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intelligent Modeling and Optimization for Smart Energy Hub

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2019年第12期66卷 9898-9908页

作者： Liu, Tianhao Zhang, Dongdong Dai, Hang Wu, Thomas Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Xi An Jiao Tong Univ Sch Elect Engn Xian 710049 Shaanxi Peoples R China Univ Wisconsin Dept Elect & Comp Engn Madison WI 53706 USA Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA

This paper proposes an intelligent modeling and optimization method to set up the smart energy hub model for the multiple energy system and optimize the operation of its associated energy hub model automatically. The core idea of the proposed method is to divide the complex energy hub model into several simple energy hub models. In this paper, the proposed computerized algorithm, which is applied to the smart energy hub model division, includes an energy loop intelligent searching method, a real nodes arrangement method, and a virtual nodes insertion method. One case study for the multiple energy system of a residential district in Guangzhou city is performed to validate the effectiveness of the proposed method. Compared with the traditional calculation method, the proposed method guarantees global optimal operation decision for the whole multiple energy system and the computational burden is significantly reduced.

关键词： Coupling matrix demand response energy management energy storage intelligent algorithms multiple energy system (MES) smart energy hub (S. E. Hub)

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Real-time bio-signal-processing of students based on an intelligent algorithm for Internet of Things to assess engagement levels in a classroom

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2018年 86卷 716-722页

作者： Kim, Pyoung Won Incheon Natl Univ Coll Educ Dept Korean Language Educ 12 Gaetbeol Ro Incheon South Korea

The level of student engagement refers to the degree of immersion of students during a class. This paper presents an intelligent algorithm that provides information to the teacher by measuring the level of engagement in real time. The Internet of Things (IoT) algorithm for assessing student engagement levels is presented in this study, evaluating the psychical state of students by measuring the electrodermal activity (or galvanic skin response). The algorithm proposed in this study is innovative in that it allows teachers to provide feedback to students while monitoring students in real time. This study provides a basis for IoT applications for teaching and learning. In particular, this study constructs a color fuzzy model to represent student engagement levels by saturation. An application on the teacher's mobile phone transforms like a chameleon, in real time, according to the immersion of students during class. If students learn this algorithm, they can monitor their own immersion levels. This is to encourage students to perform some kind of engineering thinking. (C) 2018 Elsevier B.V. All rights reserved.

关键词： intelligent algorithms Internet of Things Engagement Immersion Galvanic skin response Engineering thinking

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intelligent algorithm of geotechnical test data based on Internet of Things

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COMPUTER COMMUNICATIONS 2020年 158卷 32-38页

作者： Ma, Yawei Guo, Guihong Lanzhou Univ Sch Civil Engn & Mech Lanzhou 730000 Peoples R China Minist Educ Key Lab Mech Disaster & Environm Western China Beijing Peoples R China

In the geotechnical engineering geological survey industry, geotechnical test data is the basic data for analyzing and evaluating geotechnical engineering geology, forming reports, graphics, and survey reports. It plays an important role in the calculation of the bearing capacity, deformation calculation and physical and mechanical characteristics of the foundation soil. The purpose of this article is to solve the problems of tedious, inefficient and error-prone data collection, processing and analysis of geotechnical test data in the geotechnical and geological surveying industry of geotechnical engineering. By using the BP neural algorithm and selecting the intelligent algorithm, the SVM is used to solve the sample problem. The algorithm establishes an intelligent algorithm for geotechnical test data based on the Internet of Things. Then take the geological characteristics of the Ganjiang River Basin as an example, analyze the geotechnical test data to verify the feasibility of the intelligent algorithm for data analysis. The research results show that the algorithm realizes the automatic collection and processing of geotechnical test data, reduces the tester's workload and the influence of human factors on the test results, makes up for the shortcomings of traditional acquisition algorithm hardware fixation, and solves the problem of simultaneous multitasking. Difficult problems have promoted the development of innovative experiments.

关键词： Internet of Things Geotechnical tests intelligent algorithms Data analysis

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intelligent spectral signature bio-imaging in vivo for surgical applications

Intelligent spectral signature bio-imaging in vivo for surgi...

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Conference on Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues V

作者： Jeong, Jihoon Frykman, Philip K. Gaon, Mark Chung, Alice P. Lindsley, Erik H. Hwang, Jae Y. Farkas, Daniel L. Univ Southern Calif Dept Biomed Engn Los Angeles CA 90089 USA Cedars Sinai Med Ctr Minimally Invas Surg Technol Inst Los Angeles CA 90048 USA Cedars Sinai Med Ctr Dept Surg Los Angeles CA 90048 USA

ISBN: (纸本)9780819465542

Multi-spectral imaging provides digital images of a scene or object at a large, usually sequential number of wavelengths, generating precise optical spectra at every pixel. We use the term "spectral signature" for a quantitative plot of optical property variations as a function of wavelengths. We present here intelligent spectral signature bio-imaging methods we developed, including automatic signature selection based on machine learning algorithms and database search-based automatic color allocations, and selected visualization schemes matching these approaches. Using this intelligent spectral signature bio-imaging method, we could discriminate normal and aganglionic colon tissue of the Hirschsprung's disease mouse model with over 95% sensitivity and specificity in various similarity measure methods and various anatomic organs such as parathyroid gland, thyroid gland and pre-tracheal fat in dissected neck of the rat in vivo.

关键词： multi-spectral spectral signature intelligent algorithms K-Means hirschsprung's disease colon aganglionosis parathyroid gland thyroid gland

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Performance of different Electric vehicle Battery packs at low temperature and Analysis of intelligent SOC experiment 13

Performance of different Electric vehicle Battery packs at l...

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13th International Conference on Advanced Computational Intelligence (ICACI)

作者： Gao, Le Cai, Li Feng, Yuming Dai, Nina Xu, Qingshan Chongqing Three Gorges Univ Key Technol Lab Elect Vehicles Chongqing Peoples R China Chongqing Three Gorges Univ Sch Three Gorges Artificial Intelligence Chongqing Peoples R China Southeast Univ Sch Elect Engn Nanjing Peoples R China

ISBN: (纸本)9781665412544

This manuscript summarizes the SOC (State of charge) estimation methods of electric vehicle battery packs at low temperature, analyzes the performance of common battery packs of electric vehicle and the influence of low temperature, introduces the traditional SOC estimation method and the emerging cryogenic intelligent lifting algorithms, and summarizes their advantages and disadvantages. Combined with intelligent algorithm and battery model, the development of SOC estimation of battery packs at low temperature is prospected.

关键词： Electric vehicle Low temperature performance State of charge Battery packs intelligent algorithms

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Research on the Influence of Object Recognition Based on intelligent Algorithm on Staff's Anxiety 22nd

Research on the Influence of Object Recognition Based on Int...

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22nd IFIP TC 14 International Conference on Entertainment Computing (ICEC)

作者： Zhang, Lingyan Yao, Cheng Huang, Lanqing Ying, Weiqiang Ying, Fangtian Zhejiang Univ Hangzhou Peoples R China Macau Univ Sci & Technol Macau 999078 Peoples R China

ISBN: (纸本)9789819982479;9789819982486

This study aims to investigate the influence of object recognition based on intelligent algorithms on staff's anxiety levels in professional settings. Anxiety was measured through self-report questionnaires and physiological indicators, while object recognition performance was evaluated based on the accuracy and speed of intelligent algorithm-based systems. The study provides insight into the potential impact of technology on mental health and offers suggestions for optimizing the implementation of intelligent algorithms in the workplace.

关键词： object recognition intelligent algorithms staff's anxiety artificial intelligence mental health

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An Integrated intelligent System for IoT Device Selection and Placement in Opportunistic Networks using Fuzzy Logic and Genetic Algorithm 31

An Integrated Intelligent System for IoT Device Selection an...

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31st IEEE International Conference on Advanced Information Networking and Applications (IEEE AINA)

作者： Cuka, Miralda Elmazi, Donald Obukata, Ryoichiro Ozera, Kesuke Oda, Tetsuya Barolli, Leonard FIT Grad Sch Engn Higashi Ku 3-30-1 Wajiro Higashi Fukuoka 8110295 Japan FIT Dept Informat & Commun Engn Higashi Ku 3-30-1 Wajiro Higashi Fukuoka 8110295 Japan

ISBN: (纸本)9781509062317

The Internet is dramatically evolving and creating various connectivity methodologies. The Internet of Things (IoT) is one of these methodologies which transform current Internet communication to Machine-to-Machine (M2M) basis. The IoT can seamlessly connect the real world and cyberspace via physical objects that are embeded with various types of intelligent sensors. The opportunistic networks are the variants of Delay Tolerant Networks (DTNs). These networks can be useful for routing in places where there are few base stations and connected routes for long distances. In an opportunistic network, when nodes move away or turn off their power to conserve energy, links may be disrupted or shut down periodically. These events result in intermittent connectivity. When there is no path existing between the source and the destination, the network partition occurs. Therefore, nodes need to communicate with each other via opportunistic contacts through store-carry-forward operation. In this paper, we present the design of an integrated intelligent system for IoT device selection and placement in opportunistic networks using Fuzzy Logic and Genetic Algorithm. We introduce the system structure and present in details the design and implementation issues.

关键词： IoT Opportinistic Networks intelligent algorithms Fuzzy Logic Genetic algorithms WSNs intelligent Systems

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intelligent Mutation Operator of Biogeography-Based Optimization Algorithm

Intelligent Mutation Operator of Biogeography-Based Optimiza...

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2nd International Conference on Industrial Informatics - Computing Technology, intelligent Technology, Industrial Information Integration (ICIICII)

作者： Zhu, Chao Yang, Bo He, He Wu, Anqi Zheng, Qi Wuhan Univ Technol Sch Automat Wuhan 430070 Peoples R China

ISBN: (纸本)9781509035755

The mutation operator of Biogeography-Based Optimization (BBO) makes a large advance for the diversity of the solution space. Generally speaking, the quality of a solution is closely related with the maximum mutation rate, which is always decided by experience. But for the different situations, the maximum mutation rate may be different. In this paper, we propose an intelligent Mutation Operator of Biogeography-Based Optimization (IMOBBO), which could find the suitable maximum mutation rate in overall benign ranges. Extensive simulation results are provided to demonstrate the effectiveness and the sharpness of the algorithm.

关键词： intelligent algorithms biogeography-based optimization mutation solution space

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intelligent system of a numerical integration problem generator with gamification to ensure the ethics of academic work

Intelligent system of a numerical integration problem genera...

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IEEE International Symposium on Technology and Society (ISTAS)

作者： Pablo Leyva, Hugo Silva Lopez, Rafaela Blanca Metropolitan Autonomous Univ Dept Syst Mexico City DF Mexico Metropolitan Autonomous Univ Dept Informat & Commun Syst Lerma De Tejada Mexico

ISBN: (纸本)9798331540715;9798331540708

A problem that occurs every school period in a numerical methods course is the generation of problems. Problems are required for class examples, assignments, or exams. A wide variety of problems is needed to prevent students from having the answers before the problems are even assigned by the teacher. Preventing this is important to ensure the validity of the problems used as an assessment tool. The problems should have their answer, in addition to their solution, which can be found in a similar time to that given to solve an exam. This paper presents a problem generator for the topic of numerical integration. The developed software allows the generation of a large number of problems with the respective answer, so that the student can solve them in the time given to take the exams. One approach to teaching a course is gamification, which involves using a game environment in contexts as varied as business or education, among many others. The generated problems are numerical integration problems that are interpreted in a gamified context. The algorithms for the development of the software, the implementation, and the results regarding the generation of problems used in the numerical integration unit for the course of Numerical Methods in Engineering at the UAM Azcapotzalco are provided.

关键词： Higher education Ethics in Education e-learning problem generator with solutions numerical integration gamification intelligent algorithms problem-based learning

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Securing Public Places using intelligent Motion detection

Securing Public Places using Intelligent Motion detection

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IEEE International Conference on Engineering Education - Innovative Practices and Future Trends (AICERA)

作者： Rajpurohit, Arvind Agarwal, Ankit Gaikwad, Mayur Garg, Kapil Inamdar, Vahid Univ Pune Dept Comp Sci & Informat Technol Pune Maharashtra India

ISBN: (纸本)9781467322676;9781467322683

Human motion detection is a fundamental task for many computer vision tasks. In today's competitive environment, the security concerns have grown tremendously. It is imperative for one to be able to safeguard one's property from worldly harms such as thefts, destruction of property, people with malicious intent etc. The most popular method for motion detection is background subtraction where a background model needs to be maintained. In this paper an entropy based method for human motion detection is described which makes no use of background model. The difference image between consecutive images are calculated and at each particular pixel, and a spatial-temporal histogram is generated by accumulating pixels in difference image. This histogram is then normalized to calculate entropy and the magnitude of entropy is used to denote the significance of motion.

关键词： Motion detection crime video monitoring surveillance intelligent algorithms

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