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Experimental investigation of evolution of dynamics in short-resonant-cavity DFB laser with optical feedback

Optics & Laser technology 2025年 191卷

作者： Wenchao Chen Yuanyuan Guo Zhiwei Jia Longsheng Wang Anbang Wang Yuncai Wang Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan University of Technology Taiyuan 030024 China College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan 030024 China Key Laboratory of Photonic Technology for Integrated Sensing and Communication Ministry of Education Guangdong University of Technology Guangzhou 510006 China Guangdong Provincial Key Laboratory of Information Photonics Technology Guangdong University of Technology Guangzhou 510006 China Institute of Advanced Photonics Technology & School of Information Engineering Guangdong University of Technology Guangzhou 510006 China

We conducted experiments to investigate the evolution of dynamics in short-resonant-cavity distributed feedback laser subject to optical feedback. Results reveal that the transition of the laser into chaos involves a regular switching between the stable state and quasi-periodic state. When exiting the chaotic state, the laser exhibits a switching between stable state and chaotic state, ultimately evolving into feedback locking. A new dynamic evolution path of the DFB laser has been proposed: stable state → switching between the stable state and quasi-periodic state → quasi-periodic state → chaotic state → switching between stable state and chaotic state → feedback locking. The influences of feedback strength on the duty cycle of quasi-periodic oscillation are examined. Moreover, a mapping of dynamics with respect to feedback strength and bias current is presented.

关键词： Distributed feedback lasers

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Attribute Rule performance in Data Mining for Software Deformity Prophecy Datasets Models

Attribute Rule performance in Data Mining for Software Defor...

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Advances in the Emerging Computing Technologies (AECT), International Conference on

作者： Salahuddin Shaikh Liu Changan Maaz Rasheed Malik School of Control & Computer Engineeringt North China Electric Power Universty Beijing China dept. of Information Communication Engineering Guilin University of Electronic Technology Guilin China

ISBN: (数字)9781728144528

ISBN: (纸本)9781728144535

In recently, all the developers, programmer and software engineers, they are working specially on software component and software testing to compete the software technology in the world. For this competition, they are using different kind of sources to analysis the software reliability and importance. Nowadays Data mining is one of source, which is used in software for overcome the problem of software fault which occur during the software test and its analysis. This kind of problem leads software deformity prophecy in software. In this research paper, we are also trying to overcome the software deformity prophecy problem with the help of our proposed solution called ONER rule attribute. We have used REPOSITORY datasets models, these datasets models are defected and non-defected datasets models. Our analysis class of interest is defected models. In our research, we have analyzed the efficiency of our proposed solution methods. The experiments results showed that using of ONER with discretize, have improved the efficiency of correctly classified instances in all. Using percentage split and training datasets with ONER discretize rule attribute have improved correctly classified in all datasets models. The analysis of positive accuracy f-measure is also increased in percentage split during the use of ONER with discretize but in some datasets models, the training data and cross validation is better with use of ONER rule attribute. The area under curve (ROC) in both scenarios using ONER rule attribute and discretize with ONER rule attribute is almost same or equal with each other.

关键词： Software Data mining Deformable models measurement Data models Object oriented modeling Testing

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Attribute rule performance in data mining for software deformity prophecy datasets models

Attribute rule performance in data mining for software defor...

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2019 International Conference on Advances in the Emerging Computing Technologies, AECT 2019

作者： Shaikh, Salahuddin Changan, Liu Malik, Maaz Rasheed North China Electric Power Universty School of Control Computer Engineeringt Beijing China Guilin University of Electronic Technology Dept. of Information Communication Engineering Guilin China

ISBN: (纸本)9781728144528

关键词： Data mining

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Research on Deep Reinforcement Learning Exploration Strategy in Wargame Deduction 2

Research on Deep Reinforcement Learning Exploration Strategy...

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2nd IEEE International Conference on Information Systems and Computer Aided Education, ICISCAE 2019

作者： Shang, Tongfei Dong, Haoyang Liu, Jing Yu, Yuan National University of Defense Technology College of Information and Communication Xi'an China School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China Army Engineering University of PLA College of Command and Control Engineering Nanjing China Xi'An Satellite Control Center Xi'an China

ISBN: (纸本)9781728130668

The wargame deduction is the application of wargame. It refers to the use of boards and wargame pieces representing the battlefield and its military power, or based on the virtual battlefield environment and force of the computer, based on military rules and probability theory, simulating war confrontation. The process deduction and evaluation optimization of the combat plan is an activity that uses wargame to simulate war and is a tool for combat simulation. In this paper, the actual or assumed situation is used to simulate the military actions of two or more opposing parties. The deep reinforcement learning and exploration strategy is used to improve the realistic function of the wargame simulation and the deductive pushability function, and systematically study the wargame technology. Advancing operational decision-making and military training has certain practical and strategic significance. © 2019 IEEE.

关键词： Reinforcement learning

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Research on Evaluation Method of Wargame Strategy Based on Fuzzy Petri Net 2

Research on Evaluation Method of Wargame Strategy Based on F...

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2nd IEEE International Conference on Information Systems and Computer Aided Education, ICISCAE 2019

作者： Shang, Tongfei Dong, Haoyang Han, Kun Li, Gang National University of Defense Technology College of Information and Communication Xi'an China School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China Army Engineering University of PLA College of Command and Control Engineering Nanjing China Xi'An Satellite Control Center Xi'an China

ISBN: (纸本)9781728130668

Wargame can effectively improve the fidelity and efficiency of combat deduction, and has the ability to solve complex military problems. It is theoretical and military significance to carry out the research on the development and application of computer wargame system. In this paper, the method of knowledge representation and reasoning of fuzzy Petri nets is applied to the strategy of wargame deduction. The characteristics of the graphs are used to represent different variables with different symbols, which can form a concise PN map. This PN map can be used for the force representation and reasoning strategy in the wargame system. The results show that the Petri net-based knowledge representation and reasoning algorithm is very effective for the wargame strategy. © 2019 IEEE.

关键词： Petri nets

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Erratum: An improved point spread function for complex susceptibility-based magnetic particle imaging (2022 Meas. Sci. Technol. 33 095402)

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measurement Science and technology 2023年第7期34卷 079601-079601页

作者： Tao Jiang Wentong Yi Zhongzhou Du Wenzhong Liu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 People’s Republic of China China-Belt and Road Joint Laboratory on Measurement and Control Technology Wuhan 430074 People’s Republic of China School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou 450001 People’s Republic of China

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Study on Subjective Perception of S3D Image with Regular-texture

Study on Subjective Perception of S3D Image with Regular-tex...

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IEEE Joint International Information technology and Artificial Intelligence Conference (ITAIC)

作者： Zhibin Su Bing Liu Weiwei Li Hui Ren Rui Huang School of Information and Communication Engineering Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China CITVC KEHUA CO. LTD. Technology Service Branch Beijing China

ISBN: (数字)9781728152448

ISBN: (纸本)9781728152455

With the rapid development of binocular stereo vision technology, S3D images and videos have been widely used in many aspects. However, there are few researches on the detail perception of comfortable experience and stereo sense based on image content with certain disparity. Considering that texture is an important visual information contained in an image, in this paper, we designed the computer-generated S3D images containing two kinds of parallax based on three types of texture distribution and six regular textures for subjective evaluation. The influence of texture features on visual comfort, depth perception and the region of interest were studied through the related data analysis. For comparison with the content of disparities, the 2D images with same texture were designed and rated for assessment. Experimental results have shown that the texture was an important factor affecting the comfort perception. However, only when the subject and the background had texture at the same time, the texture was an important factor affecting the depth perception. The different texture distribution between the main subject and background would cause the change of area of interest and evaluation result. Overall, the larger the area of the texture, the lower the comfort evaluation results, and the higher the depth perception. Our studies will not only confirm the law of perception on S3D images with certain features, but also provide the guide for multidimensional content production and display, which have practical value for the development of S3D image and video technology.

关键词： Wavelet transforms Visualization Data analysis Three-dimensional displays Two dimensional displays Feature extraction Videos

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Optimizing the teaching efficiency of english classrooms in colleges and universities based on deep learning

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AIP Conference Proceedings 2024年第1期2937卷

作者： Y. Dileep Kumar M. Praveen Kumar A. Mahesh Reddy G. Vamsi Krishna G. V. Sunil Kumar Department of Electronics & Instrumentation Engineering SreeVidyanikethan Engineering College A. Rangampeta Tirupati-517102 India. Department of Control & Automation School of Electrical Engineering VIT University Katpadi Vellore 632014 Tamilnadu India. Department of Electronics &Communication Engineering Sri Venkatesa Perumal College of Engineering & Technology Puttur-517583 India. Department of Electronics & Instrumentation Engineering Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology Chikkadapally Hyderabad500020 India. Project Manager Involute Automation (P) Ltd Balanagar Hyderabad-500037 Telangana India

An accurate assessment of the quality of English classroom instruction is essential for moving English education reform forward while also raising English education standards in Chinese colleges. A comparison model for evaluating the quality of English classroom teaching is built using SVM-LM (Support vector machine-Learning Machine) model together with Particle Swarm Optimization (PSO). The SVM-LM approach reduces the need for experiment samples while enhancing model fit because fewer hidden layer neurons are required for accuracy. According to results from experiments, utilizing the SVM- LM algorithm to assess English classroom instruction is a realistic option. Consequently, the study created English classroom teaching effectiveness index system has been successful and is intended to increase the standard of English language classroom instruction as well as how it is administered. The study results proved that the proposed algorithm works better than PSO.

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Application of trend surface analysis in early warning model of coal mine gas explosion 4

Application of trend surface analysis in early warning model...

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2018 4th International Conference on Energy Equipment Science and engineering, ICEESE 2018

作者： Sun, Yuhang Tang, Shoufeng Tong, Ziyuan Tong, Minming Xu, Chaoliang China University of Mining and Technology School of Information and Control Engineering Xuzhou221000 China University of New South Wales School of Communication and Electricity NSW1466 Australia Xuzhou Hanlin Technology Co Ltd. Xuzhou221000 China

Aiming at the catastrophic problem of common coal mine gas explosion, this paper combines the trend surface analysis method to establish a gas explosion warning model, and validates the model through actual data, and the model has good robustness. Through the data fusion of the comprehensive information of gas explosion, the gas and oxygen concentration are selected as the key indicators of the early warning model, and the trend surface analysis of the finite discrete data is established. The trend surface warning model of gas and oxygen concentration is established, and the distribution of key indicators is obtained. Features that enable predictions and warnings of potential gas hazards. © Published under licence by IOP Publishing Ltd.

关键词： Coal mines

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Lightweight Distributed Attribute Based Keyword Search System for Internet of Things 1

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12th International Conference on Security, Privacy, and Anonymity in Computation, communication, and Storage, SpaCCS 2019

作者： Long, Jiahuan Zhang, Ke Wang, Xiaofen Dai, Hong-Ning School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China Science and Technology on Electronic Information Control Laboratory Chengdu610000 China Department of Information Technology Macau University of Science and Technology Macau China

ISBN: (数字)9783030249007

ISBN: (纸本)9783030248994

Internet of Things (IoT) is a promising networking paradigm that connects various kinds of sensors and exchanges data from smart devices. Since IoT always related to user’s daily life, the problems of security and privacy are of great importance. Presently, the attribute based encryption (ABE) is a popular solution to guarantee the fine-grained sharing of encrypted data in IoT. In this paper, an attribute based keyword search with lightweight decryption in multi-authority (ABKS-LD-MA) is proposed. Our system supports multi-keyword search in cloud by using searchable attribute based encryption. We also integrate the lightweight decryption to searchable ABE scheme that largely reduces the computing overhead for users. Furthermore, our ABKS-LD-MA scheme supports multi-authority scenario, which is more adaptive to the real IoT environment. The experiment analysis shows that our scheme has relatively lowered the communication cost on IoT devices. © 2019, Springer Nature Switzerland AG.

关键词： Internet of things

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