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Self-Awareness for Autonomous systems

PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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Analysis of possibilities of alleviating repercussions caused by large disturbances in the power system

Analysis of possibilities of alleviating repercussions cause...

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Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2018)

作者： Robert Noskov Ivica Petrović Hrvoje Glavaš Damir Šljivac Tomislav Barić Croatian Transmission System Operator Ltd. Vukovarska cesta 217 31000 Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Ulica Kneza Trpimira 2b 31000 Osijek Croatia

ISBN: (纸本)9781839531330

Various EU regulations have established rules for accessing the electricity exchange grid in order to ensure proper functioning of the electricity market while maintaining a proper level of system security. system security depends on the technical capabilities of its components to withstand disturbances and to help prevent serious interruptions or to re-establish system operation after a breakdown occurs. This paper generally gives a theoretical and practical overview of measures for the automatized protection against voltage disruption and reduction of the active or reactive load of lines or transformers in the subsystem PrP Osijek. In addition to automatic protection, measures of excluding certain elements of the grid will be shown, as well as functions for blocking/activating the regulation of grid elements in order to reduce active and reactive loads of lines or transformers. The analysis gives the effect of some measurements on a real transmission grid model. The model had to be adjusted with the grid state and load requirements that anticipated various unfavourable scenarios, which could cause the power system to break down.

关键词： EES AUTOMATED PROTECTION DISTURBANCES

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Fast network restoration by partitioning of parallel black start zones

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Journal of engineering 2017年第8期2017卷 418-426页

作者： Shen, Cong Kaufmann, Paul Braun, Martin Energy Management and Power System Operation Department Kassel University Wilhelmshoeher Allee 73 Kassel Germany Faculty for Electrical Engineering Computer Science and Mathematics University of Paderborn Warburger Str.100 Paderborn Germany Department Distribution System Operation Fraunhofer IWES Koenigstor 59 Kassel Germany

The restoration of large electrical power systems after a blackout is often a challenging task. A typical restoration process includes the partitioning of the power systems into subsystems and the successive booting of large non-black start (NBS) units by black start (BS) units. A proper partitioning of the starting zone can reduce the restoration time significantly. This paper investigates a novel network partitioning algorithm to improve the restoration time and ratio of generation and load in each subsystem. The proposed algorithm consists of three stages. In the first stage, the number of subsystems is determined by the number of available BS units and their electrical distance. In the second stage, NBS units are assigned to each subsystem in the way that the rebooting time difference among subsystems is minimised. In the third stage, the substations are assigned to one of the subsystems to achieve the optimal ratio of generation and load in each subsystem. With the proposed algorithm, the switching transient and steady-state over-voltages at the receiving end of unload lines are kept within acceptable ranges and the self-excitation phenomenon does not occur in the subsystems. Furthermore, the start-up sequence of NBS units in each subsystem is determined simultaneously. The proposed algorithm is flexible and can be adjusted very easily according to the real status of the power system. The validity and performance of the proposed approach is demonstrated through simulations using a New England 39 Nodes network and a real network from south China. © 2017 Institution of engineering and Technology. All rights reserved.

关键词： Restoration

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Retracted: Design of Decision Support system Determination of Inventory Inventory Using Single Exponential Smoothing Forecasting Method

Retracted: Design of Decision Support System Determination o...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information systems, and Information Technology, WMA-Mathcomtech 2018

作者： Iqbal, Muhammad Abdullah, Dahlan Hartono, H. Erliana, Cut Ita Sriadhi, S. Nurmawati, N. Prasnowo, M Adhi Hasibuan, Abdurrozzaq Iskandar, Akbar Saddhono, Kundharu Abdussakir, A. Musa, Hastuti Setiawan, Muhammad Ikhsan Sagala, Youmeni Siahaan, Rumiris Sinaga, Eka Mayastika Syahputri, Anggraini Milanie, Feby Aspan, Henry Khaddafi, Muammar Department of Computer System Universitas Pembangunan Panca Budi Medan Indonesia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Computer Science STMIK IBBI Medan Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Electrical Engineering Universitas Negeri Medan Indonesia Faculty of Industry Technique University of 45 Surabaya Indonesia Department of Industrial Engineering Universitas Maarif Hasyim Latif Sidoarjo Indonesia Faculty of Engineering Universitas Islam Sumatera UtaraMedan Indonesia Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Department of Mathematics Education State Islamic University of Malang Malang Indonesia Department of Mathematics Universitas Muhammadiyah Parepare Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia STIE Bina Karya Tebing Tinggi Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia

The development of information and communication technology at this time has touched all sides of life. Almost no side of human life is not touched by this information technology, which is more synonymous with the world of computerization. No exception also with the computerization that is popular in the corporate environment and government agencies. If in ancient times everything was still done manually. However, at this time all leaders and management have realized the importance of this information technology products that can facilitate them in carrying out the day-to-day corporate functions. Decision Making system of goods purchasing is one of the determinants of the accumulation of goods. If the decision is taken right then stockpiling of goods can be avoided. In this thesis the authors designed a web-based system that helps Management in making the decision of the purchase amount of goods. the system was developed by using Microsoft Visual Studio 2010 and using SQL Server database processing applications. The end result of system design is expected to help minimize the accumulation of goods. © Published under licence by IOP Publishing Ltd.

关键词： Decision support systems

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Implementation of Dynamic Mutual Information and Support Vector Machine for Customer Loyalty Classification

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Journal of Physics: Conference Series 2019年第1期1338卷

作者： H Sulistiani K Muludi A Syarif Departement of Computer Science Faculty of Mathematics and Sciences Lampung University Jl. Sumantri Brojonegoro No.1 Bandar Lampung Indonesia 35145 Departement of Accounting Information System Faculty of Computer Science and Engineering Teknokrat Indonesia University Jl. ZA. Pagar Alam No. 9-11 Bandar Lampung Indonesia 35145

Fast Moving Consumer Goods (FMCG) is known one of the important industrial sectors worldwide. It includes household and personal care products as well as processed foods and beverages. Because of the tight competition company must develop good marketing strategies. So, it is important for the company to know customer loyalty and also to predict the income as reference in company development planning. Data mining now is becoming popular technique for predicting customer loyalty. One of the well known data mining strategies is retaining customer's strategy. In this paper, we would present a new model for predicting customer loyalty. The model is based on Dynamic Mutual Information and Support Vector Machine (DMI-SVM) to identify the relevant factors that affect the performance of the classification of customer loyalty. The comparison of two classification methods and several selected features is given to show the effectiveness of the methods. We validated the model by 10-fold cross validation method. Classification accuracy, precision, recall and f-measure are used to evaluate classifier performance on a test/hold-out sample. A result in this paper is shown that SVM method gives better performance accuracy than Naïve Bayes.

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Data Mining: The Classification Method to Predict the Types of Motorcycle Spare Parts to be Restocked

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IOP Conference Series: Materials science and engineering 2019年第2期662卷

作者： S L B Ginting Y R Ginting Sutono A Rakhman Computer System Study Program Faculty of Engineering and Computer Science Universitas Komputer Indonesia Jl. Dipati Ukur 112-116 Bandung 40132 Indonesia Department of Mechanical Engineering Universitas Riau Kampus Bina Widya KM 12 5 Simpang Baru Pekanbaru 28293 Indonesia

The research intends to create an application which is able to analyse sales data in a motorcycle company to predict the types of spare parts which should be stocked. This prediction is crucial since problems are often encountered while restocking. For instance, when there have been some imprecisions occurring in deciding regarding the types of spare parts to restock, the spare parts accumulate. It can cause inefficiency in terms of storage, the products quality deteriorates due to having been stored for too long, and sometimes the best-selling products are not available in the warehouse. This application is developed with Naïve Bayes Classifier (NBC) method which has a high accuracy in predicting future occurrences. This method works by calculating the probability value in each attribute class and determining the optimal probability value. From the test results, 4500 training data with 200 sample test data has 90% similarity with the results of the restock decision without application. For 500 test data, the similarity was 96%. It is proven that this method has a high accuracy so that it can help the decision makers solved the company problem in predicting the types of motorcycle parts to be restocked.

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Generation of four-wave mixing with highly sharp idlers using 2 mm home-made side-polished fiber deposited by ZnO nanorod

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Laser Physics 2018年第7期28卷 076205-076205页

作者： Safaei, R. Amiri, Iraj S. Sorger, Volker J. Azzuhri, S.R.B. Rezaei, M. Ahmad, H. Yupapin, P. Photonics Research Centre University of Malaya Kuala Lumpur50603 Malaysia Computational Optics Research Group Advanced Institute of Materials Science Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Applied Sciences Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Electrical and Computer Engineering George Washington University WashingtonDC20052 United States Faculty of Computer Science and Information Technology Department of Computer System and Technology University of Malaya Kuala Lumpur Malaysia

A side-polished fiber with embedded zinc oxide nanorods (ZnO-NRs) is proposed, fabricated, and tested to generate four-wave-mixing (FWM). The side-polished fiber is manufactured by polishing a conventional single mode fiber to completely remove 2 mm of its cladding and its core partially, after which the fiber is simply immersed into a solution consisting of ZnO-NRs and allowing it to dry. A pump and a signal wavelength of 1550 and 1551 nm are injected into the fiber and generate idlers at 1549 and 1552 nm which agree well with theoretical values. Our experimental results show that the optimum FWM range is determined to be a 6 nm shifted away from the pump wavelength and occurs in the pump and wavelength spacing as narrow as 0.1 nm. The proposed system allows for the easy integration of optically active materials into a fiber. © 2018 Astro Ltd.

关键词： Zinc oxide

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Market Basket Analysis Using Apriori and FP-Growth for Analysis Consumer Expenditure Patterns at Berkah Mart in Pekanbaru Riau

Market Basket Analysis Using Apriori and FP-Growth for Analy...

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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information systems, and Information Technology, WMA-Mathcomtech 2018

作者： Mustakim Herianda, Della Maulina Ilham, Ahmad Daeng Gs, Achmad Laumal, Folkes E. Kurniasih, Nuning Iskandar, Akbar Manulangga, Gloria Indra Iswara, Ida Bagus Ary Rahim, Robbi Puzzle Research Data Technology UIN Sultan Syarif Kasim Riau Indonesia Department of Information System UIN Sultan Syarif Kasim Riau Indonesia Informatics Department Universitas Muhammadiyah Semarang Semarang Indonesia Department of Management University of 45 Surabaya Surabaya Indonesia Department of Electrical Engineering Politeknik Negeri Kupang Kupang Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Informatics Department STMIK STIKOM Indonesia Denpasar Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia

Berkah Mart is one of the new minimarkets in Pekanbaru city which began to develop as a retail business to meet the needs of the community. In his operation, Berkah Mart still uses the traditional store management perception that the placement of product layout on sale shelves has not been through sales analysis. Existing products have not been reviewed from the consumer's point of view, whereas the marketing economics concept provides a variety of product and consumer management methods for business management in Berkah Mart, including market bucket analysis techniques and various itemset search algorithms. In this research, Market Basket Basket Analysis with FP-Growth algorithm is proposed to determine the layout and planning of goods availability. The application of FP-Growth algorithm proved to be useful in generating many and informative association rules to find out the consumer spending pattern at Berkah Mart in Pekanbaru. Moreover, from the rules of the customer association can be segmented separately to meet the specific needs of customers with cost-effective by using some special promotions for the general group. The experimental results show that FP-Growth algorithm can analyze quickly and efficiently informing consumer shopping pattern at Berkah Mart and can increase Berkah Mart revenue. © Published under licence by IOP Publishing Ltd.

关键词： Sales

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A novel approach based on deep learning techniques and UAVS to yield assessment of paddy fields 9

A novel approach based on deep learning techniques and UAVS ...

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9th International Conference on Knowledge and systems engineering, KSE 2017

作者： Tri, Nguyen Cao Duong, Hieu N. Van Hoai, Tran Van Hoa, Tran Nguyen, Vu H. Toan, Nguyen Thanh Snasel, Vaclav Faculty of Computer Science and Engineering Ho Chi Minh City University of Technology Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Viet Solutions of Information System Company Ho Chi Minh City Viet Nam Faculty of Electrical Engineering and Computer Science VSB-Technical University of Ostrava Czech Republic

ISBN: (纸本)9781538635766

Yield assessment is one of the main interests at regional and national levels of agriculture management. The accuracy of the assessment is not highly expected inherently and, moreover, some costly and sophisticated tools (e.g., satellite images) have been usually involved without a careful consideration of their investment. In this paper, a novel approach has been proposed orienting to farmers (especially in Southeastern Asia) who are only affordable for low cost and easy-to-use tools. With this vision, the paper presents an idea to co-operate certain, powerful and modern technologies–deep neural networks (DNNs) and unmanned aerial vehicles (UAVs)–with respect to solving the problem of yield assessment. The imagery of paddy fields acquired by UAVs at low altitudes is then used for training DNNs and assessing the yield of the paddy fields. Four DNN models are applied to figure out the most appropriate one for this approach. To test the applicability of the proposed approach, some experiments are conducted on a dataset which was collected at paddy fields in Tay Ninh province, Vietnam. The yield assessment is not directly predicted from DNNs, instead being achieved by a combination of the classification results and a bush-level yield estimation of agricultural experts in the fields. The paper indicates that the proposed approach is quite potential for precision agriculture, along with some remaining challenges. © 2017 IEEE.

关键词： Deep neural networks

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GAN2C: Information Completion GAN with Dual Consistency Constraints

GAN2C: Information Completion GAN with Dual Consistency Cons...

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International Joint Conference on Neural Networks (IJCNN)

作者： Lujuan Zhang Jun Li Tao Huang Zhenyuan Ma Zhiyong Lin Mukesh Prasad School of Mathematics and System Sciences Guangdong Polytechnic Normal University Guangzhou China School of Software and Center for Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia School of Computer Science Guangdong Polytechnic Normal University Guangzhou China

This paper proposes an information completion technique, GAN2C, by imposing dual consistency constraints (2C) to a closed loop encoder-decoder architecture based on the generative adversarial nets (GAN). When adopting deep neural networks as function approximators, GAN2C enables highly effective multi-modality image conversion with sparse observation in the target modes. For empirical demonstration and model evaluation, we show that trained deep neural networks in GAN2C can infer colors for grayscale images, as well as estimate rich 3D information of a scene by densely predicting the depths. The results of the experiments show that in both tasks GAN2C as a generic framework has been comparable to or advanced the state-of-the-art performance which are achieved by highly specialized systems. Code is available at https://***/AdalinZhang/GAN2C.

关键词： Image color analysis Gallium nitride Task analysis Neural networks Gray-scale Generative adversarial networks Probabilistic logic

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