacks on Load ...

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international conference on Life system Modeling and Simulation (LSMS) / international conference on Intelligent Computing for Sustainable Energy and Environment (ICSEE)

作者： Shen, Yubin Fei, Minrui Du, Dajun Zhang, Wenjun Stankovic, Srdjan Rakic, Aleksandar Shanghai Univ Sch Mechatron Engn & Automat Dept Automat Shanghai Key Lab Power Stn Automat Technol Shanghai 200072 Peoples R China Shanghai Univ Sch Commun & Informat Engn Shanghai Peoples R China Univ Belgrade Sch Elect Engn Belgrade Serbia

ISBN: (纸本)9789811063640;9789811063633

While open communication infrastructures are embedded into multi-area power systems to support data transmittion, it make communication channels vulnerable to cyber attacks, reliability of power systems is affected. This paper studies the load frequency control (LFC) of multi-area power systems under DoS attacks. The state space model of power systems under DoS attacks is formulated, where event-triggered control scheme is integrated for the multi-area power systems under DoS attacks. By utilizing average dwell time design approach, exponential stability and L-2-gain of the multi-area power systems can be obtained for event-triggered LFC scheme under DoS attacks, if choosing an unavailability rate of communication channels for DoS attacks properly. Finally, the example shows that the convergences of frequency deviation of three-area power systems are compared under different DoS attack scenarios, when the proportion of the total time of DoS attacks can obtain the result properly.

关键词： Denial-of-service (DoS) attacks Multi-area power systems Load frequency control (LFC) Event-triggered mechanism

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Hybrid. poly: An Interactive Large-scale In-memory Analytical Polystore 17

Hybrid. poly: An Interactive Large-scale In-memory Analytica...

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17th IEEE international conference on Data Mining (ICDMW)

作者： Podkorytov, Maksim Soderman, Dylan Gubanov, Michael Univ Texas San Antonio Dept Comp Sci San Antonio TX 78249 USA

ISBN: (纸本)9781538638002

Anecdotal evidence suggests that the variety of Big data is one of the most challenging problems in computer science research today [Stonebraker, 2012], [Ou et al., 2017], [Guo et al., 2016], [Bai et al., 2016]. First, Big data comes at us from a myriad of data sources, hence its shape and flavor differ. Second, hundreds of data management systems which work with Big data support different APIs and storage/indexing schemes while exposing data to the users through the data model lens, specific to each system. These differences can impede work for users who simply want an accessible interface which can handle relevant unstructured data that is stored within a back-end system. Naturally, such discrepancies in formats, sizes, and shapes can also complicate the development of analytical algorithms which could be implemented on top of large-scale, heterogeneous datasets. [Gubanov, 2017b] introduced a consolidated polystore engine, designed to seamlessly ingest and query any type of large-scale data. In this paper we describe a variety of complex analytical workloads that can be processed by such polystore as well as associated research challenges.

关键词： Large-scale data management Big data analytics In-memory data management Polystore Polyfuse Query optimization Linear algebra Relational algebra Web search Data Integration Music search Machine Learning Locality-sensitive Hashing computer vision

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DNS Configurations and Its Security Analyzing via Resource Records of the Top-Level Domains 11

DNS Configurations and Its Security Analyzing via Resource R...

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2017 11th IEEE international conference on Anti-counterfeiting,Security,and Identification(ASID)

作者： Mengyuan Wang Zhaoxin Zhang Haiyan Xu School of Computer Science and Technology Harbin Institute of Technology

ISBN: (纸本)9781538605349;9781538605332

Top-level domains play an important role in domain name system. Close attention should be paid to security of top level domains. In this paper, we found many configuration anomalies of top-level domains by analyzing their resource records. We got resource records of top-level domains from root name servers and authoritative servers of top-level domains. By comparing these resource records, we observed the anomalies in top-level domains. For example, there are 8 servers shared by more than one hundred top-level domains;Some TTL fields or SERIAL fields of resource records obtained on each NS servers of the same top-level domain were inconsistent;some authoritative servers of top-level domains were unreachable. Those anomalies may affect the availability of top-level domains. We hope that these anomalies can draw top-level domain administrators' attention to security of top-level domains.

关键词： top-level domain resource record DNS configuration

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Fast and Efficient Integration of Human Upper-Body Detection and Orientation Estimation in RGB-D Video 9

Fast and Efficient Integration of Human Upper-Body Detection...

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2017 9th IEEE international conference on Communication Software and Networks (ICCSN 2017)

作者： Tao Ji Leibo Liu Wenping Zhu Jinghe Wei Shaojun Wei Institute of Microelectronics Tsinghua University Institute of Microelectronics China Key System & Integrated Circuit Co.Ltd

ISBN: (纸本)9781509038237;9781509038220

Automatic and accurate human upper-body detection and orientation estimation have great practical value in several computer vision applications. Most previous works on human upper-body orientation estimation assume that the human upper-body region is already detected and aligned. However, this is not the case in many real-world scenarios. Additional human detector is essential which is usually much slower than orientation estimator. In this paper, we propose a novel approach to single-frame human upper-body detection and orientation estimation in RGB-D images. Unlike previous works which address human detection and orientation estimation separately with different models, our method involves a random forest framework to approach both in a unified model. The whole algorithm, including human detection and orientation estimation, achieves 40 fps in 640 p resolution on a single laptop CPU without any GPU acceleration. The experimental results show the effectiveness of the proposed method.

关键词： RGB-D human detection human orientation estimation intergration framework random forest

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Technology of Sound Velocity Correction for Multi-beam Bathymetry Sounding

Technology of Sound Velocity Correction for Multi-beam Bathy...

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2018 international conference on computer science, Electronics and Communication Engineering（CSECE2018）

作者： Weiming Xu Kai Ma Department of Hydrography and Cartography Dalian Naval Academy

The multi-beam echo sounding system was the most effective instrument to detect the seabed topography. In order to reduce the seafloor terrain distortion caused by the representative error of sound velocity profile（SVP）, the indirection adjustment inversion method was introduced after analyzing the impact of the sound profile measuring error on the seabed terrain. To testify the proposed indirection adjustment technology, two group experiments were designed, in which Group 1 used the adjustment inversion method to correct the SVP data with the small error while Group 2 utilized the same method to correct the SVP data with the large error. The results of field experimental data are shown that: the standard deviation（STD） of the inversing SVP is reduced by 64.2% and that of the single Ping seabed topographic reduce 80.7%. The computational efficiency of adjustment inversion method is better than that of the substitute SVP method. Additionally, the presented approach, which can overcome many disadvantages of the manual approach to SVP correction, is superior to that of the substitution SVP and optimizing the structure of SVP.

关键词： multi-beam bathymetry souding sound correction seabed topography indrection adjustment

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Time portability evaluation of RCNN technique of OD object detection - Machine learning (artificial intelligence)

Time portability evaluation of RCNN technique of OD object d...

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2017 international conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017

作者： Gupta, Anitya Kumar Computer Science - Cloud Computing Defense Research and Development Organization Tirampur New Delhi India

ISBN: (纸本)9781538618868

This paper proposes a Quick Locale based Convolutional system strategy (Quick R-CNN) for question recognition. Quick R-CNN expands on past work to effectively characterize ob-ject recommendations utilizing profound convolutional systems. Com-pared to past work, Quick R-CNN utilizes a few in-novations to enhance preparing and testing speed while likewise expanding identification precision. Quick R-CNN trains the profound VGG16 arrange 9 quicker than R-CNN, is 213 speedier at test-time, and accomplishes a higher Guide on PASCAL VOC 2012. Contrasted with SPPnet, Quick R-CNN trains VGG16 3 quicker, tests 10 speedier, and is more exact. Quick R-CNN is actualized in Python and C++ (utilizing Caffe) and is accessible under the open-source MIT Permit. © 2017 IEEE.

关键词： Python

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Advanced migraine prediction simulation system 49

Advanced migraine prediction simulation system

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49th Summer computer Simulation conference, SCSC 2017, Part of the 2017 Summer Simulation Multi-conference, SummerSim 2017

作者： Pagán, Josué Moya, José M. Mittal, Saurabh Ayala, José L. Department of Computer Architecture and Automation CCS-Center for Computational Simulation Complutense University of Madrid Madrid Spain LSI - Electronic Engineering Department CCS-Center for Computational Simulation Technical University of Madrid Madrid Spain Complex Systems Research Lab Dunip Technologies LLC HerndonVA United States Department of Computer Architecture and Automation Computer Science Faculty Complutense University of Madrid Spain

ISBN: (纸本)9781510838284

In the Internet of Things (IoT) era, there is growing interest in wireless monitoring sensors for detection, classification and prediction of health symptoms. The prediction of symptoms in chronic diseases such as migraines brings new hope to improve patients' lives. The prediction of a migraine symptomatic event through monitoring hemodynamic variables has been previously demonstrated in our earlier work. In this paper, a simulation-based approach for a real-Time migraine prediction system is described. The simulation has been implemented using the specifications of the formal description language Discrete EVent systems (DEVS). The simulation system is a proof of concept that is ready for testing in a real-world ambulatory monitoring environment. The results obtained encourage developing a hardware/software (HW/SW) cosimulation system that incorporates Hardware-in-The-Loop (HIL) components as prior step to the expensive and slow hardware implementation of a complete migraine prediction device. When such a system is used in a real-Time setting, it can simulate failures in sensors and trigger alarms for active patient response. © 2017 Society for Modeling & Simulation international (SCS).

关键词： Forecasting

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The research of attribute granular computing model in cognitive and decision-making 2nd

The research of attribute granular computing model in cognit...

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2nd IFIP TC 12 international conference on Intelligence science, ICIS 2017

作者： Zhou, Ruqi Zhou, Yuepeng Department of Computer Science Guangdong University of Education Guangzhou510303 China School of Data and Computer Science Sun Yat-Sen University Guangzhou510006 China

ISBN: (纸本)9783319681207

The cognitive activities of human beings are complicate and diversified. So far, there hasn’t been a universal cognitive model. Each cognitive model generally only represents cognitive features in one or some aspects. Therefore, this paper aims to, based on the granular computing theory and principles, and with attributes and change laws as the main objects of the cognitive course, proposes a cognitive model which not only can describe the thing through attributes to represent the change law, but also can simulate the cognitive decision-making course with respect to the attribute change of the thing. Attribute granular computing, based on qualitative mapping, can simulate the cognitive functions of human brain, such as granulation, organization and causation. Petri net has asynchronous, concurrent and uncertainty characteristics, which is similar to the characteristics of some cognitive activities in human thinking process. Petri net is extended based on the basic concept and logic calculation rules of attribute granular computing in this paper. Some basic elements of a cognitive system, such as knowledge representation, reasoning, learning and memory mode are initially showed in the extended Petri net. The results show that this method can reflect the cognitive process of uncertainty identification and decision-making in a certain extent. © IFIP international Federation for Information Processing 2017.

关键词： Decision making

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Pelee: a real-time object detection system on mobile devices 18

Pelee: a real-time object detection system on mobile devices

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Proceedings of the 32nd international conference on Neural Information Processing systems

作者： Robert J. Wang Xiang Li Charles X. Ling Department of Computer Science University of Western Ontario London Ontario Canada

An increasing need of running Convolutional Neural Network (CNN) models on mobile devices with limited computing power and memory resource encourages studies on efficient model design. A number of efficient architectures have been proposed in recent years, for example, MobileNet, ShuffleNet, and MobileNetV2. However, all these models are heavily dependent on depthwise separable convolution which lacks efficient implementation in most deep learning frameworks. In this study, we propose an efficient architecture named PeleeNet, which is built with conventional convolution instead. On ImageNet ILSVRC 2012 dataset, our proposed PeleeNet achieves a higher accuracy and over 1.8 times faster speed than MobileNet and MobileNetV2 on NVIDIA TX2. Meanwhile, PeleeNet is only 66% of the model size of MobileNet. We then propose a real-time object detection system by combining PeleeNet with Single Shot MultiBox Detector (SSD) method and optimizing the architecture for fast speed. Our proposed detection system2, named Pelee, achieves 76.4% mAP (mean average precision) on PASCAL VOC2007 and 22.4 mAP on MS COCO dataset at the speed of 23.6 FPS on iPhone 8 and 125 FPS on NVIDIA TX2. The result on COCO outperforms YOLOv2 in consideration of a higher precision, 13.6 times lower computational cost and 11.3 times smaller model size.

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EEG Classification for Motor Imagery BCI Using Phase-only Features Extracted by Independent Component Analysis 39

EEG Classification for Motor Imagery BCI Using Phase-only Fe...

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39th Annual international conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Qureshi, Muhammad Naveed Iqbal Cho, Dongrae Lee, Boreom GIST Dept Biomed Sci & Engn BMSE IIT Gwangju South Korea

ISBN: (纸本)9781509028092

The accurate classification of the electroencephalography (EEG) signals is the most important task towards the development of a reliable motor imagery brain-computer interface (MI-BCI) system. In this study, we utilized a publically available BCI Competition-IV 2008 dataset IIa. This study address to the binary classification problem of the motor imagery EEG data by using a sigmoid activation function-based extreme learning machines (ELM). We proposed a novel method of extracting the features from the EEG signals by first applying the independent component analysis (ICA) on the time series data and transforming the ICA time series data into Fourier domain and then extract the phase information from the Fourier spectrum. This phase information was further used to calculate the maximized cross-correlation connectivity matrix. The upper diagonal of this matrix was then vectorized and it serves as the basic feature for the ELM classification framework. By using the phase-only features we achieved 97.80% (p < 0.0022) nested cross-validated classification accuracy. In addition, this process is relatively computationally inexpensive. Thus, it can be an excellent candidate for the motor imagery BCI applications.

关键词： Electroencephalography Feature extraction Time series analysis Classification algorithms Brain-computer interfaces Standards Independent component analysis

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